SLAS2023 International Conference and Exhibition

The SLAS2023 course package contains presentations from the following tracks:

Keynote Speakers
Assay Development and Screening
Automation Technologies
Micro- and Nano Technologies
Advances in Bioanalytics and Biomarkers
Cellular Technologies
Data Science and AI
Precision Medicine and Diagnostics 
New Modalities
Ignite Theater
Poster Theater
Solutions Spotlight
Exhibitor Tutorials

The SLAS Scientific Program Committee selects conference speakers based on the innovation, relevance and applicability of research as well as those that best address the interests and priorities of today’s life sciences discovery and technology community. All presentations are published with the permission of the presenters.

SLAS Full Conference Attendees get full access to this content FREE. 

Adam Abate


University of California San Francisco

Adam R. Abate received an AB in Physics from Harvard College in 2002, a Masters in Physics from UCLA in 2004, and a PhD in Physics from the University of Pennsylvania in 2006. He returned to Harvard for a postdoc in Physics in the lab of David Weitz, working on a variety of topics in soft matter physics, chemical and microparticle synthesis, and microfluidics. While a postdoc, he developed a droplet-based microfluidic sequencer that became the foundation for the sequencing company GnuBIO. He has founded several additional companies, including Mission Bio, Fluent Bio, and Scribe Biosciences. He is a Professor at the University of California, San Francisco in the Department of Bioengineering and Therapeutic Sciences and an Investigator in QB3. His research interests are in microfluidics, single cell analysis, and genomics.

Sam Abraham

Nancy Allbritton, M.D., Ph.D.

Frank & Julie Jungers Dean of Engineering and Professor of Bioengineering

University of Washington

Nancy L. Allbritton is the Frank & Julie Jungers Dean of Engineering and Professor of Bioengineering at the University of Washington in Seattle (2019- current). From 2009-2019, she was the Kenan Professor of Chemistry and Biomedical Engineering and Chair of the Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill (UNC) and North Carolina State University (NC State). Her research focuses on the development of novel technologies for applications in single-cell analysis, micro-arrays and fluidics, and organ-on-chip and has resulted in over 180 full-length journal publications and patents and led to 15 commercial products. Four companies have been formed based on her research discoveries: Protein Simple (acquired by Bio-Techne in 2014), Intellego, Cell Microsystems (, and Altis Biosystems ( Dr. Allbritton is a Fellow of the American Association for the Advancement of Science, the American Institute for Medical & Biological Engineering, and the National Academy of Inventors. She obtained her B.S. in physics from Louisiana State University, M.D. from Johns Hopkins University, and Ph.D. in Medical Physics/Medical Engineering from the Massachusetts Institute of Technology, with a postdoctoral fellowship at Stanford University.

Green Ahn

Graduate Student

Stanford University

Green is a graduate student in Prof. Carolyn Bertozzi’s lab at Stanford University. She received her B.S. in biochemistry from University of Southern California and moved to Stanford to start her graduate studies in chemistry. Her research in the Bertozzi lab focuses on lysosome targeting chimeras (LYTACs) to degrade extracellular and membrane proteins via endolysosomal pathway.

Atham Ali

Ph.D. Student

University of Southern California

During my time at the University of California, Irvine I conducted research in the lab of Dr. Frederick Ehlert which involved analyzing the effect of muscarinic receptors in the heart. I also conducted research at Quest Diagnostics in the lab of Matthew Houston which involved examining the changes in serum proteins in patients infected with the dengue virus. Upon attending USC, I rotated in both Dr. Alachkar’s and Dr. MacKay’s research groups. This allowed me to utilize recombinant protein bioengineering from Dr. MacKay’s rotation and apply that to pharmacogenomics and leukemia projects studied with Dr. Alachkar. Thanks to both mentors, I now possess complementary techniques. More specifically, I can generate elastin like polypeptides fused to scFv domains that target FLT3 and CD99. Throughout my studies I gained a deep interest in immunology, and this sparked my interest in developing different immunotherapeutics to combat AML.

Courtney Anderson

Director, Product Marketing


"Courtney Anderson is director of product marketing at Deepcell in Menlo Park, California, which is leveraging high-speed cell imaging and AI to deeply characterize and analyze cell morphology. Prior to joining Deepcell, Dr. Anderson led spatial product marketing at 10x Genomics and before that she led the applications group at ACD focused on spatial biology. Dr. Anderson received her bachelor's degree in human biology from Brown University and her Ph.D. in molecular and developmental biology from UCSF, and completed her postdoctoral studies in metabolic biology at the University of California Berkeley. "

Mike Anscomb

Arndt Asperger

Senior Applications Scientist

Bruker Daltonics GmbH & Co. KG

Arndt Asperger is analytical chemist by training and got his PhD from Leipzig University in Germany. He joined Bruker in 2002 and has been working in various positions related to MALDI-MS applications and applications development. His current focus is on applications development and customre support of MALDI-MS based high-throughput methods.

Paul Auspitz

Director of Preclinical Solutions and Standards for Exchange of Nonclinical Data Services (SEND)

Xybion Digital

Paul Auspitz is a graduate of Thomas Jefferson University with a BS degree in Finance and IT Systems Management. He has a 25 year track record of success as a trusted digital solutions expert, and adviser to business leaders in highly regulated research driven organisations. Prior to his current role as Director of Preclinical Solutions and Standards for Exchange of Nonclinical Data (SEND) services for Xybion Digital he spent five years in a similar role with Instem, Plc and also has experience including SAP EWM, SCM and sterilization consulting as well as MS 365 Business and Operations solution sales. Paul Auspitz has spent eight years successfully helping organizations address and manage SEND across preclinical research and development businesses.

Jeff Baird

Business Development


"Jeff leads product and business development and customer support and success at Celltrio. He has three decades of experience innovating, developing, and delivering robotic automation for high-throughput, high-reliability applications in all industries including Life Sciences. His passion is to drive growth and innovation at Celltrio to establish global leadership in cell line automation and biobanking. 

Prior to joining Celltrio in 2018, Jeff held key roles in product and technology development including CTO at FP International, VP of Global Automation at Flextronics and VP of Engineering and Operations at Adept Technology. He has a B.S. degree in Electrical Engineering from the University of Kentucky."

David Baker

Associate Director


Dr David Baker earned his PhD from The University of Sheffield in 2015 for investigating the role of astrocytes in SOD1-related amyotrophic lateral sclerosis (ALS). Following a short post-doctoral spell, David joined the Cellular Assay Development team in AstraZeneca, initially supporting Neuroscience and Oncology projects but with an ever-growing interest in complex models and assays for Immuno-Oncology . In 2020 David secured a position specialising in assay development for cellular therapies and as of 2022 is leading a small team working on wide-ranging projects encompassing whole genome pooled and arrayed CRISPR screens through to bespoke co-culture models for immuno-oncology projects.

Michelle Balakrishnan

Hannah Barrett

Manuel Bauer

Felix Beltran

Regional Sales Representative

Refeyn Inc.

Felix Beltran is the Western US Sales Manager for Refeyn.  Felix started his commercial career in lab automation with emphasis in clinical diagnostics, and immunoassays.  Felix joined Refeyn because of their impressive, innovative technology in 2022.  Felix loves helping scientists by introducing new technology that makes their work easier – stop by the Refeyn booth for a chat.

Courtney Bennett

Anthony Berger

Field Application Scientist

CN Bio

Dr Anthony Berger is CN Bio’s US-based Field Application Scientist, providing support for the PhysioMimix™ Organ-on-Chip benchtop platform. Anthony has an extensive research background in 3D cell culture, biomaterials, and microfluidics, focusing on how the microenvironment influences cellular decision-making. He is a proponent of complex 3D in vitro models and desires to decrease the barrier to entry of these technologies. Anthony received his BS from Indiana University (US), PhD from the University of Wisconsin (US), and completed a postdoctoral fellowship at Temple University (US).

Ryan Bernhardt

Chief Commercial Officer


"Ryan Bernhardt is the Chief Commercial Officer for Biosero where he leads Business Development opportunities through strategic partnerships, collaborations, and commercial agreements to increase diverse market penetration for Biosero’s industry-leading Green Button Go automation scheduling software suite.

In this role, Ryan also oversees Biosero’s productization roadmap and strategic focus as it relates to Sales, Marketing, Customer Success, Applications, and Business Development.  Prior to joining Biosero, Ryan Bernhardt, spent the last six and half years at Eli Lilly and Company as the Global Discovery Automation Research and Technologies Group Leader, leading a team of automation engineers and scientists in the design, implementation, and operation of a variety of innovative automation initiatives across Research and Development Laboratories."

Donna Bibber


Isometric Micro Molding, Inc.


"With over 34 years of industry experience, Donna Bibber has developed thousands of miniaturized devices incorporating micro molding and automated assembly. Ms. Bibber received her Bachelor of Science in Plastics Engineering from the University of Massachusetts Lowell and is currently the CEO of Isometric Micro Molding, Inc. 

Ms. Bibber’s plastics engineering background, expertise and unique problem-solving skills have earned her an excellent reputation and national and international recognition for her work in micro manufacturing. She has been a featured speaker at medical and drug delivery conferences across the globe and has published countless technical papers on micro molding and micro assembly.

Her expertise in bioresorbable polymers and active ingredient combination devices, slow-release devices, ophthalmic devices and implants, glucose monitoring and insulin-delivery devices, neurological implants, biosensors, and oncology markers have given rise to many platform-type miniaturized devices commercially available today."

Karen Billeci

Senior Director, High Throughput Operation

Recursion Pharma

"Karen Billeci began her career at Genentech She have 19 years of experience developing cell based and biochemical assays to support process development, in vivo pharmacokinetic and pharmacodynamic studies, and in vitro molecular characterization in a GLP/GMP, clinical and research environment. Her work in this area has resulted in the lead or co-authorship of 14 publications, and 2 patents.

In 2008, her area of focus shifted to an operation role where she worked to develop automation and build efficiencies in lab processes to support high through put generic assays used to support stable cell line development and in vivo studies.  

In 2016 Karen continue to gain experience building high throughput operation at genomic engineer, CROs and diagnostic companies.  In 2022, Karen join Recursion where she has been to apply her background and experience to build a robust and stable phenomics high throughput operation."

Patrick Bingham

Principal Scientist


Patrick Bingham is a Senior Scientist in the Biochemistry Department of the Oncology Research Unit at Pfizer, Inc. Patrick has more than 20 years of experience developing and implementing biochemical and cell based assays for target identification and validation, screening and lead identification. Currently, Patrick uses Rapid Fire Mass Spectrometry along with traditional biochemical approaches to develop assays for evaluation of epigenetic and metabolism targets within oncology research enabling a deep understanding of target biology and model systems.  Patrick is an active member of The Society for Laboratory Automation and Screening and has presented his research and contributions to the field of Mass Spectrometry at past annual meetings.

Alan Blanchard

Matthew M. Boeckeler



Multifaceted, cross-functional leader who seamlessly meshes his scientific and automation background with his top-notch business education. Innovative visionary with 20 years of successive career advancement in the life sciences industry, focused on automated platform development, process improvement, and value chain optimization. Specialties: - Technology development and implementation - Automation systems, including design & fabrication - Innovative solutions, efficiency, and value creation - Compound management operations - Biobank operations - Staff development and cultivation - Cross-functional team building - Change management leadership - Lean Sigma analysis and implementation - Project Management - Product Development - Self-motivated innovation - Creative problem solving - (Calculated) risk taking - Thinking outside the box - Being able to see the big picture

James Bond

Glenn Brandon



Glenn Brandon, Chief Executive Officer and one of the founding members of SentrySciences, brings 30+ years of sales and service experience serving both the High Technology Electronics and Pharmaceutical Markets. Prior to SentrySciences, Glenn was the Global VP of Sales and Service for Particle Measuring Systems, Inc., responsible for a global network of sales and service offices focused on the Semiconductor, Data Storage and Pharmaceutical Markets. In this capacity, he oversaw both direct and indirect sales and service resources and was responsible for the development and execution of global sales and service strategies.

Jonathan Braverman

Principle Investigator

Innovative Genomics Institution

The Braverman lab at the Innovative Genomics Institute is beginning operations Q1 2023, focusing on developing precision organoid models across a number of health applications including cancer, infectious disease, and rare/neglected diseases. Research directions include studying the tissue-level biology of colon cancer with the aim of identifying synthetic vulnerabilities, developing organoid co-culture models to facilitate development of next generation immunotherapies, and leveraging CRISPRa/i tools to study host/pathogen interactions and therapeutically modulate immune responses.

Simon Briel

Global Product Manager

Beckman Coulter Life Sciences

Simon Briel holds a Master's degree in Applied and Molecular Biotechnology MS from RWTH Aachen University, Germany, and is currently pursuing a Master's degree MS in Management & Engineering from RWTH Aachen University Business School and the University of Cambridge. He began his career in research at Technical University of Berlin and joined Beckman Coulter Life Sciences in late 2019 as a Global Product Manager. In this role, Simon seeks to streamline users' needs, technical innovation and internal strategies. His aim is to aid the development and optimization of cell culture & microbial bioprocesses. In symbiosis with cell line and strain engineering this is posing a huge potential to drive innovation in biotechnology.

Megan Brock

Paul Brooks

Chief Executive Officer

CN Bio

"Paul is the CEO at CN Bio, having joined in 2022. He has over 25 years of experience in building businesses and leading high-performance research, product, marketing, and sales teams to develop and commercialize new biotechnology technologies globally for drug discovery, bioproduction and diagnostics.

Paul has held senior leadership positions in the USA and the UK, including Head of Business Operations and Managing Director of Horizon Discovery Ltd; Chief Commercial Officer and Executive Board member of Oxford Genetics Ltd; Head of Discovery Research Services at MilliporeSigma (Merck KGaA); and Global Marketing Manager at Sigma-Aldrich Corp. Paul has a BSc in Biochemistry from the University of Wales, a PhD in Molecular Biology from the University of Manchester Institute of Science and Technology (UMIST), and an MBA from the University of Nottingham Business School."

Cyrill Brunner

Application Specialist

Bruker Switzerland AG

Dr. Cyrill Brunner is a trained pharmacist and obtained his PhD at ETH Zurich in the group of Prof. Gisbert Schneider. His main background are numerous biophysical assays including SPR and computational drug design. He joined Bruker as application specialist in April 2020 and heads the SPR application lab in Fällanden, Switzerland.

Sheila Burns

Marybeth Burton

Executive Director, Discovery Sample Management

Merck and Co.

"Marybeth Burton is Executive Director, Discovery Sample Management at Merck in Rahway, NJ, USA.  Marybeth leads Merck’s global Discovery Sample Management and is responsible for small molecule and peptide compound management, high throughput purification, commercial chemical inventory management, and discovery chemistry operations.  Her group monitors compound collection quality and participates in efforts to continuously improve both stewardship and composition of Merck's small molecule compound collection.  Marybeth has been involved with process optimization efforts and development of new workflows to support changing sample management needs resulting from globalization of drug discovery efforts.  Marybeth and her team recently completed a multiyear major infrastructure upgrade which includes new automation platforms and processes for small molecule and peptide sample management.

Prior to her tenure at Merck, Marybeth led the compound management group at Schering-Plough.  Marybeth holds a B.A. in Biology and an M.S. in Information Science."

Jessica Bush

PhD Candidate

Scripps Research

My name is Jessica Bush, I am a fifth year PhD student in The Disney Lab at The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology (formerly The Scripps Research Institute). My work focuses on the identification of novel small molecules targeting pathogenic RNA structures to modulate downstream disease pathology and biological phenotypes. The majority of my PhD has been devoted to the identification of small molecules that target the stable r(G4C2)exp repeat hairpin in C9orf72 that has been identified as the most prevalent cause of heritable amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD).

Paul Butler

Senior Product Manager

Advanced Instruments / Artel

Jessica Callan

Alex Campos

A. Bjoern Carle

Scientific Affairs & Applications Manager

Artel Portfolio - Advanced Instruments

"Keeping a continual focus on optimizing laboratory productivity, particularly in an increasingly global environment, Bjoern has been contributing to the development of international standards for well over a decade. He is a technical expert contributing to the efforts of standards development committees of ISO, ASTM International, and CLSI. 

Filling a void in testing guidance for users of automated liquid handling systems, Bjoern was one of the industry experts who proposed the development of ISO/IWA 15. He then served as project leader and technical editor for the development of the ISO 23783 series of standards for automated liquid handling systems, which was published in August 2022.  

As technical expert, Bjoern has been contributing to the 2022 revision of the ISO 8655 series of standards, serving as lead author and project leader for the new Part 8 “Photometric reference measurement procedure for the determination of volume” and project leader and technical editor for the revision of Part 7 “Alternative measurement procedures for the determination of volume.” He is the lead author and project leader for the development of Part 10 “User guidance, and requirements for competence, training, and POVA suitability.” 

Bjoern serves as chair of the ASTM E41.06 subcommittee Laboratory Instruments and Equipment and was the project leader and technical editor for the 2022 revision of ASTM E1154 “Piston or plunger operated volumetric apparatus and operator qualification.” 

Coby Carlson

Director of New Technologies

FUJIFILM Cellular Dynamics

Head of Applications team at FUJIFILM CDI since 2012.

Rebecca Carlson

PhD Candidate

Broad Institute

Rebecca Carlson is a PhD candidate co-advised by Paul Blainey and Nir Hacohen at the Broad Institute of Harvard and MIT. She is completing a degree in Medical Engineering and Medical Physics in the Department of Health Sciences and Technology at MIT with a Concentration in Computer Science. She has also received a B.S. in Chemical Engineering from Michigan State University with a minor in Chinese.

Oneil Carter

Olivier Casamitjana

SVP, Global Sample Management Head


"Engineer by training in biological sciences, Olivier Casamitjana acquired 20 years of experience in the pharmaceutical industry. Successively at Pfizer and Solvay-Fournier, Olivier worked in the domains of assay development, high throughput screening and management of sample patrimony. Then Olivier worked within Sanofi during 10 years. He was successively project leader of large automated stores for compound management and of a LIMS’ implementation to manage the inventories, the workflows and the robotics interfaces. 

Olivier Casamitjana has been the global coordinator of the Sanofi compound management group, notably in charge of the strategy and key partnership and led the Toulouse Sample Management group during 8 years. Then, Olivier held an MBA program from Toulouse Business School and led, as a deputy, a technological & translational platform (integrated Drug Discovery), aiming at developing external business.

In 2015, Olivier joined Evotec and leads the screening and compound management department of Evotec France and he is part of the senior leader team in charge of the company’s strategy. In January 2017, he became SVP global head of compound management in charge of the business development and drive the operation in this domain. 

Active member of the club robotique and then ELRIGfr since 1999, Olivier has been elected in June 2013, president of Elrigfr (European Laboratory Robotics Interest Group – Francophone)."

Valarie Cassada

Jason Cassaday

Lead Automation Engineer


Lead Automation Engineer

Natalie Castellana


Abterra Biosciences, Inc.

Dr. Natalie Castellana is CEO of Abterra Biosciences in San Diego, CA.  She is passionate about mapping the natural immune response to challenge, particularly the relationship between the B-cell receptor repertoire encoded in B cells and secreted antibodies in serum.  Abterra Bio specializes in next generation antibody discovery and sequencing, leveraging machine learning to mine the immune repertoire of llamas, alpacas, rabbits, and humans.  She earned a PhD in Computer Science from the University of California - San Diego, and BS in Computer Science from Carnegie Mellon University.

Mike Anscomb

Daniel Badcock

Scientific Leader


Working at the interface between automation and biology for most of my scientific career, I have worked on high throughput systems in many settings, from early high throughput molecular biology platforms to my current role leading the High Throughput Antibody Expression team within Biopharm Discovery at GSK where the Small Scale Antibody Expression System is based.

Rebecca Berdeaux

Vice President of Science

CellChorus, Inc.

Rebecca Berdeaux, Ph.D., is Vice President of Science at CellChorus, the leader in dynamic single cell analysis. Using her expertise in dynamic cellular signaling and leadership of scientific teams, she is overseeing development of single-cell analysis assays for immunooncology and other areas of the life sciences. Dr. Berdeaux earned a B.S. in Biology from the University of Illinois Urbana-Champaign and a Ph.D. in Molecular and Cell Biology from University of California, Berkeley. Following postdoctoral work at the Salk Institute, she took a faculty position at the McGovern Medical School of University of Texas Health, Houston. Dr. Berdeaux’ academic research program focuses on molecular signaling mechanisms in type 2 diabetes and muscle regeneration. Her lab has created numerous conditional transgenic mouse models to cAMP signaling in physiological and pathophysiologic contexts, including mice for tissue-specific chemical-genetic activation of cAMP signaling and non-invasive bioluminescent imaging of cAMP-activated transcription in vivo. She is passionate about developing methods to visualize and rigorously quantify cell behavior at single-cell resolution. 

Samuel Berryman

PhD Candidate

University of British Columbia

I am a PhD candidate at the University of British Columbia developing single-cell assays paired with machine learning analytics. My career goal is to become a scientist and engineer in an industry-based institution in the field of cell biology. In my career, I aim to develop new single-cell screening technologies which will aid in understanding how, and to what end, sub-populations of cells and tissues respond to pharmaceutical intervention. To date, a significant number of pharmaceutical studies have focused on characterizing the bulk response of cellular and tissue groups to introduced therapeutics. However, these bulk screening methods assume that the cellular targets exhibit a homogeneous identity, which can lead to costly misalignments between in-vitro and in-vivo models. Shifting the discretization of pharmaceutical experiments from bulk to single-cells will aid in developing higher quality products, minimize therapeutic resistance, and expedite disease research.

Nick Bevins

Laboratory Director

Sequence Sciences

Dr. Bevins has two decades of experience in research, clinical medicine, and the life sciences industry. He earned a bachelor’s degree in biochemistry from Columbia University then completed the Medical Scientist Training Program (MD-PhD) and residency in clinical pathology (laboratory medicine) at the University of California, San Diego. For five years he served the biopharma and diagnostics industry as a management consultant specializing in clinical development and go-to-market strategy. Dr. Bevins has more than 40 peer-reviewed publications and abstracts in genetics, clinical chemistry, and laboratory utilization. He volunteers on the Economic Affairs Committee for the Association of Molecular Pathology. Dr. Bevins is currently a free-lance commercial strategy consultant and clinical laboratory director.

Sanjeev Bhavnani

Senior Medical Advisor


Sanjeev Bhavnani MD FACC is a Senior Medical Advisor for Digital Health at FDA's Center for Devices and Radiological Health (CDRH), where he is a senior clinical expert and subject matter expert related to digital health medical devices. In his role at the CDRH Digital Health Center of Excellence, Dr. Bhavnani provides leadership for digital health policy development, technologies including artificial intelligence, and design considerations for DHTs and AI/ML clinical investigations including hybrid, decentralized, and virtual care clinical trials. Prior to joining the Agency, Dr. Bhavnani was the founder and executive director of Healthcare Innovation at Scripps Clinic in San Diego, CA and led the development of clinical trials and patient care programs that evaluated the safety and effectiveness of DHTs, nanosensor devices, cloud-based analytical platforms, and handheld ultrasound.  Over more than a decade, Dr. Bhavnani served as principal investigator of 90 DHT and AI clinical trials and patient care programs that have enrolled over 30,000 patients in the US and in resource limited areas and successfully designed the first point-of-care methods for DHT used within clinical trials.  His team developed the SMART-FHIR integration interface for DHT data into EMRs for remote patient monitoring, deployed enterprise-wide telehealth during COVID-19 achieving 1M+ telehealth visitations and created a learning health system real-world data platform to monitor healthcare quality of DHT and ML devices. Dr. Bhavnani is a practicing cardiologist and has held various leadership positions at national professional societies, advisory boards, think tanks, and educational institutions and has trained a global consortium of innovation scholars towards the advances in digital health.

Marc Bickle, Ph.D.

Institute of Translational Bioengineering


Marc Bickle obtained his Ph.D. at the Biozentrum in Basel, Switzerland, studying the immunosuppressive drug Rapamycin in yeast. He studied the genetics of behavior in C. elegans at the LMB in Cambridge, UK. He then participated in the creation of Aptanomics a Biotech in Lyon, France. 

Chamath Chandrasekera

Scientist II


I am a research scientist at GenScript developing new DNA assembly paradigms that are suitable for automation. I am also optimizing the production of large numbers of plasmid for contract plasmid production and developing robotic platforms for this. Our goal is to use cutting edge DNA manufacturing protocols that scale up for producing vaccines, gene therapies and other CGT products.

Rajan Chaudhari

Computational Chemistry Scientist

Eurofins Discovery

Rajan Chaudhari is a Computational Chemistry Scientist at Eurofins Beacon Discovery in San Diego, CA. Chaudhari received his M.S. Bioinformatics degree in 2010 from the University of Sciences in Philadelphia and then his Ph.D. biochemistry (computational) in 2015 from the same institution. His doctoral work involved development of membrane protein structure prediction method and identification of novel GLP1R agonists. He completed postdoctoral training at University of Texas MD Anderson Cancer Center in Houston, TX, where he worked on variety of cancer therapeutic targets and modalities. Before joining Eurofins, Chaudhari worked as Senior Scientist at Lassogen, San Diego, CA, where he established computational chemistry capabilities and developed novel lasso peptide based preclinical candidates targeting GPCRs and integrins.

Shimul Chowdhury

Vice President of Laboratory Operations

ClearNote Health

Shimul Chowdhury has served as a clinical laboratory director in multiple laboratories including Rady Children’s Institute for Genomic Medicine (RCIGM), Illumina Inc. and Quest Diagnostics. He has dedicated his career to implementing new genomic technologies to improve patient care and outcomes. He is a board-certified clinical molecular geneticist and licensed as a laboratory director in California, Florida and New York.

Eric Chow, PhD

Adjunct Assistant Professor

Laboratory for Genomics Research, UCSF

Eric Chow is the Director of the UCSF Center for Advanced Technology and former Head of Technology at the Laboratory for Genomics Research a collaborative center between UCSF, UC Berkeley, and GSK. He currently directs the UCSF Center for Advanced Technology, a facility focused on NGS, single cell sequencing, and high throughput auatomation.

Beth Cimini, Ph.D.

Senior Group Leader

Broad Institute

Dr. Beth Cimini is a Senior Group Leader, CZI Imaging Scientist and head of the Cimini Lab in the Imaging Platform at the Broad Institute in Cambridge, MA.  She obtained a PhD in Biochemistry and Molecular Biology with Dr. Elizabeth Blackburn at UCSF, studying splicing variants of the telomere master scaffolding protein TIN2.  This work honed her interests in image analysis, leading her to postdoctoral and staff scientist roles with Dr. Anne Carpenter's lab at the Broad, leading a team collaborating with ~30 outside scientists per year on custom image analysis projects.  The Cimini lab focuses on bioimage analysis tool creation (Piximi) and maintenance (CellProfiler), as well as on applying open source tools to novel biological problems.  She created and directs the Platform's Postdoctoral Training Program in Bioimage Analysis, and also leads the Broad efforts towards community engagement and driving biological projects for the Center for Open Bioimage Analysis (COBA).

Filippo Cipriani

Principal Scientist

The New York Stem Cell Foundation Research Institute

"Filippo Cipriani, PhD, is Principal Scientist at The New York Stem Cell Foundation Research Institute working on the Diabetes team. The team’s research focuses on developing robust models of diabetes using Pancreatic organoids derived from patient induced pluripotent stem cells. He recently received a NYSCF – Druckenmiller Fellowship Award.

In 2019, Dr. Cipriani completed his PhD in Biomedical Research at the University of Valladolid (Spain). Prior to his PhD, he was a Marie Curie Fellow working as Associate Researcher in the field of microfluidics and microsensors in the IMSAS Group at the University of Bremen, Germany. He completed his Bachelor degree in Environmental and Industrial Biotechnology in 2010 at the Faculty of Science of the University of Florence, Italy, followed by a Master degree in Molecular and Industrial Biotechnology at the Faculty of Science of the University of Pisa, Italy."

Maria Clapes

Product Manager

SUN Bioscience

Maria Clapés holds an MSc in Bioengineering from the Federal Institute of Technology of Lausanne (EPFL). She joined the R&D department at SUN bioscience in 2020, where she established liver models on their proprietary platform, Gri3D®. In her current role as a Field Application Specialist, she supports sales and applications of SUN bioscience products. In a collaboration with Molecular Devices, she supports the experimental design and imaging on the SUN bioscience platform, Gri3D®, for human intestinal organoids.

Roger Clark

Associate Director

Charles River

"Roger is Head of High Throughput Screening (HTS) within Early Discovery at Charles River Labs (CRL). An experienced drug-discovery Bioscientist, Roger joined CRL in 2018 from AstraZeneca - where he had moved through various early discovery roles over ~19 years. His current remit sees him leading CRL’s HTS department - delivering assay development and execution of molecular target-based and phenotypic Hit ID campaigns for multiple client projects.

Over his pharmaceutical R&D career Roger has worked across many fields in early discovery including HTS, SAR Screening, High Content Biology and Laboratory Automation."

Joe Clayton

Global Scientific Program Manager

Agilent Technologies

Joe Clayton is the Global Scientific Program Manager within the Cell Analysis division at Agilent. He received his Ph.D. in Cell and Molecular Biology from the University of Vermont and a M.S. in Clinical Research and Informatics from Dartmouth College. Joe has nearly 20 years of experience in diverse life science research with an emphasis on imaging-based application development and emerging technologies. 

Brad Collier

Scientist III


Brad received his doctorate in biomedical engineering from Texas A&M University in 2013.  Holding several research positions, he has contributed to the development of a variety of analytical and microfluidic biotechnologies.  Since 2017, Brad has been working for Labcorp where he currently investigates and validates various novel capillary blood microsampling solutions as well as markers of neurodegeneration.

John Conway

Chief Visioneer Officer

20/15 Visioneers

John founded 20/15 Visioneers after spending 30 years in R&D Biopharmas, Scientific Software and Consulting orgnizations where he focused on science and technology, computational sciences, informatics and strategy.  John and his teams have brought several scientiifc software platforms to market and have constantly strived to make a difference to science understanding and informatics.

Emilio Cordova

Calvin Cortes

Senior Product Manager

Beckman Coulter Life Sciences

Patrick Courtney

Member Board of Directors

SiLA Consortium

Biography: Dr Patrick Courtney has 20 years industrial experience in technology development. He worked as Director for global firms such as PerkinElmer, as well as at Sartorius and Cap Gemini. He leads a European working group on analytical laboratory robotics and is member of board of directors of SiLA (Standards in Laboratory Automation). He holds an MBA with a PhD in Robotic Engineering/Molecular Biology, and has 100 publications and holds ten patents.

Claire Cox

Malcolm Crook

Technical Director

Peak Analysis and Automation (PAA)

I have a PhD in the synthesis of insect defence secretions.  Following 12 years at British Petroleum working on automated analytical processes and the development of a cartesian robot system & software, I cofounded Process Analysis & Automation.  Now over 30 years on, Peak Analysis & Automation are now part of the Directech Group of Companies still developing cutting edge laboratory automation hardware & software solutions for the pharmaceutical and biotechnology industries and academic and research institutes.

Alvaro Cuevas

Product Manager

Hamilton Company

"Software Product Manager at Hamilton Company in Reno, Nevada.

Alvaro has a bachelor´s in Biotechnology and has worked in the life science automation industry for over 17 years. He has occupied diverse roles on three continents as a distributor, product specialist, applications engineer, sales, sales manager, and product manager. He is an expert in Hamilton's software. "

Luigi Da Via

Team Leader - High Throughput Automation


"Luigi Da Via’ is a Team Leader in Analytical Development at GSK working in the high throughput automation group. 

He has a PhD in photochemistry and catalysis at the University of Liverpool (UK). In 2018 he was elected as a GSK Fellow which recognizes the top 5% R&D staff as established leaders of science and mentors.
His current research involves the design, development, and deployment of new automated workflows for the screening of physicochemical properties of new assets during preclinical drug development. 
His role is also focusing on establishing data management strategies to streamline the integration of robotic platforms and analytical instrumentation with the wider GSK IT infrastructure."

Robert Damoiseaux

Professor, Molecular and Medical Pharmacology and Director, Molecular Screening Shared Resource


Dr. Robert Damoiseaux’s main interests are at the interface of chemistry, biology and engineering and include the development of novel assay technology platforms, High Throughput Screening, High Content Screening and nanotechnology. After having earned a Ph.D. degree at the University of Lausanne (Switzerland) where he worked on directed molecular evolution of antibodies he joined the Novartis Institute for Functional Genomics (GNF) in La Jolla, CA in 2001. Since 2004 he is the Director of the Molecular Shared Screening Resources (MSSR) – a unique state of the art screening facility at the California NanoSystems Institute of UCLA where he directs all drug discovery as well as the functional genomics projects. His private research focuses on automation, novel assay systems and toxicological issues of small molecules and nano-materials and consults for the pharmaceutical industry and law firms as expert witness in patent litigation cases.

Libby Daniele

Customer Success Manager


Libby Daniele joined Quartzy as a Customer Success Manager in 2022 after working as a Researcher and Lab Manager in academic and industry settings for over 7 years. As a former Quartzy user, she understands the perspective and needs of scientists using the platform. She is excited to continue helping labs organize and streamline their work on a larger scale.

Anthony Davies

CEO, SSO Vale Life Sciences, lead: Advanced Cell Based Assay Consortium,AProf Trinity College Dublin

Vale Life Sciences, ACBAC, Trinity College Dublin.

"Prof Davies’ CEO Vale Life Sciences, Trinity College Dublin. 

Prof Davies has for the lattwo decades focused on the development of advanced in vitro cell-based models and the rapidly growing field of high content screening and analysis. 
 He has overseen and led the establishment of Research Centres in Europe and Oceania where his work was centred on understanding human disease. In 2005 he set up the Irish National Centre for High Content Screening and Analysis (INCHSA), based in the Department of Clinical Medicine at Trinity College Dublin, one of the first purpose built academic screening centres of its kind in Europe. Anthony has developed and commercialised a number of new technologies, most notably the worlds first liquid 3D cellular scaffold and solid-state Bioreactor technologies specifically designed for use in automated drug discovery. Prof Davies is now based in Brisbane Australia where he holds the position of CEO of Vale life Sciences who have developed a range of advanced cell culture technologies."

Marije de Boer

Christophe Deben

Group Leader Tumoroid Screening Lab

University of Antwerp

Dr. Christophe Deben is currently the head of the Tumoroid Screening lab at the University of Antwerp. In this position he combines his passion for cancer research with his interest in new technologies to develop more advanced 3D cancer models and automated drug screening assays. His team applies a multidisciplinary approach that combines cancer biology, live-cell imaging, and data science to find new combination strategies that target cancer cells more efficiently and to improve the prediction of a clinical response from ex vivo tumoroid drug screenings. As co-founder of Orbits Oncology, he aims to make advanced live-cell image analysis more accessible to academic researchers and facilitate the implementation of 3D cancer models. 

Mindy Decker

Susan DeLaura

Director, Technical Marketing

FUJIFILM Cellular Dynamics, Inc.

Dennis Della Corte


Prof. Dennis Della Corte leads the Life Science Analytics team as Chief Science Officer of ZONTAL and is the acting director of the Consortium of Molecular Design at Brigham Young University. His work is focussed on building the laboratory of the future,

Prof. Dennis Della Corte leads the Life Science Analytics team as Chief Science Officer of ZONTAL and is the acting director of the Consortium of Molecular Design at Brigham Young University. His work is focussed on building the laboratory of the future, through better datasets, algorithms, training strategies. Formerly, he worked at Bayer AG as Global IT Project manager and obtained a PhD in Computational Biophysics at FZ Jülich in collaboration with Stanford University. He also holds Master's Degrees in Biomedical Engineering and Medical Physics.

Daniela Dengler

Dr. Daniela Dengler has been a lead scientist in the assay development group of the Conrad Prebys Center for Chemical Genomics (CPCCG) at Sanford Burnham Prebys (SBP) Medical Discovery Institute since 2018. Prior to joining SBP, Dr. Dengler obtained her Ph.D. in Medicinal Chemistry at the Friedrich-Alexander University Erlangen-Nuremberg in Germany, where she focused on organic synthesis and structure-based design of small molecules targeting G protein-coupled receptors (GPCRs). In her current role, Dr. Dengler seeks to exploit the tremendous untapped therapeutic potential of GPCRs by developing and optimizing novel automation-friendly methods tailored to identify small molecules that act on challenging GPCR targets or exhibit unique pharmacological profiles, such as biased agonism and allosteric modulation, which she believes will ultimately result in more effective and safe therapeutics.

Marie Depresle

Engineer Assistant

BIORCELL3D Consortium

I’m Marie DEPRESLE, an engineer assistant in BIORCELL3D consortium in France, more precisely in Clermont-Ferrand. I graduated with a bachelor’s degree in biology five years ago. I have worked in cosmetic research in LVMH research center for a work-study contract and then in screening oncology field for a permanent contract. I mainly work in cell biology and fluorescence staining, and I am also responsible for our screening machines.

Nadia DeStefano

Dwayne Dexter

Director of US Sales and Operations

Inventia Life Science

Dwayne is a seasoned life science commercial professional with 22 years’ experience in delivering novel life science research solutions to the pharmaceutical, biotechnology, molecular diagnostic, and academic markets. As Director of Inventia US, he supports the commercialization and development efforts of the RASTRUM technology in North America. His scientific and business experiences have mainly focused on bringing innovative approaches and technologies to scientific problems. He has helped companies commercialize innovative technologies, including high-throughput drug screening products and services at Invitrogen and Bellbrook, high-content imaging platforms such as the GE In Cell and the Celigo imaging platform, single-cell isolation platforms from Menarini Silicon Biosystems, and most recently the Organ-On-a-Chip technology from Mimetas.

Yujia Ding


Representing myself

Dr. Yujia Ding (M.S., M.A.Ed., Ed.D.) is a STEM educator and disability advocate with a passion for sharing her love of biology with her students. She completed her Doctor of Education where she explores how to make STEM accessible to individuals with disabilities. Her personal experiences and her students motivate her to keep fighting every day, despite the challenges she faces. Dr. Ding was the Los Angeles Unified School District Rookie of the Year recipient for the 2020-2021 school year. In addition, she received Distinguished Teacher recognition from Dallas Independent School District for the 2022 - 2023 school year. She is a proud Northwestern University Alumna (B.A., M.S.) seeking to leave a positive impact for future generations of scientists. Dr. Ding strives to show her students nothing is impossible, the word itself spells "I'm possible".

Matt Dobbin

Market Manager

Araceli Biosciences

Matt is a passionate and experienced research scientist with a background in chromatin biology and a focus on advanced imaging techniques and the application of computational approaches towards looking at biological data. He earned his PhD from MIT where he developed and applied novel imaging-based approaches towards interrogating the DNA damage response in the nervous system. Matt has worked towards bringing high-content imaging platforms and their corresponding data analysis pipelines online at several startups and bio-techs while simultaneously gaining exposure to the client and business-facing side of science.

John Doench

Director R&D

Broad Institute

John Doench is the director of research and development in the Genetic Perturbation Platform of the Broad Institute of MIT and Harvard,. He provides expert guidance on the design, execution, and analysis of genetic screens. He has contributed to numerous publications in fields such as infectious disease, cancer biology, and immunology. Additionally, Doench leads a group focused on the development of functional genomic techniques, first with RNAi and more recently with CRISPR technology. Here, his team demonstrated the potential of genetic screens with CRISPR and has since developed leading bioinformatics tools and screening libraries to enable community-wide usage of this powerful technology. Importantly, their efforts emphasize not only staying on the cutting edge of the newest approaches, but also focusing on making technologies widely available and useful, which is critical for enabling collaboration with a broader community of researchers working in diverse and challenging model systems.

Lupway Doh

Lauren Dostillo

Regis Doyonnas

High Content Screening Lab Head, Primary Pharmacology Group


Audrey Dubourg

Product Manager

CN Bio

Dr Audrey Dubourg is CN Bio’s Product Manager for the PhysioMimix™ OOC range of microphysiological systems. Prior to joining CN Bio, she worked as a postdoctoral scholar at the University of California – Los Angeles (UCLA), in the US, in the Microbiology, Immunology and Molecular Genetics department. She completed an MSc in microbiology at the University of Montpellier II (France), followed by a PhD in microbiology/parasitology at the University of East Anglia (UEA), in the UK. Audrey has extensive experience in the disciplines of molecular biology and 3D mammalian cell culture. Since joining CN Bio, she has been actively involved in promoting the benefits of incorporating organ-on-a-chip technology into drug discovery and development workflows.

Frans-Willem Duijnhouwer

Presales Consultant

USoft B.V.

After studying Natural Sciences and Business & Administration at Utrecht University, Frans-Willem Duijnhouwer started his career at Capgemini as an internet consultant, after which he continued as an entrepreneur in IT. Through a startup in web archiving and a role as a project manager at Uselab, he and a partner started a company for mobile app development, called Mobile Agency. In addition, he has developed and sold an IOT platform at EasyIQ. In 2020, Frans-Willem started working at USoft, where he works with former Capgemini colleagues in the sales department. With his broad knowledge of ICT, Frans-Willem, in his role as pre-sales/business consultant, knows how to translate specifications into solutions for core systems based on a low code development methodology.

Thomas Durcan

Associate Professor, McGill University; Director, The Neuro’s Early Drug Discovery Unit (EDDU)

The Neuro`s Early Drug Discovery Unit (EDDU), McGill

Originally from Dublin, Ireland, I have been at The Neuro for over 15 years. As an Associate Professor at The Neuro and McGill University, my research focus is on applying patient-derived stem cells towards the development of phenotypic discovery assays and 3D brain organoid models for both neurodegenerative and neurodevelopmental disorders. As director of the Early Drug Discovery Unit (EDDU) at The Neuro, I oversee a team of over 45 research staff and trainees, committed to applying novel stem cell technology, combined with CRISPR genome editing, mini-brain models and new microfluidic technologies towards elucidating the underlying causes of these complex disorders. Integrating new approaches in the group towards building MultiOmics profiles on the patient-derived IPSC cells, the long-term strategy is to identify new personalized precision therapies that can be applied towards building clinical trials on a dish.

Nick Edwards

Director, Business Development and Strategic Accounts

Science Exchange

Nick Edwards, PhD is a Director of Business Development and Strategic Accounts at Science Exchange, an R&D services marketplace. He works with biotech companies to strategically make science move faster by improving outsourcing efficiency. Nick completed his PhD in Neuroscience at Brown University and a postdoc at UCSD. After working as a consultant at BCG, he spent time in commercial strategy and operations at Illumina. During his time at Resilience and Alloy Therapeutics, Nick gained firsthand experience in building and operating fast-scaling research organizations. Outside of his day job, Nick is a passionate advocate for science communication and careers. He hosts the Once a Scientist podcast, where he interviews scientists across diverse industries and functional roles to help early career researchers understand industry and academic career options.

David Egan, Ph.D.


Core Life Analytics

"David Egan is the co-founder and CEO of Core Life Analytics, a Netherlands-based company that helps biologists to analyze their own data. Born in Carrickerry, Ireland, he completed his undergraduate training in Industrial Chemistry at the University of Limerick. He received his Ph.D. in 1997 from Cornell University Graduate School of Medical Sciences in New York, NY. 

After a post-doctoral fellowship at The Salk Institute in La Jolla, CA, and a position at OSI Pharmaceuticals in NY, he returned to Europe in 2003. In Utrecht, The Netherlands, while managing the Cell Screening Core at the Department of Cell Biology, he encountered the challenges of data analytics in phenotypic screening. This led to the development of the StratoMineR data analytics platform with Wienand Omta and the subsequent establishment of Core Life Analytics in 2016. Since then StratoMineR has been widely adopted in big pharma, biotech, and academic centers.

As part of the next stage of its development Core Life Analytics is launching the StratoVerse, a complete end- to-end, cloud-based, high-content analysis platform. It offers image storage in StratoMineR, high-performance image analysis in StratoScale, and downstream data analytics in StartoMineR, the current product."

Elizabeth Eldredge

Richard Ellson


Beckman Coulter Life Sciences

R&D molecular diagnostics professional, 10+ years of experience, with drive for results, known for high productivity and delivering products, from concept through commercialization, to market in time. Extensive
knowledge of molecular biology high throughput laboratory systems and CLIA lab operations, analytical assay validation and clinical studies to supporting clinical utility for LDTs. Enthusiastic about learning and enabling tools and solutions contributing to the improvement of human health.

Pat Escaron

Principal Sales Specialist


Patrick has spent 25 years in biotech, with 11 years directly supporting the PerkinElmer Drug Discovery Reagent portfolio in various Western US regions, namely the San Francisco Bay Area and San Diego. Patrick’s experience spans early discovery assay development for HTS and SAR campaigns, to method development for biomarker analysis in clinical studies.

Yaw Etse

VP of Engineering and Lab Innovation


"Yaw Etse is the Vice President of Engineering and Lab Innovation at Invitae. His strategic focus is next-generation and fully autonomous lab operations, machine learning, and predictive analytics. In this role, Yaw leads scientists and engineers to build fully autonomous platforms, automated assay testing and virtualization, digital twin, continuous integration, and deployment of fully automated next-generation sequencing-based assays.

Yaw previously led platform engineering and the health care provider experience and engineering at Invitae.

Before joining Invitae, Yaw was the CTO of Promise Financial and Repetere and previously led engineering teams at American Express and Capital IQ.

He has a bachelor's degree from Cornell University and pursuing a Master's in Computer Science and Machine Learning from Johns Hopkins University."

Kenda Evans

Automation Workflow Specialist

Agilent Technologies

Dr. Evans received her Ph.D. in Pharmacology from The University of Texas Health Science Center at San Antonio focusing on Serotonin 1A receptor pharmacology. She did a post-doc at the University of Houston, College of Pharmacy and Pharmaceutical Sciences concentrating on cardiovascular and respiratory pharmacology. Kenda joined Encysive Pharmaceuticals in the high throughput screening lab where she worked through many screening campaigns and had specific project management responsibilities. After 5 years with Encysive Pharmaceuticals, she joined PerkinElmer as a field application scientist with the high throughput screening reagents and plate readers group. In 2011 Kenda joined Agilent Technologies as a product specialist in the automation workflow group. Recently Kenda took on a new role as the Applications Workflow Specialist for the Automation Team where she continues to work to build out new applications using the Bravo liquid handler, AssayMAP Bravo and the Metabolomics Bravo for automated sample preparation.

Tiffany Fabianac

Enterprise Data and AI Engagement Lead


Tiffany Fabianac started her career as a molecular neurobiologist focused on understanding the molecular mechanisms controlling peripheral nerve development and the development of Neurofibromatosis Type 2 therapies. She went on to manage 2 cellular and molecular neuroscience laboratories where she led the research and development of in-vitro and in-vivo models used in the development of treatments for Multiple Sclerosis, Diabetic Neuropathy, Neurofibromatosis, and Schwannomatosis. Tiffany followed her passion for coding and statistics into the world of bioinformatics consulting where she designed, developed, and implemented analytics and data science systems for 7 of the world's largest pharma and biotech research organizations. Currently, Tiffany supports Astrazeneca's data, analytics, and artificial intelligence teams by leading the strategy of and innovation in Data & AI technology for the enterprise.

Zachary Fagiani

Research Associate

Dragonfly Therapeutics, Inc.

I graduated from Northeastern University in May of 2022 with a B.S in Bioengineering and minors in Chemistry and Spanish. I began working as a co-op at Dragonfly Therapeutics, a medium-sized immunotherapy biotech, during my final year of undergraduate studies as an SPR user in their protein analytics group. I've been at Dragonfly since May 2021, took a full-time position in May of 2022, and since then my role has expanded into one of Dragonfly's primary SPR users. I recently attended SensorFest, hosted by David Myszka of Biosensor Tools in October of 2022, where I was able to deepen both my overall SPR knowledge and my understanding of how to design a high-quality experiment. I’m currently working towards a master’s degree in biotechnology from Harvard and am looking forward to advancing my career in the biotechnology industry!

Matthias Fassler, Ph.D.

Head of Product Management


After his PhD in Cell Biology with a focus on High Content Screening, Matthias worked for 4 years as an Application Scientist at PerkinElmer, Hamburg. In this role Matthias established new imaging assays and image analysis workflows for High Content Screening. With this strong background in HCS Matthias joined Genedata in 2014, where he started as a Scientific Account Manager for Genedata Screener. In 2017 Matthias became the Project Lead for Genedata Imagence, a next-generation image analysis software based on deep learning. Since 2021, Matthias is responsible for the product management of the Genedata Screener platform and Genedata Imagence.

Andrea Feher

Marketing Manager


Nadiezda Fernandez Oropeza

US Field Application Manager

Curiox Biosystems

Amy Files


Bionano Genomics

Amy Files is a Scientist working on the Assays and Reagents team at Bionano Genomics in San Diego, CA. She has been at Bionano Genomics for the past 10 years working on several different aspects of research and development to push forward the field of Optical Genome Mapping (OGM). She was a key contributor for the sample extraction (SP) technology and helped lead the development of the current labeling technology, Direct Label and Stain (DLS), used for OGM. Her contributions to DLS won her the Distinction in Innovation award at Bionano in 2018. For the past year, she has focused her efforts on the development of automation of the SP workflow in collaboration with Hamilton. Prior to Bionano, Amy worked at various biotechnology and pharmaceutical companies, including Merck and Sequenom. She received her B.A. in Biology and Chemistry from Point Loma Nazarene University.

Sascha Fischer

Business Development Manager


Sascha Fischer discovered his passion for automation during his work for Hamilton and Tecan as an Application Specialist for Genomics and NGS. He graduated in Molecular-Medicine at the University of Tübingen and is currently in the final phase of his PhD studies in Neuropsychiatric Genetics at the University of Basel. In April 2021, Sascha joined Genedata as a Business Development Manager supporting Genedata Screener’s Automation Initiatives.

Malte Flickinger

Team Leader Automation

Analytik Jena AG

Matthias Fischer has a background in biomedical engineering, obtained in 2007 from the University of Applied Sciences, Jena, Germany. While completing his Ph.D. at the GEOMAR Helmholtz Centre for Ocean Research Kiel in Germany, he developed a fluorescence-based fiber-optical biofilm sensor for studying biofilm formation dynamics in the field. In 2013, he joined the photonics group at the University of York, United Kingdom, as a postdoctoral researcher. Since 2017 Dr. Fischer's focuses on the design and development of lab automation systems to address liquid handling applications.

Jennifer Fournier

Director, Product Marketing

Waters Corporation

Jennifer Fournier is the Director of Product Marketing in the Chemistry group at Waters.  She joined Waters Corporation in 2004. She has worked in many different parts of the organization.  She started in Life Science Research and Development, then moved into the manufacturing group for the MassPREP line of standards and was  most recently the Product Marketing Manager for the Analytical Standards and Reagents group specifically all bioseparations standards, RapiGest, Amino Acid and Released N-Glycan analysis (AccQTag and GlycoWorks).  She received her B.S. in Biotechnology and M.S. in Biology from Worcester Polytechnic Institute (Worcester, MA).  Prior to joining Waters she taught high school biology for a year and also worked in manufacturing for a small pharmaceutical company that manufactures Albuterol for inhalers.  Jennifer currently manages a team that markets and supports the Chemistry Technology Group.

Gabriela Fragiadakis

Assistant Professor

University of California, San Francisco

Dr. Fragiadakis is an Assistant Professor in the Department of Medicine and The University of California, San Francisco. Her lab uses computational approaches to study states of the immune system, using single-cell omics data from patient samples in disease contexts including autoimmunity, viral infection, and cancer. She earned her PhD in Microbiology and Immunology at Stanford University. As part of her research program she runs the Data Science CoLab, a collaboration-based research lab focused on the analysis and curation of single-cell data including single-cell sequencing and CyTOF, and is the scientific lead of the UCSF Data Library project.

Paul French


Imperial College London

Professor Paul French is Vice Dean (Research) for the Faculty of Natural Sciences at Imperial College London. He received his BSc in physics (1983) and PhD in laser optics (1987) from Imperial College London, where he joined the academic staff in 1994, having previously also worked at the University of New Mexico (1988) and at AT&T Bell Laboratories, (1990/91). Today his research group is based in the Physics Department at Imperial and in a satellite laboratory at the Francis Crick Institute. His research has evolved from ultrafast dye and solid-state laser physics to biomedical optics for applications in cell biology, drug discovery and clinical diagnosis. Current interests include the development and application of multidimensional fluorescence imaging technology for assays of biomolecular interactions, super-resolved microscopy, automated high content analysis, endoscopy and tomography, with open-source approaches to instrumentation, including hardware, data acquisition and analysis. 

Olivier Frey

Vice President and Head of Technology & Platforms

InSphero AG

Olivier Frey is Vice President and Head of Technology & Platforms at InSphero and leads the Microphysiological Systems and Organ-on-Chip programs. Before joining InSphero, he was group leader and SNF Ambizione fellow at the Department of Biosystems Science and Engineering of ETH Zurich, Switzerland on integrated microfluidic systems for single cell handling and 3D tissue cultures. He holds a Dr.Sc in Micro Engineering from the École Polytechnique Fédérale de Lausanne and an MSc in Microtechnology and Mechanics from ETH Zürich.

David Fuller

Chief Executive Officer & Co-Founder


David Fuller is the co-founder and CEO of Artificial who is developing a first-of-its-kind software stack and tools to empower labs to close the loop from scientific intent to reliable results for AI-driven and Cloud-ready lab orchestration.   David has over 25 years of experience in industrial automation and software platforms.  He has held positions in business and technology in such fields as Measurement and Automation where he was the VP of SW R&D at National Instruments.  While at NI, the tools and platforms he built provided the foundation for unique systems as diverse as the CERN hadron collider and SpaceX ground control.  He and several of the technical team now at Artificial, along with many others at NI, partnered with LEGO to build LEGO Mindstorms a low-code tool for kids of all ages to program LEGO robots.  After NI, David focused on Industrial Robotic and Logistic systems as CTO of the KUKA Group and the Managing Director of KUKA Robotics. KUKA is the number one global supplier of high throughput robots for Automotive production.  He received his BS in Computer Engineering from Texas A&M and in 2011 was recognized by the Texas Academy of Medicine & Engineering for Technology Innovation. He holds 42 patents.  He is driven by a love of technology that has a clear positive impact on society.

John Fuller

Commercial Product Manager

Beckman Coulter Life Sciences

John Fuller is the commercial product manager for Echo Drug Discovery at Beckman Coulter Life Sciences in Indianapolis, Indiana. He was previously a field applications scientist for Labcyte. He holds a PhD. from the U.N.T Health Science Center and completed a postdoctoral fellowship at Johns Hopkins University School of Medicine.

Marisol Gabriel

Tradeshow & Events Coordinator

Bio-Rad Laboratories

Linda Gijzen

Scientific Project Lead / PhD Candidate

Mimetas BV

Linda Gijzen is working as a Scientific Project Lead in the Model Development team at Mimetas where she is involved in the development and characterization of human based microfluidic models of the kidney, intestine, and immune oncology. Besides her position as Scientific Project Lead, she is doing a PhD at Mimetas and the University of Utrecht focusing on microfluidic disease models.

Roger Giles

Logan Gin

Assistant Director for STEM Education

Sheridan Center for Teaching and Learning, Brown University

Dr. Logan Gin is the Assistant Director for STEM in the Sheridan Center for Teaching and Learning at Brown University where he works on initiatives related to STEM graduate student and postdoc teaching professional development. Prior to arriving at Brown, Logan was an NSF Graduate Research Fellow at Arizona State University and served as the Program Manager for an NSF S-STEM program focused on involving community college transfer students in undergraduate research. Logan holds a Ph.D. in Biology from Arizona State University where his dissertation work centered around the experiences of STEM students with disabilities. He also has a B.S. in Biology and a B.A. in Political Science from the University of North Carolina at Chapel Hill. 

Peter Girling


Tessara Therapeutics

Peter Girling began his career researching the mechanisms of disease in a variety of organ systems at universities in Australia, California, and Switzerland. He then studied business and entrepreneurship at Babson College (Massachusetts) and the EPFL and USI (Switzerland) prior to co-founding and becoming CEO of CELLnTEC Advanced Cell Systems, a life science company focusing on advanced in vitro models for research and regenerative medicine.  He has worked at Tessara since 2020 where he is involved in advancing production processes and establishing projects under the early-access program.

Antoine Goisnard

Universite Clermont Auvergne

"Specialised in cell biology (more precisely in cancer drug resistance and 3D cell culture models) Antoine has realised its PhD works in the Clermont Auvergne University (within the BIORCELL3D consortium). His works were focused on the development of innovative protocols to preserve caner spheroid models (as alternatives to classic cryopreservation methods), and on the biological validation of fluorescent conjugates able to detect and quantify cancer drug Resistance.

Publications :
• The New Serum-Free OptiPASS® Medium in Cold and Oxygen-Free Conditions: An Innovative Conservation Method for the Preservation of MDA-MB-231 Triple Negative Breast Cancer Spheroids - Cancers – April 2021 – DOI : 10.3390/cancers13081945
• LightSpot®-FL-1 Fluorescent Probe: An Innovative Tool for Cancer Drug Resistance Analysis by Direct Detection and Quantification of the P-glycoprotein (P-gp) on Monolayer Culture and Spheroid Triple Negative Breast Cancer Models - August 2021 – DOI : 10.3390/cancers13164050"

Ilya Goldberg



Dr. Ilya Goldberg has played a leading role in the development of image informatics and machine learning for bio-medical imaging. At ViQi, Ilya leads development of automated cell-based imaging assays using AIs. Prior to ViQi, Ilya co-founded a company that developed the first medical device to receive regulatory clearance that uses an AI to help diagnose lung cancer in CT screening exams. Prior to this, Ilya led a research group at the NIH National Institute on Aging, developing machine learning software for image analysis in the life sciences, and studying the basic biology of aging. As a postdoc at MIT, Ilya co-founded the OME project, which continues to be used for imaging infrastructure in large image repositories. Ilya has over 60 peer-reviewed articles from his years at Johns Hopkins, Harvard, MIT, and NIH in molecular and cell biology, pattern recognition, image informatics, and aging.

Alon Goren

Associate Professor, Department of Medicine

University of California San Diego

"2008 Ph.D. Hebrew University, Jerusalem, Israel, Howard Cedar's lab;

2008-2014 Postdoctoral Fellow: The Broad Institute, Cambridge, MA - Aviv Regev and Brad Bernstein's Labs
2014-2016 Research Scientist, Broad Technology Labs, The Broad Institute, Cambridge, MA
2016-2022 Assistant Professor, Department of Medicine, University of California, San Diego.
2022- Associate Professor, Department of Medicine, University of California, San Diego.

My research focuses on epigenomic mechanisms, and merges the study of basic and disease biology, technological innovations and computational analyses. I am an advocate of reproducible and robust research tools. My major interest is in regulatory epigenomics, and includes the employment and innovation of tools to address unanswered questions in chromatin biology. The main efforts of my group revolve around investigating the organization and function of chromatin regulatory networks during developmental transitions in normal and aberrant states, what are the cellular means to maintain the epigenome during processes such as the cell cycle, and how genetic variation, such as tandem repeats (TRs) and SNPs, impact the structure of chromatin."

William Go

Chief Medical Officer

A2 Bio

"William Go, M.D., Ph.D., Chief Medical Offier, oversees all aspects of A2 Bio’s development of T cell therapies utilizing the company’s novel logic-gated platform technology.

Previously, Will worked at Kite Pharma (acquired by Gilead) where he developed novel immune-cellular therapies for the treatment of cancer. At Kite, Will led the ZUMA-1 pivotal study and eventual FDA and EMA approvals of YESCARTA®, the first CAR T cell therapy approved in large B-cell Lymphoma. YESCARTA received the Prix Galien Award for Best Biotechnology Product in 2018. He became a vice president of clinical development at Kite/Gilead leading large B-cell lymphoma clinical development.

Earlier in his career, Will played an instrumental role in the clinical development of Vectibix® in colorectal cancer, as well as identifying new predictive biomarkers as a medical director in global clinical development at Amgen.

Will received his bachelor’s degree in biology from Carleton College and then attended the University of California San Diego’s (UCSD) Medical Scientist Training Program. He received his Ph.D. in 2004 with a focus on immunology and completed his M.D. in 2006. Will did his internal medicine residency, hematology/oncology fellowship at UCSD. He was the recipient of the California Institute for Regenerative Medicine fellowship award and the American Association of Cancer Institutes’ fellowship award studying tumor immunology.

Will also volunteers as a Board Member for the American Pancreatic Association Foundation and as a Board of Trustee and COVID-19 Taskforce Scientific Advisor for Viewpoint School."

Mark Greenough

Senior Scientist

Tessara Therapeutics

Mark Greenough PhD is the principal scientist at Tessara Therapeutics (Melbourne, Australia), having joined the company in 2021. Mark’s research expertise is in the fields of neuroscience and genetics where he has applied his skills using cell culture models to elucidate mechanisms of neurodegeneration, with a particular focus on Alzheimer’s disease. Mark also has a keen interest in the metal biology of neurodegeneration and the role that iron plays in health and disease states. Mark has had a significant impact on the growth of Tessara; helping to establish automated protocols for RealBrain microtissue production and leading R&D efforts in assay design, biomatrix formulation, QC protocols and generation of new RealBrain models. Leveraging Mark’s strong track record in Alzheimer’s disease research and recent discoveries related to ferroptosis susceptibility (Greenough, Cell Death and Differentiation, 2022, DOI: 10.1038/s41418-022-01003-1) he has applied this knowledge to help establish ADBrain as a ‘first of its kind’ human 3D model for Alzheimer’s disease drug discovery.

Russell Green

"Russell is Automata's Director of Product Growth and looks after product strategy across the Synthetic Biology and Drug Development markets. He started his career studying molecular structures using crystallography, and then moved into life science instrumentation where he has held strategic roles at numerous Life Science technology businesses centred around automation hardware and software tools including Beckman Coulter, Thermo Fisher and Synthace. Russ has managed global teams consulting for automated systems for life sciences; led product development for hardware and software and been subject matter experts for automation of both genomics and cellular biology applications.

Day to day, Russ guides product development to best meet the automation needs of the Life Science industry."

Regis Grenier

Kalpesh Gupta

Sr. Principal Automation Engineer


"Kalpesh Gupta is the Principal Automation Engineer, leading the automation efforts at Moderna Inc., located in Cambridge, MA. Kalpesh has a master’s degree in Bioinformatics' from Brandies University, and a master’s in science in Biotechnology from Northeastern University. He is a recognized expert in developing and programming methods for various liquid handling platforms like STAR, STARlet, Starplus, Vantage, and Nimbus. Currently managing a team responsible for programming for 49 Hamilton systems, Kalpesh is overseeing automation growth in Moderna. 

Before joining Moderna, he also has worked in cell signaling technology where he has an extensive experience in Protein Chemistry, Molecular biology, Protein spectroscopic analysis, SDS-PAGE, IEF Western Blotting, Size Exclusion Chromatography, HPLC, DSC, ELISA, dissolution, Activity and cell-based assays, DLS, etc."

Zachary A. Gurard-Levin, Ph.D.

Chief Scientific Office

SAMDI Tech, Inc

Dr. Zachary Gurard-Levin has served as chief scientific officer at SAMDI Tech, Inc. since 2016. He brings 15 years of multidisciplinary research experience with expertise in chemistry, biochemistry, cellular biology and drug discovery research. Dr. Gurard-Levin was a pioneer user of SAMDI technology and co-developed SAMDI as a high-throughput, label-free solution for drug discovery research.

Prior to SAMDI Tech, Dr. Gurard-Levin was a research scientist at the Institut Curie in Paris, France, leading epigenetics drug discovery and diagnostics projects in oncology. Dr. Gurard-Levin has authored numerous peer-reviewed articles and has been awarded multiple research grants. He has a doctorate in chemistry from the University of Chicago. In addition, he completed a postdoctoral fellowship at Institut Curie with Dr. Genevieve Almouzni.

Rositsa Hadzhipetrova

Carrie Halle

Richard Hammond

Chief Technical Officer

Sphere Fluidics

Richard is responsible for R&D at Sphere Fluidics, managing the development of their science and technology. Richard has over 20 years’ experience in developing cutting-edge commercial products for healthcare and life sciences. Richard has held numerous senior positions responsible for product and technology development. At Alere Inc (now part of Abbott) he led several major cross-company R+D programmes for in-vitro diagnostic devices including the development of the Alere i platform, the world’s first CLIA-waived point-of-care infectious disease diagnostic device using isothermal DNA amplification techniques. At Cambridge Consultants Ltd. Richard started their bioinnovation group, providing technical design and consultancy services at the intersection of biology and engineering. Over six years this group grew from one person to a team delivering substantial projects in areas such as automated cell transfection, CAR-T cell therapy manufacture and digital data storage in DNA. Most recently Richard was VP Technology at DNA Electronics, leading the R&D team developing a novel fully-automated sample-to-answer in-vitro diagnostic platform using DNA sequencing. Richard holds MA and MEng degrees in engineering from King’s College University of Cambridge.

Anna Hartwig

VP Product & Technology Development

Exai Bio

"Experienced team lead with 10+ years in NGS technology and nucleic acid methodology with molecular oncology focus. Experienced in leading assay development and validation in regulated environments. Passionate about creating engaged and collaborative teams that solve important technical and biological problems

PhD from Karolinska Institute Stockholm, Sweden, 2005-2010
Post Doc at Yale University, CT, 2011-2016
Toma Biosciences, Foster City, CA (Senior Scientist - VP R&D), 2016-2018
Guardant Health, Redwood City, CA (Manager - Associate Director), 2018-2022
Exai Bio, Palo Alto, CA (VP Product &Technology Development), 2022-current"

Sandy Hayes

Senior Director, Cell Therapy Platform and Discovery

Janssen Research & Development, LLC

Sandy Hayes, PhD, is Senior Director, Cell Therapy Platform and Discovery, at Janssen Research & Development. She has more than 25 years of experience in both academia and industry studying the biology and clinical application of γδ T cells. Sandy holds a Bachelor of Arts degree from Franklin & Marshall College and a PhD in Immunology from the University of Connecticut Health Center.

Ernest Heimsath

Applications Development Scientist

Agilent Technologies, Inc.

Dr. Ernest Heimsath joined the Agilent Biotek scientific applications team in 2019 as an Applications Development Scientist. He earned his B.S. in Biology from UT San Antonio, and his Ph.D. in Biochemistry from Geisel School of Medicine at Dartmouth, where he studied the biochemical regulation of actin polymerization. Ernest conducted postdoctoral research at the National Institutes of Health and UNC School of Medicine, where he used advanced imaging techniques and animal models to define the contribution of actin-associated genes in building actin-based cellular structures crucial for cancer metastasis and organismal development. With expertise in fluorescence microscopy, his primary role at BioTek is to develop and optimize imaging-based applications.

Nathaniel Hentz

Director Scientific Market Development

Artel Portfolio - Advanced Instruments

"Nat is an industry leader with years of experience developing HTS assays, automating and optimizing laboratory equipment, and investigating new technologies with Eli Lilly & Co. and Bristol-Myers Squibb. During his tenure at North Carolina State University, Nat specialized in hands-on instruction and development activities to assist with the growth of the biomanufacturing industry. As Director, Scientific Market Development at Artel, Nat focusses on developing new applications to solve problems for the assay development community."

Ben Hoffstrom

Adjunct Assistant Professor

University of California, Los Angeles

Dr. Hoffstrom is cell biologist with over 22 years of combined academic and industrial research experience in field of antibody discovery and drug development.  From 2011 to 2021 he was the Director of the Antibody Technology lab at the Fred Hutch Cancer Research Center. In 2021 he was recruited to the Department of Medicine at ULCA by Dr. Dennis Slamon to design and build a next generation monoclonal antibody screening platform for therapeutic antibody discovery.

Sue Holland-Crimmin

Scientific Consultant

Pharma Discovery Logistics & Technology Consulting

Nicholas Holliday

Chief Scientific Officer

Excellerate Bioscience

Dr Nick Holliday is Chief Scientific Officer (CSO) at Excellerate Bioscience, a contract research organisation for in vitro pharmacology, and is also part-time Associate Professor in Pharmacology at the University of Nottingham (UK).  Following university studies in Cambridge (MA) and King’s College London (PhD), Nick has over 25 years’ experience in the molecular pharmacology of receptors and other drug targets, together with the development of in vitro imaging based assay systems to measure binding and signalling kinetics.  He is a Fellow of the British Pharmacological Society.

Daniel Holmes

Clinical Professor

University of British Columbia

Daniel Holmes earned his undergraduate degree in Chemical Physics from the University of Toronto. He went to medical school at the University of British Columbia (UBC) where he also did his residency in Medical Biochemistry. He is a Clinical Professor of Pathology and Laboratory Medicine at UBC and Head and Medical Director of the Department of Pathology and Laboratory Medicine at St. Paul’s Hospital in Vancouver and Interim Medical Director of the British Columbia Provincial Toxicology Laboratory. Interests include clinical endocrinology with a focus on secondary hypertension,  lipidology, clinical mass spectrometry, and data science in application to data automation, visualization and clinical utilization.

Saman Honarnejad

Chief Scientific Officer

Pivot Park Screening Centre B.V.

Dr. Honarnejad is a biotechnologist with >15 years of experience in high-throughput biomolecular and cellular screening and currently serves as Chief Scientific Offier at Pivot Park Screening Centre (PPSC), a spin-off from former Organon/MSD lead discovery screening unit in the Netherlands. At PPSC he is involved in a broad range of commercial, academic, and shared-risk lead discovery programs. He carried out his doctorate in biotechnology jointly at the University of Heidelberg and Harvard University. Prior to joining PPSC, he was active in methods development for high-content in-vitro compound profiling and genome-wide RNAi/cDNA screening methods at various prestigious research organizations such as Harvard Medical School, Max-Planck Society, and European Molecular Biology Laboratory.

Nathan Hotaling

Senior Data Scientist

National Center for Advancing Translational Science

"Dr. Nathan Hotaling received his PhD in Biomedical Engineering from the Georgia Institute of Technology and a Masters in Clinical and Translational Science from Emory University in 2013. After his PhD, Nathan did two post-doctoral research terms at the National Institute of Standards and Technology (NIST) and the National Eye Institute (NEI), respectively, where he helped standardize the measurement of biodegradable nanofiber scaffolds and the cells grown on them, for use in a primary human cell therapy for age-related macular degeneration, which implanted its first patient in August of 2022.  While pursuing these projects he began to develop a platform to analyze high content datasets collected for drug screening and cell bio-manufacturing. This work led to his transition to Axle Informatics and NCATS where he oversees the development of the next generation of data analysis tools for researchers in the high-throughput and high-content screening fields. 

In conjunction with the above research work Dr.Hotaling is the Senior Vice President of Data Science at Axle Informatics where he founded and developed the Data Science Division. As a division founder his role has spanned a gamut of management and leadership roles from budgeting/accounting to culture definition and operational planning. During this time, he also secured contract funding and has grown the team to over 40 data scientists, software engineers, and researchers in the past 4 years."

Rob Howes

CEO and Site Director

Rosalind Franklin Laboratory

"Prof. Rob Howes, Site Director and CEO, Rosalind Franklin Laboratory, Leamington Spa, UK

Rob has 20 years experience in Industry working across a range of organisations in the early drug discovery area. Most recently he spent 8 years at AstraZeneca with a year at the Cambridge Covid-19 Testing Centre supporting the UK’s Covid-19 response. In June 2021, he joined the UK Government's Health Security Agency to run the newly created Rosalind Franklin Laboratory in Leamington Spa focused on Covid-19 Diagnostic assays and to establish it as a leading centre for diagnostics within the UK.

Rob is the SLAS Discovery podcast editor and an Editorial Board member of SLAS Discover. He was made a SLAS Fellow in 2020."

Alison Hoyer

James Hoying, Ph.D.

Chief Scientist

Advanced Solutions Life Sciences

"James (Jay) Hoying is a leading expert in tissue vascularization, vascularized tissue models, and tissue model fabrication with more than 25 years of experience in basic and applied sciences involving tissue and vascular biology. Hoying is a founding Partner of Advanced Solutions Life Sciences and serves as its Chief Scientist.  Previously, he was Professor and Chief of the Division of Cardiovascular Therapeutics at the Cardiovascular Innovation Institute (CII) where he developed a broad background in tissue fabrication, cell therapeutics, and translation of discoveries to industry and the clinic. He also has joint appointments at the Department of Physiology at the University of Louisville and the Department of Biotechnology at the University of New Hampshire. Hoying pioneered the use of native, intact microvascular elements in modeling vascularization and vascularizing tissues in vitro and in vivo. He holds numerous patents related to vascularizing tissues and related cell-based therapies. He has edited a book and published over 130 original research papers, reviews, and book chapters. As a researcher, he has secured nearly $18 million in grants as PI or co-PI. Hoying currently serves on the Editorial staff of Frontiers of Physiology and reviews for several other national and international journals. He reviews individual and program grant proposals for the National Institutes of Health, the Veterans Affairs, the American Heart Association, and international funding agencies. Hoying has organized, chaired and co-chaired more than 11 international and national conference sessions and delivered more than 51 keynote and invited talks at conferences and University seminars. He currently serves in an advisory role for 5 programs including the Leadership Advisory Council of the Advanced Regenerative Manufacturing Institute, the Research and Industry Council of the New Hampshire BioMade EPSCoR program, and the New Hampshire Tech Alliance/BioMed|Tech Leadership Council. He is also a Fellow of the American Heart Association. "

Sarah Huntwork-Rodriguez

Director, Clinical Biomarkers

Denali Therapeutics

"Sarah Huntwork-Rodriguez, PhD, is a Director and Lab Leader at Denali Therapeutics in South San Francisco, California. In this role, she leads the development and implementation of target engagement and disease-associated pathway biomarker assays for Denali's LRRK2 inhibitor program for Parkinson's disease. She has worked extensively with academic collaborators and The Michael J. Fox Foundation to measure Parkinson’s disease biomarkers in the LRRK2 Cohort Consortium, the 24 hour Biofluid Study, the LRRK2 Detection Consortium, the LRRK2 Biobanking Initiative, and PPMI.

During her academic career, she focused on cellular and molecular neuroscience. A graduate of Stanford University, she obtained her PhD in Neurobiology from the Department of Biology at the Massachusetts Institute of Technology. During her postdoctoral work in the laboratories of Marc Tessier-Lavigne and Joseph Lewcock at Genentech in South San Francisco, California, she studied mechanisms of the neuronal stress response in triggering cell death following neuronal insults."

Kevin Jacobs

Vice President of Bioinformatics and Data Science

Deepcell, Inc

Jacobs is a distinguished industry expert leading AI and data science strategy and implementation at Deepcell as VP of Data Science and Bioinformatics. Jacobs has decades-long experience in computational methods and large-scale molecular and imaging datasets at several well-known companies such as Progenity, Helix, 23andMe, and Invitae. He earned his degree in computer science from Case Western Reserve University’s School of Engineering.

Sudhakar Jha

Associate Professor

Oklahoma State University, College of Veterinary Medicine, Stillwater, OK, USA

Dr. Sudhakar Jha is an Associate Professor in the Department of Physiological Sciences at Oklahoma State University. Dr. Jha is a cancer biologist with interest in deciphering how epigenetic pathways are deregulated during tumorigenesis. His group has identified, purified, and characterized multiple protein complexes that are hijacked by pathogens to promote growth.

David Julovich

Research Core Director

Southern Methodist University

"David Julovich completed his bachelor’s degree in Biology from Purdue University and a Master of Science in Data Science from Southern Methodist University. His initial work experience started on the industry side where he gained valuable experience at Abbott Laboratories in an FDA regulated setting and later in Cytogenetics in CLIA and CAP regulated labs (Impath, Genzyme).  

Following his career path on the industry side, Mr. Julovich found his way into academia and supported projects at prominent universities including Purdue, Arizona State University, Indiana University and most recently the University of North Texas Health Science Center. Through his work at UNTHSC, he supports several liquid handlers and automated digital workflows.  

Mr. Julovich years of expertise with multi-plex ELISAs and automated technologies allow him to support and improve Biomarker Screening for neurodegenerative diseases. His current work truly highlights how science and technology can come together to provide a healthcare solution that impacts 10’s of thousands of patients per year and in the future, improve healthcare for millions."

Ken Kaiser

Magdalena Kasendra

Director of Research and Development at the Center for Stem Cell and Organoid Medicine (CuSTOM)

Cincinnati Children`s Hospital and Medical Center

"Magdalena Kasendra is the Director of Research and Development at the Center for Stem Cell & Organoid Medicine (CuSTOM). She leads a multifaceted effort to translate breakthrough discoveries in stem cell biology and organ development into innovative organoid-based solutions to address unmet medical needs. These include organoid-based platforms enabling discovery and development of safer and more efficient drugs, precision medicine applications and organoid-based tissue replacement therapies.

Prior to joining CuSTOM’s leadership team, she managed the multidisciplinary team responsible for developing, translating and commercializing Organs-on-Chips technology at Emulate Inc., a spin-off from Harvard's Wyss Institute for Biologically Inspired Engineering. This research has led to major advances in bioengineering of intestinal tissue by combining microchip manufacturing methods and organoid technology and demonstrated the utility of this platform in drug development, disease modeling and precision medicine. 
Dr. Kasendra’s career spans industry, academia and the start-up world. She performed her PhD project at Novartis Vaccines and Development, which was followed by post-doctoral research fellowship at the Harvard Medical School and the Wyss Institute for Biologically Inspired Engineering at Harvard University. She has authored numerous publications and patents."

Stephen Kasper

Associate Principal Scientist


I am a scientist-engineer at Merck Research Labs in Cambridge, MA, where I work on scaling and implementing new technologies in an effort to discover and de-risk drug targets. My research often focuses on developing complex in vitro models and systems that can be used for target de-risking. My team uses a variety of core capabilities in microfluidics, screening/automation, 3D culture, microbiology, and chemical/molecular biology to build and validate these systems. Before joining Merck in 2017, I was a co-founder of Empire Biotechnologies, a biotech startup developing therapies for gastrointestinal diseases. I received my Ph.D in Nanoscale Engineering and B.S. in Biochemistry and Molecular Biology from the University at Albany, SUNY.

Sam Kean


Sam Kean is the New York Times bestselling author of six books, including The Icepick Surgeon, The Bastard Brigade, The Dueling Neurosurgeons, and The Disappearing Spoon. His books have won multiple international awards for literary science writing, and his work has been featured on NPR’s “Radiolab,” “All Things Considered,” and “Fresh Air.” His podcast, The Disappearing Spoon, debuted at #1 on the iTunes charts for science podcasts.

Ian M. Kerman

Director of Customer Success


Ian Kerman studied bioinformatics and molecular biology at the University of California, San Diego. Soon after starting as a research associate at a biotech startup, Ian began applying machine learning techniques to his company’s screening and assay data. Ian later joined a life science-focused data science company, helping laboratory scientists process, analyze, and extract insights from their data. More recently, Ian studied machine learning at the Georgia Institute of Technology and is the Director of Customer Success at LabVoice, an AI-powered digital assistant company for scientists. When he isn’t helping scientists analyze and automate their processes, he spends time with his husky-pug or SCUBA diving with sharks.

Christian Kis

Field Applications Staff Scientist, Automated Sample Prep and Analysis for Nucleic Acid and Protein

Thermo Fisher Scientific

Christian Kis is a Staff Scientist in Field Applications for the Life Science and Laboratory Products team.  He has worked at Thermo Fisher Scientific for 11 years and has supported the Kingfishers and Sample Prep portfolio for over 10 of those years.  He is currently involved with training and instrument and applications support in the field for the KingFisher Sample Purification Systems, providing an integral connection between sales, R&D and customers.

Cullen Klein

Automation Chemist


Cullen Klein received his B.S. in Chemistry and Mathematics at The Ohio State University in 2002 and completed his PhD in Organic Chemistry at Indiana University-Bloomington in 2009 under the direction of Professor David R. Williams.  He continued his studies with post-doctoral research under Prof. Dr. Peter Seeberger at the Max Planck Institute for Colloids and Interface Science, and Prof. Tom Snaddon at Indiana University-Bloomington.  He subsequently then worked in the Instrument Research and Development division of Siemens Healthcare Laboratory Diagnostics in Newark, Delaware.  In 2020 he joined the National Center for Advancing Translational Science (NCATS) to work on the ASPIRE program as an Automation Chemist.

Nikita Kolhatkar

Senior Research Scientist


"Dr. Nikita Kolhatkar recieved her Ph.D from the University of Washington, Department of Immunology and is currently a senior research scientist at Gilead Sciences focusing on clinical biomarkers in infectious diseases, specifically Chronic Hepatitis B (CHB). She previously held roles as a clinical immunologist at Vaxart, Inc. where she worked on the development of an oral influenza vaccine. Additionally, she has worked as a scientist in the immuno-safety science group at Amgen working to support toxicology studies within the immuno-oncology space."

Michaela Kraus

Robin Krüger

Vice President ARRALYZE

ARRALYZE / LPKF Laser & Electronics AG

"Dr. Robin A. Krüger

Robin studied chemistry and biochemistry at Philipps University in Marburg, Germany, where he also conducted his doctoral research on fluorescent biomarkers and bacterial photoreceptors. After a postdoctoral stay at the University in Calgary/Canada, he joined LPKF in 2011, where he held various development positions. Since 2020, Robin is leading the ARRALYZE team."

Takuya Kubo

Associate Professor

Kyoto University

Takuya Kubo is an associate professor of Analytical Chemistry of Materials, Department of Material Chemistry, Graduate School of Engineering, Kyoto University.  He received his Ph.D. from Kyoto Institute of Technology in 2004. After working as a Research Assistant in National Institute for Environmental Studies (2001–2004), he joined Graduate School of Environmental Studies, Tohoku University as an assistant professor (2004–2012) and Department of Chemistry, Portland State University, OR, USA a visiting (2010–2011) (JSPS Excellent Young Researcher Overseas Visit Program), then moved to Kyoto University as an associate professor in 2012.

Sunil Kurian

Research Scientist/Scientific Director

Scripps Health

Dr. Kurian is an accomplished scientist with 22 years of research experience and more than 85 published research and review papers.  He is trained in biomarker discovery and genomics of varied disciplines, and in the critical assessment of bio-informatics approaches needed to prioritize and validate biomarkers. He is currently Scientific Director of the Scripps Health/Scripps Clinic Bio-Repository and Bioinformatics Core (SCBBC). Dr. Kurian serves as a scientific advisor for Transplant Genomics, a company specializing in post-transplant care, and as Chief Scientific Officer for MindX Sciences, which focuses on biomarkers of mental health, and was a founding member for both companies.

Brandon Kwan-Leong

Automation Engineer

Laboratory for Genomics Research

Brandon Kwan-Leong is an automation engineer at the Laboratory for Genomics Research, where he is standardizing the tools used to build genome-wide guide RNA libraries and perform arrayed CRISPR-based screens. His previous roles in manufacturing and clinical labs produced robust systems used across multiple labs. Brandon has worked as a researcher, engineer, and consultant to develop novel assays and bridge the gap between low and high throughput workflows. He is currently focused on applying automation in an academic setting.

Astha Lamichhane

Research Assistant

University of Akron

Currently a 5th year Ph.D. student in Biomedical Engineering at The University of Akron. My research focus is on understanding cancer drug resistance using 3D tumor models i.e. spheroids and organoids and finding effective ways to target them. I have been awarded Tony B Award for the third time in SLAS. 

Christa Lamps

Janelle Laurano

Meghan Lawler

Director, Affinity Technology


Meghan is a biochemist with experience ranging from peptide synthesis to SELEX to lncRNA footprinting. While pursuing her PhD at Duke University, she employed each of these with protein biochemistry to explore dynamic interactions of epigenetic complexes. In 2019, she joined the world of DEL and is developing new approaches to the wide variety of biochemical problems in the DEL space. 

Connie Lebakken


Stem Pharm, Inc.

Connie Lebakken, PhD, COO and co-founder of Stem Pharm, has 20 years experience in life science companies with roles in manufacturing, operations, and R&D. She has extensive expertise in high-throughput biochemical and cell-based drug discovery assays with a focus on neurology and oncology.

Clarence Lee

Sr. Product Manager, Digital PCR

Thermo Fisher Scientific

Clarence is leading product development efforts in the digital PCR business at Thermo Fisher Scientific, focused on enabling customers through automation to make the world healthier, cleaner and safer.  He has more than 15 years of experience innovating in the life sciences industry in various capacities, including next-generation sequencing and assay development.  

Jeong Hyun Lee

Postdoctoral Fellow

University of British Columbia

I’m a postdoctoral fellow at the University of British Columbia, currently working on mRNA analysis of CAR-T cells in time-lapse. Also working on developing a next-generation image-based cell sorting system. I received my Ph.D. degree at the University of British Columbia-Vancouver. My Ph.D. research focused on developing efficient techniques for single-cell RNA analysis on rare cells and rare cellular events.

Celine Legros

Drug Discovery Partnerships Director

Eurofins Discovery

Celine Legros is a Drug Discovery Partnership Director at Eurofins Discovery. With extended knowledge of Eurofins Discovery’s expertise and services. She is the primary scientific contact for clients, deeply involved in the design of complex projects, such as HTS, Hit-to-Lead and Lead-Op programs. Prior to joining Eurofins, Celine was Scientific Project Leader in the Screening Department at Institut de Recherches Servier, France, where she was responsible for designing and running screening cascades from Target to Hit/HTS through to Lead Optimization. In close collaboration with chemistry and biophysics teams, Celine led screening projects in neuroscience, cardiovascular & metabolic diseases, immune-inflammation and oncology. In addition, she developed and ran assays on GPCRs, transcription factors, PPi, kinases, Ser-hydrolases and Tyr-kinase receptors, combining scientific relevance with robotics, data quality and throughput. Employing her expertise in HTS and previous experience in platform design, in close collaboration with robotics engineers, she designs automated platforms and implements new HTS technology. Celine holds a Ph.D. in Animal Physiology (melatonin circanual rhythm and melatonin receptors) from the University of Tours, France, and completed a postdoctoral fellowship within the Blood Brain Barrier Group at King's College London, UK.

Chuck Li

Automation Engineer

A2 Biotherapeutics

I am a multi-disciplinary engineer with over 20 years of R&D experience primarily in the areas of laboratory automation and advanced analytical and detection technologies. I started my career at Amgen Inc and am now helping to develop new cancer treatments at A2 Biotherapeutics, a fast-growing biotech startup in the greater Los Angeles area. I completed my undergraduate degree in biomedical and electrical engineering and my master's degree in biomedical engineering, both from the University of Southern California.

Jing Li

Principal Scientist

Biochemical & Cellular Pharmacology (Genentech)

Jing Li is a Principal Scientist in the Biochemical and Cellular Pharmacology (BCP) department at Genentech. He is the BCP representative on multiple key pipeline projects at Genentech, providing assay strategy to identify lead molecules for early development. Jing received a medicine degree from Peking University and subsequently obtained a Ph.D. in biochemistry from Technical University in Munich under the direction of Professor Johannes Buchner. His Ph.D. work focused on understanding the molecular mechanism of heat shock protein Hsp90. In 2012, Jing started his postdoctoral research to study proteasome and protein degradation at Caltech under the supervision of Dr. Raymond Deshaies. He developed the first-in-class inhibitor targeting Rpn11/PSMD14, an essential deubiquitinase located on the 19S proteasome. In 2017, he moved to Amgen Inc. to finalize his postdoctoral research, where he identified natural compounds that inhibit JAMM metalloprotease.

Li Li

Postdoctoral scholar, Altschuler and Wu lab, Pharmaceutical Chemistry Department

University of California, San Francisco

Dr Li. Li is a postdoc fellow in the joint laboratories of Dr. Steven Altschuler and Dr. Lani Wu. Currently, she is applying system biology methods to study acute hypoxia. Previous to that, she received her PhD in Biochemistry and Molecular biology from the Peking University-National Institute of Biological Sciences, Beijing joint program, where she applied medicinal chemistry and chemical biology methods to explore human disease related mechanisms and develop new therapeutic approaches.

Samuel Little

PhD Candidate

Concordia University

"Sam is currently a Ph.D. candidate in electrical engineering at Concordia University with a B.Eng in mechanical engineering from Ontario Tech University. In his research, Sam focuses on applying novel microfluidic paradigms to find solutions not available at the macro-scale. In particular, he is interested in how immune cell engineering can be advanced with creative engineering solutions."

Betty Liu

Yue Liu

Associate Director

Generate Biomedicines Inc.

Yue has over 10 years’ experience in drug discovery and has spent majority of her time in the research and development sectors in both large pharma and biotech companies. In her current role as a team lead and project lead, she excels at applying interdisciplinary knowledge of antibody R&D and lab automation to characterize antibody at scale, and in integrating the wet lab and dry lab capabilities to build machine learning technology platform and pipeline programs.

Yanli Li

Paul Lomax

Product Manager

SPT Labtech

Paul joined SPT Labtech in 2015 as a Product Manager responsible for automated systems for drug discovery and genomic research, such as mosquito and dragonfly which utilise novel patented positive displacement pipetting and non-contact dispensing technologies . Paul works closely with reasearchers and collaborators in developing new solutions for the market, both in terms of new instruments and application dvelopment. Most recently Paul led the introduction of the new firefly platform from initial concept design, through development, culminatiing in its launch at SLAS 2022 in Boston. Paul has over 20 years’ experience in the automation of sample processing across a wide range of application areas in the academic, clinical, environmental, biotech, and pharmaceutical sectors.

Mike Loos

Global Director of Pre-Sales Solution Architecture


Mike is the Global Director of Solution Architecture at TetraScience, bringing over 20 years of experience in the systems integration domain. Previous to TetraScience, Mike honed his expertise at organizations such as MuleSoft, Oracle, and Fastenal Company while somehow also carving out time to play golf. His goal is to shoot Par at least once in his lifetime. He has accomplished this goal on 9 holes, but has yet to accomplish it on 18.

James Love

Vice President, Automation and Process Optimization

Novo Nordisk

X-ray crystallographer by training at Cambridge University, I moved into using automation to help in the high throughput expression of proteins. Using automation was key to success. Now focusing in automation and digitalization in many aspects of target identification and validation, drug discovery and development across many areas in Novo Nordisk.

Stefan N. Lukianov, BS, BS, MS, AM


Salve Therapeutics

Stefan N. Lukianov, AM MS is the first-time JHU student founder of Salve Therapeutics.  He has undergraduate degrees from the University of Maine and masters from the University of Pittsburgh and Harvard University in the biomedical sciences.  He has worked in reputable labs at Boston Children’s Hospital, Brigham and Women’s Hospital, McLean Hospital and the UPMC Hillman Cancer Center. He also has extensive experience in science journalism, having published and edited for ASBMB Today, ACS C&EN Show Daily, the Harvard Medical Student Review and MIT Science Policy Review.  Stefan also loves teaching and has held a diverse array of private and public education roles at various grade levels in STEM fields.

Xiaoyong Lu

Director of Chemistry &RNA Delivery


Xiaoyong Lu is a passionate field executor in RNA therapeutics development. He has over fifteen years combined experience in Medicinal chemistry, drug delivery and RNA therapeutics. He got his PhD. in Organic Chemistry from Ohio University and continued postdoc training at The Ohio State University and University of Maryland College Park. He currently holds a Director of Chemistry position at Sirnaomics Inc.. He leads the oligonucleotide drug delivery team and supervised oligonucleotide synthesis lab to develop novel RNA targeting delivery platform for novel siRNA therapeutics. He is the inventor of Peptide Docking Vehicle (PDoV-GalNAcTM) RNA targeting delivery system and siRNA-gemcitabine conjugation for cancer treatment. Lead the precilinical development for pipelines STP135G and STP155G for PCSK9 and HBV targets treatment using PDoV-GalNAc based targeting delivery system. He has published a few dozens of publications and is a key-inventor for over ten patents.   

Jennifer MacFarland

Global Market Development Manager

Thermo Fisher Scientific

Jennifer MacFarland is a Global Market Development Manager with Thermo Fisher Scientific, where she works with a team of scientists, product managers, and commercials leaders to understand the needs of customers and how Thermo Scientific  instruments, equipment, and consumables can assist in his/her workflow.  Before starting her career, Jennifer received degrees in Forensic and Anthropology.  She has spent 20+ years working in various roles from bench scientist, project manager, and marketing manger in the life science industry.

Chris MacNaughton

Software Architect


Chris MaNaughton is a software architect at DeepCure with over 15 years of experience working in various industries, including education, e-commerce, pharma, precision health, and wellness. Chris works across the software stack to build large-scale, highly-available applications and platform services. (DeepCure is located in Boston, Massachusetts. Visit the website at

Sven Malik

Senior Application Specialist

Bruker Daltonics SPR

"Sven studied Bioprocess Engineering at the Technical University of Dresden, Germany and graduated in 2012. During his diploma studies he investigated the interaction of cytomegalovirus protein pp65 against certain antibodies.

In 2012 he joined Sierra Sensors GmbH to start his role as application specialist. After 6 years he became senior application specialist as Bruker acquired Sierra Sensors GmbH. Currently he is involved in the customer support and product development."

Nubia Manchola Varon

​Postdoctoral Fellow

Calibr - California Institute for Biomedical Research

Postdoctoral fellow at the Scripps Research Institute (California), Division of Infectious Diseases. Research topic: Chagas HTS. Previously Professor collaborator at the Institute of Chemistry of the University of São Paulo (Brazil). Postdoctoral fellow at the Institute of Chemistry at the University of São Paulo. Research topic: signaling pathways involved in the interaction between Trypanosoma cruzi and mammalian cells, with special emphasis on the role of second messengers in the adhesion process of trypomastigotes and an extracellular matrix of host cells. Collaborator of the Colombia Science Clubs initiative (2018), program to promote science in children. PhD in Sciences from the University of São Paulo (2017), (Department of Parasitology associated with the Institute of Biomedical Sciences -USP), research topic: biochemical degradation pathways of branched amino acids in Trypanosoma cruzi. Scientific internship at the University of Buenos Aires (2015). Biologist - Universidad del Tolima (2012). Experience in molecular biology, trypanosomatid biochemistry, cell culture, metabolite transport, parasitology, bioinformatics, protein cloning and purification, enzymology and microscopy.

Henning Mann

Business Development & Partnerships

Nikon Instruments

"After 10+ years of cancer research at Fred Hutch in Seattle Dr. Mann joined ucpoming Nortis, Inc. in 2012. There he led Nortis' science team, their model and business development and Applied Sciences of innovative, perfused 3D tissue models. Among others, these models represented vascular and kidney biology and (immuno-)oncology and their use in toxicology, preclinical drug testing and development. Nortis technology is characterized by mostly autonomously running tissue culture vessels optimized for image acquisition and analysis and ideally suited for being merged with scientific imaging technology.

After moving to Nikon Instruments Dr. Mann took over Business Development & Partnerships with the goal to develop Nikons CRO business for North America. Nikon has a large laboratory available equipped for conducting contract research with a focus but not limitation on scientific image acquisition and analysis. Offered are services from general image acquisition and analysis to complex tissue culture and data acquisition."

Tamsin Mansley


Optibrium Inc

"Tamsin E. Mansley, PhD, MRSC, CChem, CSci, is an experienced drug discovery scientist, having worked as a medicinal chemist at Eli Lilly and UCB Research. It was here that she developed her passion for applying computational chemistry and predictive modelling approaches for compound selection and design. Her particular interests lie in coupling machine learning and artificial intelligence techniques with generative chemistry approaches to explore chemistry space and guide compound design.

Since 2005, Tamsin has worked with scientific software providers supporting project teams and their use of computational and cheminformatics applications in drug discovery, enabling them to make informed decisions that will improve the efficiency and productivity of the drug discovery process. Tamsin joined Optibrium in 2015 to develop new opportunities for Optibrium’s fully integrated, elegant software for small molecule design, optimization, and data analysis across North America. In October 2022, Tamsin accepted the role of President at Optibrium's new US subsidiary, Optibrium, Inc. She also leads the global Application Science team, supporting the company’s existing client base.

Tamsin holds a PhD in Organic Chemistry from the University of East Anglia in the UK and pursued Postdoctoral studies in the labs of Prof. Philip Magnus at the University of Texas, Austin."

Naim Matasci

Director of Bioinformatics and Computational Biology

Lawrence J. Ellison Institute for Transformative Medicine

Naim Matasci leads the Ellison Institute’s computational lab as the Director of Bioinformatics and Computational Biology. In his role, he supports the Institute's researchers by providing analytical guidance and expertise across the entirety of the project life cycle. Dr. Matasci earned his MSc in Molecular Biology from the University of Zurich, Switzerland. Later, Dr. Matasci joined the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, to study the evolution of human protein expression for his PhD. He then joined the iPlant Collaborative team at the University of Arizona, now CyVerse, where he helped design and develop a data-centric computational infrastructure for the Life Sciences. His current research areas are digital pathology and genomics, in particular for cancer diagnosis.

Jesse Mayer

Applications Consulting Manager


Mylene Mazza

Sharon McAvoy

J. Eric McDuffie

Director, Investigative Toxicology

Neurocrine Biosciences, Inc.

Dr. J. Eric McDuffie is Director of Investigative Toxicology group at Neurocrine Biosciences, Inc. located in San Diego, CA, USA. He joined Neurocrine in 2021, after a 14-year tenure at Janssen, where he last served as Global Head of Safety Biomarkers/Clinical Pathology. Dr. McDuffie previously served as the Head of Mechanistic & Investigative Toxicology team at Janssen’s La Jolla site. Earlier, he had a 7-year tenure at Pfizer’s Ann Arbor and Plymouth, MI, USA as well as Mississauga, Ontario, Canada site, where he was responsible for providing Lab Core (necropsy &histology) support as well as investigative pathology and immunotoxicology support for Antibacterial, Cardiovascular/Atherosclerosis, Neuroscience, Dermatology, Inflammation, and Oncology projects. At Neurocrine, Dr. McDuffie’s team provides support to early discovery teams to delivery rapid selection and progression of safe neurotherapeutic candidates for clinical trials. He serves as a regulatory toxicology lead for multiple discovery and late stage drug candidates, for example, the treatment of depression, schizophrenia, motor neuron disease and epilepsy. Dr. McDuffie has 21 years of experience in preclinical toxicology, including applications of mechanism-based toxicity moddels to investigate potentially translatable organ-specific liabilities for late stage drug candidates.

Cole McKnight

µPulse Product Manager


Cole McKnight is the product manager for the µPulse product line. He has been working to create lab automation technology with Formulatrix since 2020 with past experience in 3D bioprinting technology. His training is in mechanical engineering with further graduate studies in product design at the University of Pennsylvania. At FORMULATRIX, he manages engineering R&D and instrument/consumables production while facilitating sales, marketing, and customer support.

Shaun McLoughlin

Principle Research Scientist I


Studied analytical chemistry at the University of Illinois Urbana-Champaign with Professor Neil Kelleher concentrating on the articulation of non-ribosomal and polyketide synthesis by top-down mass spectrometry. Joined Abbott Laboratories advanced protein characterization group in Fall of 2005. Has worked on advanced characterization of protein and antibody structure by labeling, H/D exchange and limited proteolysis. Was a foundational member of Abbott's phenotypic screening group and worked in target and mechanism identification. Joined AbbVie at its foundation and continued to work in proteomic, genomic and reference database methodologies for target identification. Joined the genomics research center at AbbVie working to identify protein components in areas of SNP-induced open chromatin. Recently working in chemical biology for targeted protein degradation.

Claire McWhirter

Senior Principal Scientist


"Claire has a MChem and PhD in Chemistry from the University of Sheffield. Whilst studying as an undergraduate she developed an interest in enzymology which lead to a PhD studying the kinetic mechanism of Protein Phosphatase1 (PP1) catalysis and subsequent post-doctoral research positions studying alternative mechanisms of kinase inhibition at AstraZeneca and the role of PP1 in Ischemic cell death at Weill-Cornell Medical School.

Claire is a Senior Principal Scientist at Artios Pharma where she leads the Biochemistry  department. Prior to joining Artios, Claire spent six years at AstraZeneca in the Mechanistic Biology and Profiling group where she specialised in the kinetic characterisation of compounds. Along with the detailed kinetic characterisation of inhibitors, Claire has an interest in developing higher throughput kinetic methodologies to enable the identification of mechanistically differentiated hit series immediately post HTS and how differentiated compound mechanisms may translate into differences in efficacy in both cellular and in vivo systems."

Michael Mellody

Graduate Student Researcher

University of California, Los Angeles

My name is Michael Mellody and I am a PhD student in the department of Bioengineering at UCLA. I am co-advised by Prof. Robert Damoiseaux and Prof. Dino Di Carlo. I have several years of research experience in developing new technologies to facilitate high-throughput drug discovery and screening. My research interests include automation technologies, robotic systems, machine learning and artificial intelligence, and microfluidics.

Adriana Migliuolo

Lane Milde, Ph.D.

Senior Scientist


Lane Milde is a Senior Scientist supporting laboratory automation and liquid handling workflows and instrumentation for Compound Management & Distribution at Pfizer within Worldwide Research & Development under Discovery Sciences in Groton, CT. He has been at Pfizer for 10 years and has over 18 years of experience in highly automated laboratories within academic, biotechnology, and pharmaceutical settings. Lane started his career at the University of Wisconsin working as a scientist in molecular biology and high-throughput screening. He spent several years at a small biotechnology company developing automated in-vitro diagnostic devices before joining Pfizer in 2012. In his current role, he is responsible for managing automated microplate and liquid handling instrumentation in support of sample management for early drug discovery. This includes the management of an instrumentation quality control program, maintenance and troubleshooting, LIMS integration, and equipment succession planning as well as developing and maintaining automated workflows and solutions supporting a wide range of sample management processes.

Kevin miller

Chad Mirkin

Tenured Professor

Northwestern University

Chad A. Mirkin, PhD is the Director of the International Institute for Nanotechnology and the Rathmann Professor of Chemistry, Engineering, and Medicine at Northwestern University.  He is a chemist and nanoscience expert, known for his invention of spherical nucleic acids, Dip-Pen Nanolithography and related cantilever-free nanopatterning, materials discovery methodologies, and his contributions to additive manufacturing. He has authored >840 papers and >1,200 patents worldwide (>400 issued) and founded nine companies. Mirkin has been recognized with >230 awards. He served for eight years on the President’s Council of Advisors on Science & Technology, and is one of very few scientists to be elected to all three US National Academies. Mirkin has served on the Editorial Advisory Boards of over 30 scholarly journals, is the founding editor of the journal Small, was an Associate Editor of J. Am. Chem. Soc., and is a Proc. Natl. Acad. Sci. USA Editorial Board Member.

Derrick Miyao

Vice President of Molecular Foundry


Derrick Miyao is the Vice President of Molecular Foundry at DeepCure. Derrick Miyao is a trailblazer in robotic synthesis and automated assays. Derrick joined DeepCure from Neurocrine, where he spent 20 years creating systems for automated drug discovery, including building two systems that can synthesize 10,000 compounds a day and successfully integrate synthesis with affinity binding for closed discovery loop. At DeepCure, Derrick leads the Molecular Foundry, a fully automated synthesis and screening lab in Rehovot, Israel, that will unlock AI and chemistry to get better drugs to patients faster. 

John Moe

Austin Mogen

Field Application Scientist Manager

Corning Life Sciences

Austin Mogen leads a team of Field Application Scientists that covers West USA and Latin America. Before joining Corning, Austin gained industry experience as a senior scientist of upstream process development and manufacturing supervisor for viral vector production. In these positions he focused on cell line and bioprocess development, closed system solutions for cell culture scale-up, and manufacturing of gene therapies. Austin and the Corning Life Sciences FAS team work extensively with research, development, and manufacturing groups to develop 3D assays and disease models, as well as cellular scale-up conditions for viral production, cellular therapeutics, and biologics.

Dean Montano

Senior Product Manager, Sample Automated Solutions

Azenta Life Sciences

Dean started his career as a Telecomms design engineer for Nokia, and has since worked in product management roles at Braemac Ltd and Promethean, as well as product marketing roles at NXP Semiconductors and Cooper Bussmann (part of Eaton). He joined Azenta Life Sciences in 2017 as a Senior Product Manager with responsibility for automated sample storage

Rachel Moore

Senior Research Scientist


I joined AstraZeneca in 2018 following the completion of my PhD at the University of Sheffield, where I investigated how endocytosis regulates the JAK/STAT signalling pathway. Since joining AZ I have worked as a Senior Scientist in the global HTS centre, optimising and prosecuting screens across multiple targets and therapeutic areas, using an array of assay technologies. I am particularly interested in developing new methodologies for use against novel targets, including RNA, and for identifying undesirable hits from HTS outputs to aid prioritisation of quality chemical equity.

Shannon Mumenthaler, PhD

Faculty and Chief Translational Research Officer

Lawrence J Ellison Institute for Transformative Medicine

Shannon Mumenthaler, Ph.D., is an Assistant Professor of Medicine and Biomedical Engineering at the University of Southern California. She is also Chief Translational Research Officer for the Lawrence J Ellison Institute for Transformative Medicine of USC, which is a translational institute that bridges research and innovation by bringing together researchers, patients, and physicians dedicated to improving health of the human condition. Dr. Mumenthaler’s research program is centered around the development and utilization of physiologically relevant, organ-dependent tumor models that allow for the characterization of colorectal cancer cellular dynamics, and serve as a platform for testing specific therapeutic modalities to prevent or delay tumor progression. Specifically, she is integrating biologically-inspired 3D model systems (i.e., organoids and organs-on-chips) with dynamic imaging and computational approaches to provide new insights into the significance of the physical and cellular microenvironment on tumor progression.

Coleman Murray


Ferrologix Inc

Leveraging my experience, qualifications, and passion for bioengineering & mechanical design I can accelerate innovative ideas to products for real world applications. I have a talent for linking early stage technologies to address specific market needs and have experience in growing tech platforms from initial concept to commercialization, with unique expertise in micro/nanotechnologies. In 2015, I founded Ferrologix based on my doctoral work at UCLA and currently serve as Chief Operating Officer where I oversee technical development and management of technical staff. Our company mission and vision is to use cutting edge magnetic nanotechnology to accelerate & scale emerging diagnostics & therapeutics.

Merve Mutlu

Postdoctoral Scholar

Novartis Institutes for BioMedical Research

Merve Mutlu is a postdoc with two years of experience working at Novartis Institute of Biomedical Research. Throughout her academic career, Merve specialized in CRISPR technology and genome-wide phenotypic screening to identify mechanism of action of therapeutic agents. In her PhD, she accomplished unveiling new key regulatory elements of radiotherapy response in breast cancers. In Novartis, she expanded her interest unveiling working principles of agents to the field of targeted protein degradation (TPD). Besides her postdoctoral research, as an early career professional in ELRIG networking group, she organized the first SLAS-ELRIG networking meeting in Basel in June 2022 where she initiated a hub of scientific collaboration in the field of TPD between pharma, academia, and biotech companies. Merve is a passionate researcher with positive attitude and tireless energy to seek the mysteries of cellular mechanisms. She balances her work enthusiasm with outside work activities such as bouldering and dancing.

Omprakash Nacham

Sr. Scientist


I have completed my Ph.D in Analytical Chemistry at Iowa State University. Following graduation, I conducted my postdoctoral studies at the University of Minnesota where I developed bioanalytical techniques to understand autophagy biology in mammalian systems. I have started my industrial career at PPD (CRO) and acted as subject matter expert on oligonucleotide analysis for multiple stability programs. After moving to Abbvie, I have worked on developing various LC-MS/MS targeted metabolomics and proteomics workflows to understand disease biology for various early discovery programs.

Kristen Nailor

Principal Scientific Manager, Biologics Sample Management

Genentech, Inc

Kristen Nailor is a Principal Scientific Manager and leader of the Biologics Sample Management Group at Genentech, Inc.  Kristen holds a degree in Biochemistry from Indiana University. She began her career at GlaxoSmithKline where she spent 7 years as a medicinal chemist. She then transitioned into the Sample Management world in 2010 when she accepted a position as the head of Compound Management at Vanderbilt University.  At Vanderbilt, she built a robust compound management facility and workflows that supported a wide variety of academic drug discovery programs and industry collaborations. After almost 5 years at Vanderbilt, she became the leader of the La Jolla based Compound Logistics team at Janssen Pharmaceutical Companies of Johnson and Johnson in 2014.  In addition to leading her team, she was also a key member of a global core team tasked with implementing a Mosaic Sample Management Software rollout and laboratory infrastructure upgrade across multiple sites. Since 2017, she has been the group leader of the Biologics Sample Management Group at Genentech in South San Francisco, CA.  As interest in biologics and new modalities have grown across the industry, her current passion is to see biological sample management further expanded and elevated to a higher level of throughput, efficiency and impact as small molecule sample management in the drug discovery process. Kristen is also a dedicated advocate and active volunteer in the broader Sample Management Community, and currently serves as one of the Chairs of the SLAS Sample Management Special Interest Group, as well as the program committee for the 2021, 2022 and 2023 SLAS Americas Sample Management Symposia.  She is also the co-chair for the SLAS 2023 International Conference and Exhibition.

Andrew Napper

Head of Automation and Assay Technologies

Bristol Myers Squibb

Dr. Andrew Napper studied at the University of Oxford and Penn State University before working in the Boston area for Genzyme, Enanta, ArQule, and Elixir Pharmaceuticals. While at Elixir, he played a leading role in the discovery of selisistat (EX-527), which was licensed to Siena Biotech and progressed to Phase II clinical trials as a treatment for Huntington’s disease. In 2005, he joined the University of Pennsylvania to direct one of the labs in the Molecular Libraries Screening Center Network. Dr. Napper joined Nemours in 2009 to establish a lab focused on the discovery of targeted therapies for rare pediatric diseases. After eight years at Nemours, he joined FLX Bio in the San Francisco Bay Area for one year before moving to Evotec as Vice President of Discovery Sciences and Princeton Site Head. From Evotec he joined BMS in March 2021 as Executive Director, Head of Automation and Assay Technologies. Dr. Napper was co-chair of the SLAS 2020 International Conference, and currently he serves as co-chair of the Screen Design and Assay Technology Special Interest Group and a member of the Awards and Grants Committee.

Joe Negri

Jon Newman-Smith

R&D Director


Nicole Nguyen

Software Product Manager

Artel Portfolio - Advanced Instruments

Nicole Nguyen is the Software Product Manager at Artel. She has over a decade of experience with software development teams and is a Certified Software Test Engineer (CSTE). Her commitment to quality user experience and the ability to represent the voice of the customer enable the delivery of  software products that meet the needs of laboratories and scientists across industries.

Ekaterina Nikolov

Senior Application Scientist

Protein Fluidics, Inc.

Dr. Nikolov is a Physician-Scientist with 10+ years of academic and industrial experience in cancer biology and cell imaging. She has a broad background in solid tumor models, tumor microenvironment and immunotherapy.  In her previous experience she led the development of 3D micro-tumor assay from biopsies to predict patients’ response to therapy to improve outcomes. She developed the T cell-based platform for phenotypical screening of a library of new compounds targeting senescence. In her current role at Protein Fluidics, Dr. Nikolov leads the projects on 3D cell-based assay development and automation using microfluidic based PuMA System. Her work involves innovating 3D cell-based applications with the Pu·MA System, high-content imaging and plate-reader based assays.

Michael Nilsson

Assistant Engineering Director, Liquid Handling


"As the head of Liquid Handling Product Management and Engineering at Formulatrix, Michael's focus is to ensure that our products continue to move the needle on innovation, efficiency, and transforming the status quo of scientists' and researchers' experience with lab automation.  Our Mantis and Tempest dispensing platforms continue to evolve with new features to address the needs of researchers seeking to miniaturize and simplify workflows.  Our new F.A.S.T. and FLO i8 systems bring to bear some of the easiest-to-use software interfaces that are enabled by the thoughtful and modern use of sensors and imaging systems designed into the instruments.  Our Rover Lab Automation system is helping to close the last mile problem of current state-of-the-art lab automation installations to fully connect islands of automation into truly seamless workflows.

Formulatrix is committed to continually engineering and innovating our existing and new products and projects.  We are constantly deriving new ideas and insights from our customers and their challenges.  Please feel free to stop by our booth to say ""Hi!"" and to discuss your ideal vision for the future of laboratory and pharmaceutical research."

David Nippa

Doctoral Researcher

LMU Munich / Roche

David Nippa is a Doctoral Researcher working on digitalization and automation in Medicinal Chemistry at Roche Innovation Center Basel (RICB) and LMU Munich. His research focuses on combining high-throughput experimentation (HTE), data science and machine learning to accelerate drug discovery. David completed his undergraduate studies at the Technical University of Munich (TUM), Nanyang Technological University (NTU) Singapore and The Scripps Research Institute (TSRI) San Diego. In parallel to his studies, he conducted internships at Wacker Chemie and Roche.

Qiankun Niu


Emory University

Qiankun Niu, Ph.D., is an instructor in the Department of Pharmacology and Chemical Biology at Emory University School of Medicine. She is interested in understanding how cancer genetic alterations contribute to tumor initiation and progression, and identifying potential therapeutic targets for precision medicine. Her work focuses on interrogating oncogenic mutation-mediated differential protein-protein interactions to inform the molecular basis and functional significance of driver mutations in cancer for therapeutic innovation.

John Nolan


Scintillon Institute

John Nolan is a Professor at the Scintillon Institute, where his group develops new tools for cell and molecular analysis. He received BS degrees in Biology and Chemistry from the University of Illinois and a PhD in Biochemistry from Penn State. He did post-doctoral training at Los Alamos National Lab, where he was later a Technical Staff Member and Director of the National Flow Cytometry Resource. He is also founder and CEO of Cellarcus Biosciences, which offers products and services for extracellular vesicle research. He is on the editorial boards of Cytometry and Current Protocols in Cytometry, past-President of the International Scoiety for Advancement of Cytometry (ISAC), and a Fellow of the American Insitute of Medical and Biological Engineering (AIMBE).

Michael Nosswitz

Application Specialist



University of Zurich: Human biology 

University of Applied science Zurich: 3D cell culture and tissue engineering group 
Department of Oncology, University Children’s Hospital Zurich: Leukemia research group, Drug response profiling team 
since 2021 with Tecan, focusing on the development and support of applications on Tecans liquid handling platforms in cellomics and proteomics area

3D cell culture, tissue engineering, bioprinting, microfluidics, drug screening, personalized medicine"

Kendra Nyberg

Lab Automation, Interim Group Lead

Calico Life Sciences LLC

"Kendra Nyberg is the Group Lead of Lab Automation at Calico Life Sciences. She earned her Bachelor of Science degree at the University of Oregon in Physics and her Ph.D at UCLA in Bioengineering. 

During her undergraduate studies, she conducted research in membrane biophysics, holographic microscopy, and droplet microfluidics at University of Oregon, Harvard and UC Berkeley. For her dissertation at UCLA, she developed a microfluidic platform for rapid phenotyping of cancer cell mechanical properties. After graduate school, she designed microfluidic components for inkjet printers at HP Inc and built out in-house technology for a synbio startup, Triplebar Bio. 

At Calico, Kendra leads a team that develops custom solutions, ranging from liquid handlers, integrated systems and microfluidic technologies, that enable scientists to deepen our understanding of aging."

John O'Rourke

CEO and President


Dr. O’Rourke has 30 years of experience in the research, testing and development of tools and therapeutics for the oncology space.  He received his Ph.D. from the Ohio State University and spent 9 years as research faculty at the University of New Mexico Health Sciences Center. After receiving his MBA from the University of New Mexico Anderson School of Business, John joined Intellicyt/Sartorius.  As Head of Product Development for cell analytics at Sartorius, he led the development and commercialization of reagent, software, and hardware solutions for the high throughput flow cytometry community.  He joined BennuBio as Director of Assay Development where he focused on optimizing workflows and developing new applications for 3D-based flow cytometry. Dr. O’Rourke is currently the CEO and President of BennuBio and leading the company’s commercialization of the Velocyt® LP large particle flow cytometer.

Andrea O'Hara

Strategic Technical Specialist

Azenta Life Sciences

Andrea O’Hara is a technical specialist at Azenta Life Sciences and has over 13 years of experience in next generation sequencing. She earned her PhD from the University of North Carolina at Chapel Hill in genetics and molecular biology and did her postdoctoral training at the National Institutes of Health.

Kristen Olson

Senior Principal Scientist

Xellar Biosystems

Bill Ortiz

Principal Sales Specialist


Bill Ortiz, Principal Sales Specialist, PerkinElmer Life Sciences   Bill Ortiz has over twenty five years of experience in the biotechnology industry developing, selling and supporting multimode plate reader detection technology.  He has spent the last 20 years covering the Northwestern United States supporting PerkinElmer’s assay, screening and plate reader technologies.  

Cristina Ortiz-Mateos

Susan Overby

Gary Pace, Ph.D.

Chief Executive Officer

Cell Microsystems, Inc.

Dr. Pace has over thirty years of experience in the life science field, with 20 years legal and corporate experience and 12 years in biotech research for large and small companies. He is a registered patent attorney with a record of over 40 issued US patents. Since 2001 he has helped many early and development stage companies in the life sciences with their strategic, intellectual property, and transactional activities. Dr. Pace has held executive management positions in several companies, including Novartis Corporation, Gentris Corporation, Quill Medical, Inc., and BASF Corporation. Dr. Pace has a J.D. degree from the School of Law at North Carolina Central University, and his Ph.D. from North Carolina State University. He has been CEO at Cell Microsystems since 2014.

Chorom Pak


Lynx Biosciences, Inc.

Dr. Chorom Pak launched Lynx Biosciences, Inc. (LynxBio) to commercialize MicroC3™, a multi-omic microfluidic platform developed while earning her PhD in Molecular and Cellular Pharmacology from the University of Wisconsin – Madison. The technology was born out of an interdisciplinary collaboration between cancer biologists, physicians, biomedical engineers, physicists, and biostatisticians to solve the technical challenge of characterizing suspension cells in a miniaturized manner that would recapitulate individual patients’ disease. LynxBio is partnered with multiple pharmaceutical companies to leverage the MicroC3™ technology for immuno-oncology drug discovery and development. Before creating LynxBio, Chorom was the clinical and R&D lead at Cellectar Biosciences, Inc. (NASDAQ:CLRB), where she co-developed a drug against hematological malignancies and advanced it to Phase 2 clinical trials. Dr. Pak was awarded the Biocom Catalyst Award, holds seven patents, and has over 13 years of experience with hematological cancers and development of microfluidic platforms.

Chris Parker

Associate Professor

The Scripps Research Institute

Chris earned his B.Sc. in Chemistry from Case Western Reserve University (2007). He did undergraduate research in the lab of Philip Garner working on synthetic methodology and the synthesis of alkaloid natural products. He received his Ph.D. in Chemistry from Yale University (2013), under the supervision of David A. Spiegel. During his graduate studies he developed a class of bifunctional molecules that recruit endogenous antibodies to specific disease targets, such as HIV, resulting in their immune-mediated clearance. He carried out postdoctoral studies under the supervision of Ben Cravatt as a fellow of the American Cancer Society at The Scripps Research Institute, where he developed chemical proteomic platforms aimed towards expanding the ligandable proteome. Chris, currently an Associate Professor, started his independent lab at Scripps in August 2018 in the Department of Chemistry where his group develops chemistry-centric strategies to investigate human biology in therapeutic contexts.

Samir Patel

Application Scientist

Nexcelom from PerkinElmer

Samir Patel is an Application Scientist as part of the Advanced Technology R&D Team at Nexcelom from PerkinElmer, Lawrence, MA. His primary focus is to develop collaborations with a variety of scientific communities, including immunology, microbiology, oncology, and cell/gene therapy. He assists these communities with assay development, experimental design, initial feasibility testing, including on- and off-site support for the Cellometer, Cellaca, and Celigo image cytometry instruments. Additionally, he works with collaborators to author papers for submission to journals. He received his B.S. in Biology from Providence College (2006-2010) and his Ph.D. in Immunology and Microbiology from University of Massachusetts Medical School (2012-2018).

Noelle Peeters

Gianluca Pegoraro

Facility Head

National Cancer Institute

Dr. Pegoraro heads the High-Throughout Imaging Facility (HiTIF), which provides NIH intramural investigators with the expertise and the technology needed to set-up, optimize and implement high-content imaging (HCI) assays. HCI assays are used to analyze large numbers of experimental conditions, such as in functional genomics or chemical compounds screens. In addition, the HiTIF applies HCI in combination with single-cell image and data analysis to quantify exceedingly rare but biologically important events in heterogeneous populations of cells.

Taci Pereira


Systemic Bio

Taci Pereira is Chief Executive Officer of Systemic Bio, a 3D Systems biotech company focused on the development of vascularized organ models made out of hydrogels and human cells to be used for drug discovery and development. Ms. Pereira joined 3D Systems as Vice President and General Manager of Bioprinting in May 2021 from Allevi, where she was Chief Scientific Officer and led the company’s exit. She holds a Bachelor of Science in Bioengineering from Harvard University, where she worked at the Wyss Institute for Biologically Inspired Engineering. Ms. Pereira’s research at the Mooney Laboratory for Cell and Tissue Engineering (Wyss) focused on biomaterials for cancer immunotherapy, under the advisory of David Mooney, Ph.D.

Nisha Peter

Senior Research Scientist

Discovery Biology , AstraZeneca

Nisha works within Discovery Sciences at AstraZeneca , where she is responsible for building cell-based assays to support early drug discovery projects, primarily against Oncology targets. She received her PhD Biochemistry degree from the University of Sussex , UK and has done a post-doc at the Wellcome Trust funded – Sussex Drug Discovery Centre.

Carl Peters

Senior Applications Scientist

BMG Labtech

Dr. Carl Peters is a microplate reader senior application scientist with BMG LABTECH. He obtained a PhD in Cell and Molecular Biology from Northwestern University while studying Protein Kinase C signaling. He also has a B.S. in Biology from Hastings College. Prior to BMG LABTECH, he was an adjunct or assistant professor of Biology, Biochemistry and Molecular Biology at several different universities.

Timothy Petrie

Head of Pharmaceutical R&D Tools


Timothy Petrie (PhD, MBA) is the Head of Pharmaceutical R&D Tools at Draper (Cambridge, MA), a non-profit engineering innovation company where he guides business development for organ-on-chip, medical devices, and diagnostic technologies.  Prior to this business role, he was Principal Investigator for numerous commercial- and government-sponsored programs within the organ-on-chip, tissue engineerin, and diagnostics space at Draper. Tim received his PhD in Bioengineering from Georgia Tech, MBA from Indiana U, and completed postdoctoral work at the NIH and University of Washington. He has over 35 peer-reviewed journal articles and holds 6 issued patents.

Janette Phi



Janette has over 25 years of research and business experience in life science instrumentation and reagent companies. Experienced executive in both small start-ups as well as Fortune 500 companies. Extensive knowledge of the bio-analytic sector, functional expertise in the inbound and outbound aspects of marketing, sales, business development, and launching new technologies into the market. Involved in raising over $100M in corporate and venture funding at five companies. Inventor or co-inventor of 8 issued patents.

Piotr Pierog

VP, Precision and Translational Medicine

AffiniT Therapeutics

Piotr L. Pierog, Ph.D. earned a Ph.D. degree from Rutgers University in Biomedical Sciences. In his decade long professional career, Piotr held roles of increasing responsibilities at global pharmaceutical companies including: Takeda, Novartis, Pfizer, Bristol Myers Squibb and Johnson & Johnson; ranging from target discovery to late-stage development. In his previous role at Novartis Piotr was responsible for aspects of product development and precision medicine where he contributed to the global regulatory approval of cell therapy product for pediatric patients with acute lymphocytic leukemia. More recently, Piotr built and led a Translational Medicine and Clinical Pharmacology teams in cell therapies responsible Phase 1 and pivotal clinical trials at Takeda. Piotr is currently contributing to a built of a T cell receptor (TCR) startup biotechnology company in Cambridge, MA.

Ashwin Pillai

Automation Scientist

Ginkgo Bioworks

My name is Ashwin Pillai; I currently work at Ginkgo Bioworks in Boston, MA as an Automation Scientist in the High Throughput Screening Group. I graduated from University of Illinois with a B.S. in Ag & Bioengineering with a minor in Integrative Biology. I have also completed a Bioinformatics Certificate from Harvard Extension School. My role involves bridging the gap between Automation, Biology, and Data with a guiding principle of making the lives of scientists easier by enabling the utilization of automation technologies and data tools. I work directly with scientists to onboard new assays onto robotic platforms, to improve data pipelines for new instruments and metadata capture, and enabling new technologies to scientists to execute on their lab work more efficiently. Previously, I have contributed to R&D in Pharma at Bristol Myers Squibb in Lead Discovery (uHTS), supporting Lead Profiling (ADME-Tox) across multiple robotic platforms (HighRes Bio Cellario, Thermo Momentum). In addition, to supporting Pfizer’s Antibody Discovery Group.

Zachary Pitluk

VP of Life Sciences

Paradigm4, Inc

"1991 PhD Molecular Biophysics and Biochemistry Yale University

1991-1995 Postdoctoral Fellow MBB Yale University
1995-1997 Assistant Research Faculty MBB Yale University
Sales roles at ISCO, BMS, Clontech, Cellomics
VP of Sales at Definiens
VP of Sales at GNS
COO at Proveris Scientific
Currently head of Sales and Marketing at Paradigm4"

Reid Powell

Research Assistant Professor

Texas A&M

Dr. Powell has a diverse research background, with expertise in cell and molecular biology, computer science, and lab automation. He graduated from Texas Tech University with a B.S. in Biochemistry and a minor in Biology in 2012. He then went on to obtain his PhD in Medical Science from Texas A&M University, which he completed in 2018. He has continued his academic career as a post-Doctoral research fellow and now as an Assistant Research Professor in the Gulf Coast Consortia’s Combinatorial Drug Discovery Program and High Throughput Flow Cytometry Programs at Texas A&M Institute of Bioscience and Technology. He has developed a wide array of image-based, flow-based, and biochemical high throughput screening platforms, which have been applied to the development and repurposing drugs across multiple disease contexts including cancer, pathogenic infections, and neurologic disorders. Dr. Powell's research interest also include the development and implementation of methods used to contextualize high dimensional data via integrative machine learning approaches that combine genomics, transcriptomics, chemical, image-derived and drug susceptibility data sources. To support these efforts Dr. Powell has built and maintains a distributed computing cluster that is housed between multiple CPRIT funded core facilities.

James Prescott

Field Applications Scientist

Beckman Coulter Life Sciences

James Prescott is a Field Applications Scientist for the BioLector XT microbioreactor based in Denver, CO. He conducts trainings and provides support to help BioLector users optimize their microbial screening workflows. Prior to joining Beckman Coulter Life Sciences, James was a development scientist for Aalto Scientific Ltd, a biotech company that manufactures controls and calibrators for in vitro diagnostics. He was responsible for the research and development of manufacturing recombinant proteins as well as designing native protein purification schemes. For his education, James received both his BS and MS in biology from Georgia College & State University where he concentrated his studies in microbiology. He published some of his research on detecting foodborne bacterial pathogens in oysters in coastal Georgia.

Raymond Price

Chief Business Officer

Neuroservices Alliance

"Raymond Price, PhD, MBA, is the Chief Business Officer at Neuroservices Alliance. His role is as a pharma/biotech business development executive responsible for increasing sales and managing collaborative R&D agreements for Neuroservices Alliance as part of the commercial team. 

He has an MBA from INSEAD (2009), and has work experience in Japan, the US, and France. He also has a Ph.D. in Pharmacology from Vanderbilt University and extensive R&D experience. Finally, he's the founder and owner of a (profitable!) small business that performs solutions services (medical writing and editing) for non-native English speakers, with global clients in more than 10 countries."

Laralynne Przybyla

Assistant Adjunct Professor, Director

UCSF, Laboratory for Genomics Research

"Laralynne Przybyla received her PhD from MIT where she studied the role of autocrine signaling in mammalian development using custom-engineered microfluidic platforms. Her subsequent postdoctoral work at UCSF expanded on this to investigate how mechanical signaling dictates developmental cell fate transitions. Since then, her research across academia and industry has involved generating model systems based on pluripotent stem cells, setting up custom functional genomics screening platforms for human developmental and disease biology, and developing next-generation high-throughput assays for small molecule and genetic screening applications. 

Dr. Przybyla is currently UC Scientific Director at the Laboratory for Genomics Research and an Assistant Adjunct Professor in the Biochemistry and Biophysics Department at UCSF, where her research is focused on applying CRISPR-based functional genomics screening techniques to sophisticated human cell-based disease-relevant models and assays to uncover new biology and identify novel therapeutic targets."

Emmanuel Quevy


Probius Inc

"Emmanuel P. Quevy, Ph.D., is co-founder and CEO of Probius.

Emmanuel applies his expertise in advanced sensor products and technologies and his experience in entrepreneurship and technology transition to a commercial scale. Before founding Probius, he was responsible for engineering and technology at SDI, overseeing product and technology roadmaps of inertial guidance systems and managing strategic customer programs with Boeing, the US Navy, and other key accounts. Prior to that, he was co-founder, president, and CTO of Silicon Clocks, which was acquired in 2010 by Silicon Laboratories (NASDAQ:SLAB) and where he served as director of MEMS engineering for timing products.

Dr. Quevy’s 20 years of experience in the design and integration of complex sensor technologies include co-authoring more than 40 publications, co-inventing more than 40 issued US patents, and serving as a reviewer and committee member of various journals and conferences. 

His engineering degree from ISEN Lille, France, and M.Sc. degree in electrical engineering and computer science from the University of Science and Technology of Lille (USTL), France, preceded his Ph.D. degree in electrical engineering from UST, with post-doctoral work at Berkeley Sensor and Actuator Center where he led the DARPA-funded IMT program."

Luca Raess

Scientist R&D Automatization


Luca Raess is a scientist working on the development of mass spectrometry-based proteomics sample preparation workflows. His specific focus lies in the design, implementation, testing and optimization of automated end-to-end protocols with the ultimate goal is to achieve better laboratory efficiency and reproducibility. He received his education in biotechnology from ETH Zurich before joining Biognosys' R&D team.

Lance Ramsey

Julian Reading

Senior Manager, Flow Cytometry

Allen Institute for Immunology

In my current position of Senior Manager, Flow Cytometry I am building out the FACS and cell sorting capabilities of the Allen Institute for Immunology in support of a multi-center longitudinal human immune system multi-omics study. Previously I served as the FACS and immunology specialist on multiple project teams expediting small molecules and biologics with Gilead Sciences and MedImmune/AstraZeneca and led teams at Wellstat Diagnostics and the NCI.

Huw Rees

Field Applications Scientist

SPT Labtech

After completing a Ph.D. in Chemistry at the University of Chicago, Huw used his expertise in RNA crystallography and the mosquito to join SPT Labtech's application team. With SPT, Huw has become experienced in supporting a wide variety of liquid handling workflows in genomics and drug discovery using the mosquito, dragonfly, and now firefly.

Steve Rees

VP Discovery Biology, Discovery Sciences


Steve is Vice-President of Discovery Biology at AstraZeneca with responsibility for reagent generation and assay development, functional genomics, and cell and gene therapy. Previously Steve led the Screening Sciences department with accountability for Compound Management, Hit Discovery and Lead Optimisation biology. Prior to joining AstraZeneca, Steve worked at GlaxoSmithKline for 24 years in various roles. He has served in many roles within the Society of Laboratory Automation and Screening most recently as Chair of the European Council. He has also served as Chair of the European Laboratory Research and Innovation Group, and is currently Industry Trustee of the British Pharmacological Society. Steve sits on multiple Scientific Advisory Boards including EU-OPENSCREEN, WCAIR at the University of Dundee and the Centre for Membrane Protein Receptor Research (COMPARE). Steve has authored over 70 research papers and was awarded an OBE in 2021 for services to science and the COVID19 response.

Gareth Reid

Senior Automation Scientist

CSL Limited

"Gareth Reid is a Senior Automation Scientist at CSL Limited. He studied in the fields of Software Engineering, computational biology and bioinformatics, as well as completed advanced robotics courses, in particular using liquid handling platforms. He has worked in the areas of clinical genomics, core pathology, research, and pharmaceutical development. 

He specialises in implementing laboratory automation solutions using liquid handlers and track arms to support sample preparation. His current work involves implementing automation solutions using ThermoFisher robotics and Momentum software as the core platform. His key focus is leveraging, off these automation platforms, to implement important peripherals such as automated QC pipelines, data and metrics analytics and dynamic liquid handling protocols, as well as creating tools to allow scientists to actively contribute science during the workflow development.
Gareth has presented at several conferences on these topics, including the New York Genomics Centre in 2015, where he presented a self-developed, fully automated Illumina NGS workflow, to an industry audience still coming to terms with the concept of automating complex, long running assays. 
He is highly experienced in the areas of liquid handling robotics, software & process engineering, bioinformatics and scientific instrument integration."

Michael Rerick



I’m currently an Investigator in the High-Throughput Automation team at GSK with a Ph.D. in Analytical Chemistry.  The goal of my work is to develop efficient analytical protocols for the rapid screening of GSK therapeutic candidates to determine their physicochemical properties.  Our group utilizes an array of solid and liquid dispensing automated platforms to deliver solubility, forced-degradation, and crystallization screens to aid in small molecule drug development.  My role is to serve as a point of contact for internal and external GSK stakeholders by designing, executing, and communicating the results of our analytical workflows.  Prior to joining GSK, I received my Ph.D. at the University of Pittsburgh focusing on bioanalytical separations.  My dissertation concentrated on developing capillary-scale UHPLC methods for biochemical applications including sub-minute online microdialysis separations of neurotransmitters and utilizing microfluidic devices to study ectopeptidase activity using electroosmotic perfusion and LC-MS.

Daniel R. Rines, PhD

VP, Digital Transformation & Tech Enabling Services

Strateos, Inc.

Daniel has more than 20 years of experience in the biopharma industry, working across multiple functional disciplines, including phenotypic assay development, high-throughput screening, and software engineering. Before Strateos, he was a Research Investigator at Novartis (GNF) and led multiple drug discovery campaigns. His research focused on developing novel phenotypic assays across various indications. Daniel received a B.S. in Biochemistry from the University of California at Davis and a Ph.D. in Cell and Molecular Biology from the Massachusetts Institute of Technology (MIT).

Sara Rivera

Lab Manager/ Lecturer

University of Michigan

Sara R. Rivera, PhD is a Lab Manager and Lecturer at the University of Michigan. Focused on researching harmful algal blooms in the Great Lakes, Dr. Rivera works with many collaborators from the Cooperative Institute for Great Lakes Research (CIGLR), NOAA- Great Lake Environmental Research Laboratory (GLERL), and Lawrence Livermore National Laboratory. Her primary work is in Dr. Greg Dick's Geomicrobiology laboratory.

Heaven Roberts

Staff Scientist, R&D, Protein and Cell Analysis

Thermo Fisher Scientific

Heaven’s Ph.D. work at Oregon State University focused on mycotoxin biotransformation and immunotoxicity, which ultimately led to a career in the nutritional specialty products industry. In 2020, Heaven’s experience with cytometric analysis of a wide range of sample types led to her current role developing flow cytometry instrumentation at Thermo Fisher Scientific. She now develops detection and analysis solutions for customers wishing to expand their understanding of cellular systems using flow cytometry and imaging.

Yusuf Roohani

Graduate Student

Stanford University

Yusuf is a PhD student at Stanford University advised by Jure Leskovec and Stephen Quake. He is affiliated with the Stanford AI Lab and the Department of Biomedical Data Science. He works on designing new machine learning approaches for modeling biological systems. In particular, he is interested in how artificial intelligence can inform better experiment design for discovering new medicines. Previously, he worked as a machine learning engineer at GSK where he led a cross-disciplinary team to biologically profile their compound collection.

Renata Roth

Paul Russell

Senior Scientist

Horizon Discovery

Paul joined Horizon in 2012 to work on client lead target validation projects utilizing both CRISPR & RNAi based technologies. For the last few years, Paul has developed and performed pooled and arrayed screening platforms to assess the functionality of Horizon's Pin-Point base editing technology platform. Prior to working at Horizon, Paul performed research at the University of Cambridge, where he studied the early BRCA genetics in Breast & Ovarian cancer with Prof Bruce Ponder. Then with Prof Ashok Venkitaraman, he subsequently studied the role of the spindle assembly checkpoint in determining the outcome from a drug induced mitotic arrest.

Ali Safavi, MS

Founder, President & CEO

Grenova, Inc.

Ali Safavi, founder, President, and CEO of Grenova, is on a mission to enable laboratories around the world to become sustainable and waste-free. Ali founded Grenova, which is short for Green Innovation, shortly after graduating from college using the firsthand experience he gained working in the lab industry. Today, his award-winning company has created the only technology solution in the industry that enables life sciences and healthcare laboratories to reduce their plastic consumables cost and biohazard waste by over 90%. As a result of his work, Grenova's environmental and economic impact on the life sciences industry has so far resulted in 4,581 metric tons in Carbon Emission (CO2e) reduction, 2,650,848 lbs. of biohazard plastic waste reduction, and $84,135,258 in savings and cost reduction.

Nancy Salt

Sarah Sandoz

Operational Manager

Pelago Bioscience

"Sarah Sandoz, PhD is the Operational Manager of the Explore Team at Pelago Bioscience, which conducts proteome-wide studies of target engagement with CETSA.

She holds a M.Sc. in Biology with a major in microbiology and immunology from ETH Zurich and a Ph.D. in Molecular Life Sciences from EPFL Lausanne. Her research has involved studying virus and bacterial toxin entry, cell trafficking and endocytosis as well as protein folding.
She has worked with both the targeted and proteome-wide formats of CETSA at Pelago since 2020 as a Senior Scientist. Since 2022 she has been managing the team working on the proteome-wide studies, where CETSA is combined with quantitative LC-MS based proteomics to give unique insights into global compound-induced effects in the living cell."

Samantha Savage

Senior Customer Success Manager


"Samantha is a Senior Customer Success Manager supporting industry, academic, non-profit and governmental organizations to onboard and fully utilize Quartzy - the world’s #1 lab management solution. Quartzy accelerates science by helping researchers streamline communication, simplify ordering, and track inventory.  Samantha is a dedicated client success advocate and has helped to build the Customer Success program at Quartzy for the last 2 years.  She is an experienced research professional specializing in academic lab management and strategic program development. Samantha has 10+ years experience as a scientist, laboratory manager, community volunteer and mentor. Her passion is to support research groups by applying creative problem-solving skills, knowledge of the field, and attention to detail, while adapting efficiency and organization."

Jonathan Schneeweis

Senior Scientist


"Jonathan provides advanced robotic, informatics, and operational support across multiple facets of drug discovery within the DTMP group at Janssen.  On any given day he may be found designing or implementing new robotics platforms to accelerate drug discovery, supporting or operating one of our existing automation solutions for 1536w uHTS, Lead Evaluation, Phenotypic screening, Biophysics, or Compound Logistics, or designing or troubleshooting some new custom application or informatics solution to streamline data capture and analysis. Jonathan’s happiest at the intersection of Engineering, Informatics, and Scientific discovery crafting and supporting synergistic solutions to enable drug discovery. 

Prior to joining Janssen in 2014, Jonathan brings 15 years of industry experience with Merck, Schering-Plough, and Bristol-Myers Squibb where he spearheaded the design, implementation, and operation of numerous laboratory automation initiatives in support of high throughput screening, high content imaging, lead evaluation and profiling, cell line development, compound management, molecular biology/genomics, and clinical diagnostic applications.  In addition to his wealth of automation experience, Jonathan also has significance experience and expertise designing, implementing, and supporting screening informatics and compound logistics IT solutions blending commercial solutions with custom application design to accelerate and automate drug discovery sample tracking and data analysis. 

Jonathan earned a Masters of Engineering degree, in Biotechnology, from the University of Pennsylvania, and two Bachelor of Science degrees, in Vertebrate Physiology and Nutritional Biochemistry, from Penn State University."

Craig Schulz

Head of Automation

Terray Therapeutics

Chemist converted to engineer.  I have been handling laboratory automation for 20+ years, spanning early discovery to clinical development for both small and large molecule workflows.  Experienced in system integration of commercial systems but really enjoy de-novo design of automated systems.  19 years in big pharma, 2 years at a start-up.

Kathrin Schumann

Assistant Professor

Technical University of Munich

"Prof. Dr. Kathrin Schumann is heading the laboratory ""Engineering Immune Cells for Therapy” at the Technical University of Munich (TUM). She studied biochemistry at the University of Tübingen and obtained her Ph.D. at the Max Planck Institute of Biochemistry in Martinsried. After a research stay at Novartis Institutes for Biomedical Research, Basel, she continued her research at the University of California, San Francisco. While working in the laboratories of Alex Marson and Jeffrey Bluestone, she developed CRISPR technologies for the engineering of primary human T cells. In 2018, she was appointed Rudolf Mößbauer Tenure Track Assistant Professor at TUM School of Medicine.

Prof. Kathrin Schumann’s research is focused on human immune cell engineering. She uses innovative CRISPR technology to ablate or modify genetic regions in human T cells in order to characterize their role in cellular function and stability. In the long term, this knowledge may help to develop new therapies for the treatment of autoimmune diseases and cancer."

Tanja Seifert

Vishwesh Shah

PhD Candidate

University of California, Los Angeles

Vishwesh has over seven years of experience in life sciences research. His previous work involved studying cancer cell metastasis, and discovering novel pathways to inhibit cancer cell motility and proliferation. His current work involves building accessible droplet technologies that are compatible with minimal instrumentation for scalable and accessible assays. These are now being combined with low cost readers to enable technologies that are deployable in low-resource settings to improve health in underserved communities.

Katheryn Shea

Vice President, Repository and Innovation

Azenta Life Sciences

Kathi Shea is the Vice President of Repository and Innovation at Azenta Life Sciences.  She has been a member of ISBER since its inception in 1999 and served on the ISBER Board for 8 years in various roles, including Director, Secretary Treasurer and President.  She remains active in the Society today through participation in Society meetings, committees and working groups. In 2020 she was awarding the ISBER awarded the Distinguished Leadership award in 2020. Kathi also served on the Advisory Working Group that developed the College of American Pathologists Biorepository Accreditation Program and was an active member of the CAP BAP Committee for 6 years.  She has over 30 years of experience leading biorepository programs and advising government, academia, pharmaceutical and other life science companies on the design of biorepositories, quality systems, and optimal methods for collection, preservation and annotation of biospecimen collections.

Antony Sheehan

Director of Immunoassays (Site Head)

TGR BioSciences

A commercially minded biotechnology scientist with over 15 years industry experience in the development/commercialization of immunoassay screening technologies for academics, pharma/biotech's and diagnostics. Lead the team in South Australia and its ongoing investment in the AlphaLISA SureFire Ultra platform for measurement of high value drug targets (kinases) for pharma/biotech drug discovery programs.

Linda Sheehy

Xiling Shen


Xilis Inc

Dr. Shen is currently a professor and the chief scientific officer of the Terasaki Institute for Biomedical Innovation and the founder and chief executive officer of Xilis Inc, which raised an $89M Series A to advance precision medicine. He was formerly the Hawkins Family Associate Professor in the Department of Biomedical Engineering and the director of the Woo Center for Big Data and Precision Health at Duke University. He received his BS, MS, and PhD degrees from Stanford University and the NSF career award at Cornell University. He was the steering committee chair of the NCI Patient-Derived Model of Cancer Consortium, co-chair of the NCI Tissue Engineering Consortium, and cancer track chair of Biomedical Engineering Society 2019. His lab studies precision medicine from a systems biology perspective. Areas of interests include cancer, stem cells, the gut-brain axis, and microbiome.

Ian Shoemaker

Senior Applications Scientist

Beckman Coulter Life Sciences

Graduate of University of Arizona (BSE) with 13 years of lab automation and instrumentation experience in automated extraction, personalized medicine and clinical molecular diagnostics.  Formerly an instrumentation core manager and on-site repair and technical services provider, in his role at Beckman Coulter Life Sciences Ian focuses on applying his integrated sytems hardware & software skills to nascent and novel applications and vendor collaborations.

Marc Siladi

Kaylene Simpson

Head, Victorian Centre for Functional Genomics

Peter MacCallum Cancer Institute

Prof Simpson Heads the Victorian Centre for Functional Genomics, a technology platform at Peter MacCallum Cancer Centre. She plays a critical role in driving new research enterprises by actively guiding discovery-based screening projects from concept and funding applications, through the assay development phase, screen execution and data analysis. Her laboratory supports compound, CRISPR and RNAi screens in both 2D and 3D settings with a strong emphasis on quantitative cell phenotyping using high content imaging. Her lab has developed automated 3D screening pipelines using cell lines, PDX and patient derived materials, successfully screening compound libraries and performing 2- and 3-way drug synergy studies. The VCFG team have developed machine learning strategies to analyse patient derived organoids across many individuals and can quantify organoids at whole-well or as single structures, allowing us to dissect tumour heterogeneity and drug response.

Ilyas Singec

Chief Scientific Officer

FUJIFILM Cellular Dynamics Inc.

Ilyas Singeç is currently the Chief Scientific Officer of FUJIFILM Cellular Dynamics, a global developer and manufacturer of human cells derived from induced pluripotent stem cells (iPSCs). Prior to this role, he served as the inaugural director of the Stem Cell Translation Laboratory (SCTL) at the National Institutes of Health (NIH). The SCTL was funded by the NIH Common Fund (Office of the NIH Director) with the mission to help advance the iPSC technology into clinical applications and drug discovery by developing innovative foundational technologies that can be broadly utilized. At NIH, he introduced novel methods for iPSC culture, single-cell cloning, and genome editing. He also pioneered industrial-scale robotic cell culture and the development of advanced cell differentiation protocols. Prior to this role, Dr. Singeç held leadership positions at Pfizer and the Sanford-Burnham-Prebys Medical Discovery Institute focusing on cell reprogramming and genetics-based target identification and validation for neurological and psychiatric disorders. Dr. Singeç received his MD and doctoral degree (summa cum laude) from the Universities of Bonn and Freiburg (Germany) and completed training in anatomy and clinical neuropathology.

Avtar Singh

Principal Scientist


Avtar Singh is a Senior Scientist in the Cell and Tissue Genomics Department at Genentech, where he develops new approaches for image-based screening and high-throughput biological discovery. During his postdoc with Paul Blainey at the Broad Institute, he established optical pooled screens as a method for high-content screening of genome-scale CRISPR libraries. Prior to that, he specialized in super-resolution microscopy and single-molecule imaging during his PhD in Warren Zipfel's lab at Cornell University.

Nikhita Singh

Co-Founder & CPO


"Nikhita is the Co-founder and Chief Product Officer of Artificial, a first-of-its-kind lab automation platform that lowers the barrier of adopting automation so labs can accelerate their next breakthrough. Prior to Artificial, Nikhita was a researcher at the Personal Robots Group at the MIT Media Lab where she designed and studied socially intelligent robotic and AI platforms.

Nikhita also drove product at Palantir for several Fortune 500 companies and government agencies in the US and Europe. She has worked at various startups including Rypple (acquired by Salesforce), Loose Button, and university research labs such as UC Berkeley AutoLab, Robarts Research and CSTAR.

Nikhita received her M.Sc. in Media Arts & Science at the Massachusetts Institute of Technology and her B.Sc. in Industrial Engineering and Operations Research at University of California-Berkeley.

Outside of her work, Nikhita mentors founders and companies as a Founder Advisor at the MIT Engine and Climate Capital Bio, and can be found designing disaster relief solutions with the Field Innovation Team, obsessively trying to conquer the Sunday NYT crossword, or building fun projects in the machine shop."

Oksana Sirenko

Sr. Scientist

Molecular Devices

Dr. Sirenko is an established cell biologist and imaging specialist who is an expert in developing assays with complex cell-based models for research and drug discovery. She is a senior scientist at Molecular Devices where she works on development of high-content imaging methods to the analysis of novel cell systems. Dr. Sirenko currently leads a group of scientists developing methods and new tools for automation of 3D cell models – including organoids and organ-on chips – for modeling cancer, neurotoxicity, and toxicology. Dr. Sirenko holds a PhD in Biochemistry/Biophysics, has over 15 years of industry experience, and has authored more than 35 scientific papers.

Zachary Sitte

University of North Carolina At Chapel Hill


Zack completed his undergraduate studies at Rensselaer Polytechnic Insititute studying Chemistry and Biochemistry/Biophysics. He is currently a 4th-year graduate student at the University of North Carolina at Chapel Hill studying under Dr. Matthew Lockett. His focus is on developing 3D cell culture models that are more representative of in vivo conditions.

Sara Siwiecki

PhD Candidate

Yale University

Sara Siwiecki (she/her) is a PhD candidate at Yale University in Molecular Biophysics & Biochemistry and a graduate of Chapman University with a BS in Biochemistry. Sara's thesis focuses on the evolution of jellyfish from a materials science perspective and uses various biochemical and biophysical techniques. Outside of her thesis research, she is a disability advocate for scientists. At Yale, she is a leader of the Graduate Student Disability Alliance, which is a disability advocacy group for graduate students, and a leader of the Disability Peer Mentorship Program, which is a program that facilitates peer mentorship for disabled students on campus. She has also worked with LabVoice to imagine how digital assistants can improve lab accessibility and participated in the SLAS's New Matter podcast about conversations around accessibility in the lab. She envisions a future where scientists feel welcome and successful in their labs through advancements in new assistive technology for lab equipment and improvements in conversations around disability in STEM. She would be happy to chat with anyone about science accessibility (or why jellyfish are super cool!) 

Nikolai Slavov

Associate Professor

Northeastern University

Nikolai Slavov is an Allen Distinguished Investigator and associate professor at Northeastern University in the Bioengineering Department and Barnett Institute. His lab has pioneered several multiplexed experimental methods for quantifying proteins in single cells and is developing new computational methods for analyzing and understanding single-cell protein data. He organizes the annual single-cell proteomics conference ( and contributes to organizing other leading conferences, including HUPO, Oxford Global, NeurIPS, and others. The Slavov lab obtained direct evidence for a new regulatory mechanism of protein synthesis (ribosome specialization) and continues to drive research in this emerging field. Research from the Slavov lab has been recognized and supported by many prestigious awards, including the Allen Distinguished Investigator Award, the NIH Director’s Award, the Chan Zuckerberg Initiative. Nikolai Slavov received BS from MIT in 2004, a PhD from Princeton University (Botstein laboratory) in 2010 and conducted postdoctoral research in the van Oudenaarden laboratory at MIT.

Andrew Smith

Senior Automation Engineer


Andrew Smith is Senior Automation Engineer at AstraZeneca, based in Maryland. He has a background as a scientist at various pharmaceutical and biotech companies, and eventually made the transition into automation engineering specializing in automated analytics and Tecan liquid handlers. He holds a bachelor’s degree in biomedical sciences from Nottingham Trent University.

Joshua Smith

Global Lead for Industry Partnerships, Accelerated Discovery Strategic Partnerships and Operations Research

IBM T.J. Watson Research Center

"Joshua Smith received his Ph.D. in Electrical Engineering from Purdue University in 2011 on a National Science Foundation Graduate Research Fellowship Award, joining the IBM T. J. Watson Research Center as a Research Staff Member.  With a background and training in low-dimensional nanoelectronics, Dr. Smith developed a growing interest in biomedical engineering and biotechnology, and in 2013 he helped establish the Translational Systems Biology and Nanobiotechnology Group at IBM Research and later managed the Molecular Health Solutions Group, overseeing R & D efforts for microfluidic devices aimed at separation and detection of single molecules for advanced biomedical diagnostics and preparative technology solutions.  After serving as the technical assistant to the Vice President of Healthcare and Life Sciences at IBM Research from Nov 2020 to Jan 2022, he joined the Accelerated Discovery team focused on holistic acceleration of scientific discovery workflows for healthcare and materials research.   

Dr. Smith has held an Adjunct Assistant Professor position at Columbia University in the Department of Electrical Engineering and is an IBM Master Inventor with more than 80 filed patent applications and over 50 granted patents.  He has co-authors 22 peer-reviewed journal articles, and his research has been highlighted by Forbes, CNN Money, IEEE Spectrum, and Pharma Technology Focus among other media outlets as well as on-stage at TED."

Luisa Smith

Veronica Soloveva

Principal Scientist, HCI group at QB



Ph.D. Biochemistry, 1996
University of Illinois at Chicago, Department of Biochemistry, College of Medicine, Chicago, IL
Awards: 1993-American Diabetes Association student research award.

MS. Biochemistry and Molecular biology, 1990
Moscow State University, Department of Molecular Biology, Moscow, Russia
Awards: 1990 -""Cum Laude"" Diploma of Moscow State University.
1986-1990 - University Academic Award (Moscow State University)

Professional Experience
1)  11/2018- present: Principal Scientist, HCI/QB, Merck Research Laboratories, 
Merck, Boston, MA ,
2) 6/2013- 11/2018: Senior Scientist, Lead in vitro screening, at Therapeutic Discovery Center, Molecular Translational Sciences Division,  USAMRIID 
3) 3/2010- 5/2013: Sr. Scientist, Director, Center for Core Technologies, IPK (Institute Pasteur in Korea),  Seongnam-si, Korea ,
4) 09/2002- 02/ 2010 . Principal Research Scientist II, Group Leader for Cellular Assay Development, Screeening Sciense, Wyeth research , NY & PA, USA
5) 05/1996– 05/2002: Senior Research Associate. Northwestern University, Laboratory of Dr. Daniel I.H. Linzer, Evanston IL 
05/1996– 05/2000 – postdoctoral fellowship"

Alice Soragni

Assistant Professor

University of California Los Angeles

Alice Soragni, PhD, is an Assistant Professor in the David Geffen School of Medicine at UCLA, a member of the Jonsson Comprehensive Cancer Center and of the UCLA Molecular Biology Institute. She has a Bachelor and Master of Science cum Laude from the University of Bologna, Italy and a PhD from the ETH of Zuerich, Switzerland. Her laboratory in the Department of Orthopaedic Surgery at UCLA couples basic research into mechanisms of disease to the development of novel therapeutic strategies. Her expertise lies in the development of tumor organoid models to investigate the biology of rare tumors and perform screenings for functional precision medicine applications.

Glauco Souza, Ph.D.

Director of Global Business Development & Innovation

Greiner Bio-One North America, Inc.

"Dr. Souza is the Director of Global Business Development and Innovation, 3D Culture at Greiner Bio-One and former Adjunct Assistant Professor at the University of Texas Health Science Center at Houston. He is one of the creators of magnetic 3D cell culture, including magnetic 3D bioprinting. Results using these groundbreaking technologies have been reported in various high-impact scientific journals, including Nature Nanotechnology, Proceedings of the National Academy of Sciences, Nature Protocols, Biomaterials, and Nature Reviews Cancer. Recently, his work was selected for the Short List of The Lush Prize for outstanding research producing an effective non-animal safety test. Dr. Souza’s research has been funded by grants from National Science Foundation (NSF), National Institute of Health (NIH), Department of Defense (DOD), Center for Advancement of Science in Space (CASIS), and Texas Emerging Technology Fund (ETF)."

Thomas Spanjers

Global Sales Manager

Lab Services

"Hello, my name is Thomas Spanjers, and I am an accomplished sales manager in the lab automation industry. With over 15 years of experience, I have a proven track record of success in building and leading high-performing sales teams that deliver exceptional results.

I hold a Bachelor's degree in Biotechnology.Throughout my career, I have worked with a wide range of clients in the pharmaceutical and Biotechnology sector, developing and implementing customized lab automation solutions that help them optimize their operations and achieve their business objectives. My extensive knowledge of lab automation technologies and industry best practices allows me to provide expert guidance and support to my clients throughout the sales process. I have a deep commitment to creating a positive, collaborative work environment that fosters success.

I look forward to meet the people visiting the SLAS and am open to all inquiries."

Matthew Spitzer

Associate Professor


Dr. Spitzer completed his undergraduate degree in Biology from Georgetown University followed by graduate training in Immunology at Stanford University in the laboratories of Drs. Edgar Engleman and Garry Nolan. There, he developed experimental and analytical methods to model the state of the immune system and immune responses to cancer using high-dimensional single-cell data. Dr. Spitzer moved to UCSF as a Parker Fellow and a Sandler Faculty Fellow in 2016. He is currently an Associate Professor in the Departments of Otolaryngology-Head and Neck Surgery and of Microbiology & Immunology as well as an Investigator of the Parker Institute for Cancer Immunotherapy and the Chan Zuckerberg Biohub. His research lab uses systems immunology methods including single-cell analysis to understand how the immune system is altered by and mounts responses against cancer.

Guy Starbuck

Co-Founder and CTO

AIQ Global, Inc.

Guy is co-founder and Chief Technical Officer of AIQ Global. Guy has over 20 years of commercial software experience, including 14 years as Software Architect and Development Manager for Yahara Software and Stericycle Inc. working in regulated environments and medical devices. He joined AIQ in 2016 and led the efforts toward FDA clearance and subsequent high-scale cloud deployment of the company's novel technology for evaluation of treatment response in complex diseases.

Diane Stephenson

Executive Director

Critical Path Institute

I am a neuroscientist by training with 30 years combined experience in academic neuroscience and drug discovery. In my academic career, I focused my research on Amyotrophic Lateral Sclerosis and Alzheimer’s disease while in industry I supported identification and validation of new targets for Alzheimer’s disease, stroke and Parkinson’s disease.  While in industry, I developed a passion for public private partnerships and engaged in translational research including biomarker identification and validation across multiple CNS diseases. I joined the Critical Path Institute in 2011 and served as the Executive Director of the Coalition Against Major Diseases (CAMD), a flagship precompetitive consortium focused on streamlining the regulatory path for accelerating treatment of Neurodegenerative diseases.  I presently lead the Critical Path for Parkinson’s, a trans-continental consortium aimed at bringing together Parkinson’s disease data from around the world to accelerate effective delivery of treatments.

Allysa Stern, PhD

Scientist II, Product Applications

Cell Microsystems

Dr. R. Allysa Stern, M.S., Ph.D., is an accomplished cell biologist with extensive experience using cell-based assays to study mechanisms of disease and toxicity. She received her Ph.D. in Physiology from North Carolina State University with a concentration on cellular physiology and disease modeling. She has years of experience developing novel 2D and 3D in vitro models using a variety of cell types from multiple tissues, including primary hepatocytes and stem cells. As a Product Applications Scientist at Cell Microsystems, she leverages her expertise in advanced imaging and cellular and molecular biology techniques for new product and assay development and customer support.

Janick Stucki

CEO & Technical Director

AlveoliX AG, Swiss Organs-On-Chip Innovation, Bern, Switzerland

Dr. Janick D. Stucki is currently the CEO & Technical Director at AlveoliX, a Swiss SME providing innovative in-vitro solutions by combining unique microfluidic chip design with complex organ-on-chip modelling. He studied mechanical engineering at the Swiss Federal Institutes of Technology in Zurich (ETHZ) and holds a PhD in Biomedical Engineering from the University of Bern. He has more than 10 years of experience in developing and commercializing organ-on-chips.

Lorna Suckling, Ph.D.

Team Leader


With 13 years experience in drug discovery, Lorna has worked in both the academic andindustrial fields to gain expertise in high-throughput screening and automation. Shecompleted her PhD in Cancer Therapeutics at the Institute of Cancer Research, London followed by a Postdoctoral research position at Imperial College London where she used automated robotics platforms to develop high-throughput assays for engineering biology. Her current role at GSK includes leading a team to develop cell-based assays, in particular using High-throughput Flow Cytometry, and implementing automation capabilities for complex cell-based screening.

Johan Sunyrd

Scientific Solutions Consultant


"Johan Sunryd is a Scientific Solutions Consultant at Benchling, the leader in cloud informatics for life sciences R&D.  Johan Sunryd works with R&D organizations to understand their informatics needs and identify best ways to augment scientists’ productivity with software solutions. Prior to Benchling, Johan worked as an interdisciplinary scientist and engineer for various medical devices companies, ranging from early R&D to preclinical animal models. His education includes a PhD in Cellular and Molecular Biology from UMass Amherst and a B.S. in Biochemistry from Michigan State University."

Tomoiku Takaku

Hematology Branch

Juntendo University School of Medicine Tokyo, Japan

Ansley Tanoto

Senior Automation Engineer


Ansley Tanoto is a Senior Automation Engineer at Metagenomi, where he works to expand the company's gene editing candidate screening capacity. He uses his scientific/programming expertise to design, build, and facilitate workcell buildouts and expansions. He is also heavily involved in design/deployment of connecting automation to Metagenomi's future LIMS system. Before joining Metagenomi, Ansley held engineering roles at PACT Pharma and Intrexon where he onboarded and transitioned workflows onto newly released platforms such as the Biomek I-series and Hamilton Vantage. Prior to that, he worked in operations development on Twist Bioscience's gene manufacturing workflow. Ansley received a B.S. in Molecular Cell Biology and minor in Bioinformatics from UC Santa Cruz.

Mike Tarselli

Chief Scientific & Knowledge Officer


Mike Tarselli, Ph.D., MBA is the Chief Scientific Officer for TetraScience, a Boston-based start-up building the Scientific Data Cloud. He has held scientific and leadership roles at SLAS, Novartis, Millennium, ARIAD, and Biomedisyn. Mike has received awards and fellowships from IUPAC, Wikipedia, ACS, NSF, and the Burroughs-Wellcome Trust. He volunteers in roles promoting scientific education and diversity, including the National Science Foundation, the Pistoia Alliance, the NIH Assay Guidance Manual, and the UMass College of Natural Sciences Advisory Board.

Austen Terwilliger

Laboratory Director

Baylor College of Medicine

"I'm a molecular microbiologist committed to combating the notorious ESKAPE pathogens and multi-drug resistance. I am developing technologies that evolve and purify bacteriophage (phage) to rapidly generate and formulate therapeutic cocktails. Co-founding the phage technology service center “TAILΦR” provides a unique opportunity to develop intellectual property assets and treat patients on a compassionate use basis.

As Director of Operations for TAILΦR, I coordinate center development, client projects, research, phage discovery, and patient cases amongst team members. I also liaise between clinical, academic, and regulatory teams, including the FDA, for compassionate use patient cases. We are compiling libraries of pathogens and their corresponding phages to reduce response time to the next case or outbreak.

My many passions/hobbies include science outreach, fishing, stand-up comedy, meditation, and steelers football. Maybe one day I'll get to use the kayak I foolishly bought just before the birth of my daughter."

Jeroen Theeuwes

Peggy Thompson

VP Biology


Peggy joined Plexium in 2020 to lead the targeted protein degradation drug discovery efforts. She has more than 20 years of experience in drug discovery and development in the biotechnology industry. Prior to Plexium, Peggy was a co-founder and Executive Director of Biology at eFFECTOR Therapeutics where she established their technology platform for targeting dysregulated mRNA translation for supporting oncology drug development and lead their eIF4A program (Zotatifin, Phase II) from concept to clinical development in solid tumor malignancies. She previously served as Director of Biology at Anadys Pharmaceuticals, Inc. She held positions of increasing responsibility during her tenure including leading the drug discovery biology efforts as well as supporting the development of Setrobuvir until the company was acquired by Roche Pharmaceuticals.

Jörg Tost

Director, Laboratory for Epigenetics and Environment

CEA - National Center for Research on Human Genomics (CNRGH)

Jörg Tost received his PhD in genetics from the University of Saarbrücken (Germany) in 2004 devising novel methods for the analysis of haplotypes and DNA methylation patterns. After a postdoctoral stay in the technology development department of the Centre National de Génotypage (CNG, Evry, France), he led the Epigenetics groups from 2006-2012, before becoming Director of Laboratory for Epigenetics and Environment at the Centre National de Recherche en Génomique Humaine (CNRGH). The laboratory is involved in the development and application of technologies to analyze DNA methylation and other epigenetic modifications quantitatively at high resolution at target loci and genome-wide using state-of-the-art sequencing technologies as well as the development of bioinformatic tools for the processing of such data. The laboratory has focused the analysis of epigenetic changes in neurodegenerative and immune-related Jörg Tost (H-index=52) is author or co-author of more than 220 publications and senior editor of the journal “Epigenomics”.

Sebastiaan Trietsch



Dr. Bas Trietsch, is the CTO and co-founder of MIMETAS. He is co-inventor of the OrganoPlate®, optimized it towards a mass manufacturable product and enabled the establishment of MIMETAS’ production facility. He developed the initial tissue models on the OrganoPlate and continues to support assay development in the OrganoPlate. As CTO he currently drives product development and grows Mimetas' tissue production, HTS based drug discovery and data science capabilities. Bas holds a Ph.D. in biopharmaceutical sciences from Leiden University and co-authored over 50 peer-reviewed publications and patents.

Asako Tsubouchi

Project manager, Application Research Group


Asako is the Head of Drug Discovery at ThinkCyte and is responsible for leading the development of genome-wide and drug screening platform. Prior to ThinkCyte, she was a project assistant professor at the University of Tokyo, where she was a member of the University-Social Joint Division and collaborated with Nikon Corporation in the development of image-based screening using confocal microscopy. She was also a research associate at Duke University Medical Center, where she specialized in anatomical and functional analysis of somatosensory neurons. Asako holds a Ph.D. in Bioscience from Kyoto University.

Antonia Turberville

Senior Scientist


Completed a PhD in chemical biology at University of Sheffield,UK with an emphasis on kinetic characterisation of heme biosynthetic enzymes in 2019. Before joining AstraZeneca in 2019 as a member or Protein Science followed by High Throughput Screening (HTS). Within High Throughput Screening, I have an interest in high throughput mechanism of action (MoA) studies which can be used to annotate biochemical screening outputs. 

Louis Turcotte

CEO - Co-Founder


Louis is CEO and Co-founder of Saguaro Technologies. He has built extensive experience over the the years in high-tech business management, business development and product development. Before starting Saguaro, Louis was Vice-President - Global Strategy - for a multinational high-tech company that he helped grow from 200 to 1000 employees in 5 years. Having grown through this experience, Louis decided to start Saguaro with his co-founder. Their purpose is to build a company that will become the most powerful leverage in accelerating life science discoveries and improving human health. 

Selim Unlu



M. Selim Ünlü received his Ph.D. (1992) degree from the University of Illinois at Urbana-Champaign, in electrical engineering. Since 1992, he has been a professor at Boston University. He is currently a Distinguished Professor of Engineering appointed in electrical and computer engineering, biomedical engineering, physics, materials science and engineering, and graduate medical sciences. His research interests are in the areas of nanophotonics and biophotonics focusing on the development of biological detection and imaging techniques, particularly in high-throughput digital biosensors based on detection of individual biological nanoparticles, viruses, and single molecule counting.

Dr. Ünlü has authored and co-authored >200 journal articles and has over 12,500 citations (h-index of 59); edited one book; and holds 20 US/international patents. In 2021, he was selected as Boston University Innovator of the Year. Dr. Ünlü  is a Fellow of IEEE, Optica, and AIMBE. He was awarded the Science Award (2008) by the Turkish Scientific Foundation.

Claudia Utcke

Marketing Manager - North America


Frederic Vaillancourt

Senior Vice-President

Remix Therapeutics Inc.

Fred oversees the biomolecular sciences, screening and lead discovery effort at Remix Therapeutics. He has more than 18 years of experience in a range of roles in drug discovery and held various leadership roles at H3 Biomedicine and Boehringer Ingelheim. Now, Fred is motivated to push the current boundaries of drug discovery with the Remix team. He received his PhD in biochemistry and molecular biology from the University of British Columbia and completed his postdoctoral training as a Merck-sponsored Helen Hay Whitney Foundation fellow at Harvard Medical School.

Amit Vaish

Senior Scientist


"PhD in Bioengineering from Pennsylvania State University

Senior Scientist, Lead Discovery and Characterization, Amgen 2018-present
 Supporting discovery projects including targeted proteolysis for biophysical characterization to identify lead therapeutic candidates
 Representing discovery attribute sciences in various project team meetings
 Evaluating novel technologies to fulfill business needs
Scientist, Discovery Attribute Sciences, Amgen 2015-2018
 Supported discovery projects for binding analysis using multiple techniques (i.e., SPR, DLS and DSF) to understand biology, to validate target, and to identify lead therapeutic candidates (both small and large molecules)
 Developed membrane-protein-focused technologies ranging from novel reconstitution/solubilization strategies to advancing direct-binding assay
 Played a key role in the collaboration with Prof. Richard Murray (California Institute of Technology) in securing the funding from Amgen Chem-Bio-Engineering Award, and co-mentored the graduate student
 Evaluated and implemented novel technologies to fulfill business needs
Research Associate, Department of Chemical and Biomolecular Engineering, 2013-2015
University of Delaware, and National Institute of Standards and Technology
 Determined membrane protein structural changes in the presence of additives using scattering techniques (i.e., DLS, SANS, and SAXS)
 Investigated role of various surfactants in stabilizing and crystallizing membrane proteins using multiple biophysical techniques (i.e., CD, NMR, ITC, and fluorescence spectroscopy)
 Developed chromatography-based methods (i.e., affinity, ion exchange, and size exclusion chromatography) to purify detergent-solubilized recombinant membrane proteins
 Calculated monoclonal antibody (mAb) interactions based on atomistic models to understanding the solution behavior of concentrated mAbs
Postdoctoral Researcher, National Institute of Standards and Technology 2011-2013
 Developed a surface plasmon resonance (SPR)-based assay to investigate the stability and activity of membrane proteins under different solution conditions (i.e., pH, temperature)
 Designed a membrane-protein biomimetic platform for functional characterization of membrane protein (i.e., ion channels) using electrochemical impedance spectroscopy"

Dave Vance

Automation Engineer

Boston University DAMP Lab

Dave Vance is an automation engineer at the DAMP Lab of Boston University. He has contributed to the campus-wide COVID-19 surveillance testing done in the Clinical Testing Lab as well as ongoing work at the DAMP Lab core facility. His expertise is in laboratory automation, specifically Hamilton hardware and Venus software and in planning and design of automated protcols. 

James Vandegrift

Senior Research Associate


James Vandegrift is senior research associate in Analytical Development at Takeda in Lexington, MA. His primary focuses are glycan characterization and automation of test methods. He received his BS in chemistry from Ursinus College and has previously worked in DNA synthesis and analytical chemistry. James lives in Boston and enjoys hiking in his free time.

Arne Vandenbroucke

Director, Automation and Systems Engineering


Arne is the Director of Automation, Process and Systems Engineering at Synthego.  Synthego is a genome engineering company with a mission to make CRISPR cell engineering readily available to any scientist or clinicians involved in direct patient care.  Arne has over 2 decades of experience developing and validating scientific instrumentation. He previously worked as product manager at a life science SaaS company, prior to that he was a software engineer at a diagnostics company, and previously a systems engineer at a liquid handling instrumentation company. Arne is passionate about the industrialization of Biology, addressed by multi-disciplinary teams. He holds a PhD in Experimental Physics from Ghent University, Belgium. During his PostDoc at Stanford University, CA, he focussed on Molecular Imaging Instrumentation.

Meghav Verma

Product Manager


Meghav Verma is currently working for National Center for Advancing Translational Sciences(NCATS/NIH) as a Product Manager, Robotics & Automation. His job is to create the vision and develop a state-of-the-art robotics and automation lab for the various scientific groups at NCATS and manage the ASPIRE program. Meghav works with the engineering team to develop various fixed and mobile robotic systems to automate the labs and create a digital eco-system of lab insturmentation using IoT to help the institute perform faster and more efficient research towards drug discovery and therapeutics development for rare diseases.

Dieter Wagner

Product Manager, Cytomat Series

Thermo Fisher Scientific

Dieter Wagner received his degree in Automation from the THM Friedberg and worked in sales and product management roles in several different industries including vacuum technology, optical disc, semiconductor and organic materials. During this time Dieter developed a passion for biotechnology and this led him to Thermo Fisher Scientific, where he is currently Product Manager for the Cytomat product line.

Erica Waller

Product Manager

Azenta Life Sciences

"Erica graduated from MIT with a BS in Mechanical Engineering in 2017 and began her career as a Rotational Engineer at Brooks Automation, working in various roles throughout the company before landing permanently in the Life Sciences division as a Systems Engineer. She transferred to product management with responsibility for automated cryogenic storage in 2021, looking after the products she used to do the engineering work for."

Ramona Walls

Executive Director of Data Science

Critical Path Institute

"Ramona L. Walls, Ph.D. is Executive Director of Data Science at the Critical Path Institute (C-Path). She oversees multiple efforts including the development of C-Path’s Data and Analytics Platform, expansion and modernization of C-Path’s data integration pipeline to encompass new data types, and development of a rare disease knowledge graph. Walls joined C-Path in December 2020 as a Data Scientist in Ontologies, Standards, and Metadata. In 2021 she was promoted to Associate Director of Data Science. Walls retains an appointment in the Bio5 Institute of the University of Arizona, where she has been Principal Investigator on multiple grants from the National Science Foundation and other funders. She has published over 50 peer-reviewed papers in fields as diverse as rare diseases, environmental health, evolution, biodiversity, sustainability, and space situational awareness. Walls received a bachelor’s degree in Environmental Resource Management and Horticulture at Penn State and a Ph.D. in Ecology and Evolution from Stony Brook University and did a post-doc at the New York Botanical Garden. Google scholar profile:"

David Walsh

Assistant Group Leader

MIT-Lincoln Laboratory

"My name is David Walsh, Ph.D. and I am an Assistant Group Leader at MIT-Lincoln Laboratory.  I manage a team of biologists and engineers focused on developing and transitioning innovative biotechnologies to government, academia, and industry partners.  The enabling capabilities of additive manufacturing, rapid prototyping, and integrated sensors have led to the development of high-throughput platforms for interrogating various human physiologies such as: the gut microbiome, the blood-brain-barrier, and liver.  My passion is to deliver the capabilities to improve accuracy, speed, and cost of drug discovery by improving throughput, scalability, and user-friendliness of advanced in vitro models (e.g. organ-on-chip)."

Jenny Wang

High-Throughput Screening facility manager, Network Biology Collaborative Centre (NBCC), Lunenfeld-Tanenbaum Research Institute (LTRI)

Mount Siani Hospital

Jenny Wang has a master’s degree in Pharmacology and Physiology from McMaster University. She has over 20 years of experience with assay development and implementation in automation using different software. She has managed over 100 screens using Momentum, such as ELISA, numerous cell assays and LUMIER, against chemical libraries and siRNA libraries.

Jill Waters

Application Scientist

DNA Script

Jill is an accomplished bench scientist specializing in NGS and spatial transcriptomics. She started her NGS career in single cell genomics when only a handful of labs in the world had knowledge in this field. Jill comes from a background heavy in early R&D bringing cutting edge technology to the forefront. Her work has spanned across academia at MD Anderson through larger companies such as Ilumina, but really found her nitch in the smaller start up culture. She has taken this creativity cultivated from this background, and applied it to the art of supporting customers in the Field.

Jeramie Watrous

Co-Founder and Head of Analytical R&D

Sapient Bioanalytics

"Dr. Watrous is an analytical chemist and engineer with more than a decade of experience using mass spectrometry for small metabolite measures and associated informatics, both in academia and industry environments. Prior to co-founding Sapient, he was a postdoctoral researcher and subsequently an Assistant Professor of Medicine at Jain Laboratory at the University of California San Diego (UCSD). During this time, he was responsible for developing fully automated, high throughput mass spectrometry-based workflows for global small molecule analysis in biological fluids. Dr. Watrous was also previously a scientist at Watson Pharmaceuticals, where he developed cGMP analytical testing methods for emerging generic drugs. At Sapient, Dr. Watrous is responsible for the generation, optimization, and standardization of Sapient’s rLC-MS systems and other innovative instrumentation and lab automation infrastructure.

Dr. Watrous earned his undergraduate degree in Bioanalytical Chemistry from California State University-San Bernadino and received his MS and PhD in Bioanalytical Chemistry from UCSD."

Justine Watterson

Gregory Way

Assistant Professor

University of Colorado Anschutz

I lead a biomedical data science lab with a mission to reduce human suffering. We develop software and machine learning methods and approaches using genomics and microscopy data to study disease, improve clinical decision making, and perform innovative drug discovery. I received my PhD at The University of Pennsylvania in Genomics and I performed a postdoc at The Broad Institute of Harvard and MIT in image data science for drug discovery.

Valeria Weld

DNA Script

Andrea Weston

Senior Director in Discovery Sciences


"Andrea is a Senior Director within the Discovery Sciences Group at Pfizer, where she oversees four teams, Functional Genomics, Cell Model Generation, Protein Homeostasis, and Protein Sciences.   She joined Pfizer in 2016, and prior to that she spent 10 years in the Lead Discovery Group at Bristol-Myers Squibb.  In both roles, Andrea has been involved in driving the evolution of cell models and assay screening methods to enable improved physiological relevance.  This includes the development and use of iPSCs and primary cells for target ID and lead generation.  Andrea’s teams have leveraged phenotypic screening for close to 15 years, with several lessons learned along the way. 

Andrea holds a PhD in Physiology and Molecular Biology from the University of Western Ontario."

Riley Whalen

Research Assistant

Oregon Health & Science University

Riley Whalen received a BS in biology from the University of Washington in 2020 and works as a research assistant in a cancer research lab at Oregon Health and Science University in Portland, OR. Currently, she studies a novel population of circulating cancer cells that possess both cancer and immune cell characteristics, known as hybrid cells, that have been implicated in the metastatic cascade. Riley is also interested in novel cell populations and how their unique features affect living systems and has accepted an offer to attend a biomedical sciences PhD program at OHSU in the fall. 

Ceri Wiggins



Ceri Wiggins (PhD) is a Director in the Functional Genomics department at AstraZeneca, leading the Phenotypic Screening group. Her team is responsible for identifying novel targets to support AstraZeneca’s clinical pipeline, by coupling perturbation technologies such as CRISPR with complex cell models to screen at scale. Prior to AZ, Ceri spent 9 years at Horizon Discovery where she lead their R&D team in the development of Horizon’s CRISPR screening platform and internal target discovery initiative. She also led the scientific development and commercialisation of Horizon’s novel base editing platform Pinpoint™.  

John Wikswo

University Distinguished Professor

Vanderbilt University

John P. Wikswo is the University Distinguished Professor of Biomedical Engineering, Molecular Physiology and Biophysics, and Physics and A. B. Learned Professor of Living State Physics at Vanderbilt University, and founding Director of the Vanderbilt Institute for Integrative Biosystems Research and Education (VIIBRE). He received his Ph.D. in physics from Stanford University. His group’s current work focuses on the development of intelligent well plates that serve as perfusion controllers, microclinical analyzers, and microformulators, and the refinement and use of tissue-chip models of the blood-brain barrier, blood-CSF barrier, airway, and engineered cardiac tissue constructs. He is merging multichannel microfluidic pumps and valves, sensors, mass spectrometry, computational systems-biology models, and artificial intelligence/machine learning software to create robot scientists operating as self-driving biological laboratories for microbial and mammalian cells. Dr. Wikswo has published more than 230 peer-reviewed papers, is a fellow of seven professional societies, and holds 44 patents.

Guy Williams

Senior Research Scientist


I graduated from the University of Bath in 2020 with an Integrated Masters in Pharmacology. Now based within AstraZeneca's Global High Throughput Screening Centre, I have experience in a variety of biochemical- and cell-based assays to identify chemical equity for drug discovery across a range of therapeutic areas. I am interested in high-content imaging approaches, such as Cell Painting, to generate unbiased morphological profiles of chemical or genetic perturbations. 

Jennifer Williams

Sarah Williams

Associate Research Leader, Small Molecule Drug Discovery, CRL

Charles River

"Sarah Williams is a Associate Research Leader at Charles River Laboratories working at Chesterford Research Park, Cambridge. Sarah is passionate about electrophysiology and in vitro assay development, with 12 years ion channel experience. 

Sarah’s interest in ion channels started in 2009 during a summer placement, following this she completed her PhD at the University of Southampton. After her PhD, Sarah did postdoctoral research at Brandeis University. Sarah moved back to the UK in 2016 to work for a Cambridge based contract research organization (CRO). In 2018 she moved to Charles River, where she has worked with both manual and automated patch clamp platforms. Sarah has worked on a range of voltage and ligand gated ion channel targets at Charles River, successfully delivering profiling projects and leading HTS projects from assay development into potency phases."

Scott Wolkenberg

Scientific Director

Janssen Pharmaceutical Companies of Johnson & Johnson

Scott Wolkenberg is Scientific Director in Janssen Global Discovery Chemistry and serves as Global Head of Parallel Medicinal Chemistry.  Scott’s focus is driving acceleration in all discovery pipeline stages through novel capabilities, to deliver high quality clinical candidates faster.  This includes high throughput experimentation, novel reactions, prediction, and lab automation.  Scott is a member of the Journal of Medicinal Chemistry Editorial Advisory Board, is past Chair of the Gordon Research Conference on High Throughput Chemistry and Chemical Biology, is a past member of the National Medicinal Chemistry Symposium SAB, and is an ACS Division of Organic Chemistry Mid-Career Investigator awardee.  He has co-authored more than 50 publications and numerous patents.  Prior to joining Janssen, Scott held positions in Medicinal Chemistry, Technology-Enabled Synthesis, and Chemical Biology at Merck & Co., Inc.  He received his B.A. from Cornell University and completed his Ph.D. with Dale L. Boger at the Scripps Research Institute.

Antony Wood

Senior Director, Product Design and Strategy

Cell Signaling Technology, Inc.

Antony completed his PhD at the University of Guelph, Ontario, Canada, studying the role and regulation of cell death processes in vertebrate ovarian development. He then pursued postdoctoral studies at the University of Michigan, examining the role of insulin-like growth factor signaling in vertebrate embryonic development. He subsequently joined a research group at Massachusetts General Hospital and Harvard Medical School, where he employed genetic approaches to study embryonic and postnatal germline development and regeneration. He joined Cell Signaling Technology, Inc. in 2011, where he now serves as the Senior Director of Product Design and Strategy. 

Paul Wylie

Director of Multiplex Applications


Paul Wylie, PhD has a long and robust commercial history of developing and commercializing multiplexed assay solutions primarily to Pharma and Biotech companies. He has a lot of extensive experience, working closely with research scientists to understand their problems and requirements to effectively help to provide robust multiplexed assay solutions. 

Shuo Xiao

Assistant Professor

Rutgers University

Dr. Xiao is an Assistant Professor in the Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy at Rutgers University. He is also a principal investigator at the Rutgers Environmental and Occupational Health Sciences Institute (EOHSI). Dr. Xiao and his research team focus on female reproductive biology, disease, and toxicology, including (1) the adverse effects of classic and emerging environmental contaminants on women’s reproductive health, in particular of women’s ovaries and associated ovarian functions, menstrual cycle, and fertility; (2) engineering an ovary-on-a-chip and a female reproductive-tract-on-a-chip using microfluidic and organ-on-a-chip technologies; (3) developing novel women’s birth control pills; and (4) investigating the effects of environmental exposure on women’s reproductive diseases such as polycystic ovarian syndrome (PCOS). Dr. Xiao’s research is supported by EOHSI at Rutgers, NIH, Bill & Melinda Gates Foundation, Health and Environmental Sciences Institute (HESI), and New Jersey Department of Environmental Protection (NJDEP).

Han Xu

VP, Therapeutic and Translational Science

A2 Biotherapeutics

"2018-present: VP, Therapeutic and Translational Science at A2 Biotherapeutics, leading immuno-oncology projects from target ID to IND filing.

1997-2018: Amgen; varies scientist and group leader positions in Discovery Research; experienced in antibody and small molecule drug discovery as well as technology development
Ph.D. in Biochemistry and Cell Biology from Rice University"

Ming Yao

Postdoctoral Fellow

University of Washington

Dr. Yao is a postdoctoral fellow working with Dr. Nancy Allbritton at University of Washington. They have developed a picoliter thin layer chromatography (PicoTLC) technology that can be used to assay lipid signaling pathways in ultra-small samples, and even in single cells. If you are interested, please contact us at:

Viktoria Zieger, n/a

PhD student

Laboratory for MEMS Applications, IMTEK - University of Freiburg

Viktoria Zieger started her bachelor's degree in physics in Heidelberg in 2015 and completed it with her thesis about simulations of the accuracy of dose delivery for particle radiation in cancer therapy. In 2018 she continued her studies with a master's degree in Muenster with a focus on nanophysics and biophysics. For her thesis, she constructed a novel optical setup that combined a light sheet microscope with optical tweezers and used it to carry out microrheological measurements while simultaneously acquiring 3D microscopic images. In March 2021 she started her PhD in the Laboratory for MEMS Applications at the University of Freiburg. As part of her project, she is developing a platform for automated 3D microtumor analysis for personalized therapy. In this context, she designs and tests different methods for both automated microtumor production and automated single microtumor deposition to enable and facilitate high-throughput drug screening.


Does AI Accelerate the Discovery of Therapeutics and Biomarkers?
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Open to view video.  |   Closed captions available An information revolution in healthcare and life sciences has led to an explosion in health-related data, including omics, foundational science, diagnostic, treatment, outcome, and other related clinical data. Truly unlocking the value of this information for accelerated therapeutics and biomarker discovery, however, requires leveraging key technologies that together can provide actionable insights to researchers and clinicians. This talk will focus on how core technologies, such as AI, hybrid cloud, and high-performance computing, together with more generalizable foundation technologies, including knowledge extraction and integration, AI-enriched simulation, generative modeling, and automation, as well as other accelerator technologies, have and may continue to come together in the future to break through long-standing bottlenecks in discovery workflows to provide value to the end user. Specific example implementations of these technologies will be provided within the drug discovery and development pipeline, demonstrating how this fusion can help optimize the modeling of new molecular entities, enhance clinical trial design, aid in biomarker discovery, and improve automation through AI-driven chemical reaction prediction, retrosynthesis planning, and generation of experimental procedures.
Spoons and Thumbs: Funny, spooky, poignant, and completely true science stories
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Open to view video.  |   Closed captions available Join national bestselling author Sam Kean as he spins a selection of funny, spooky, poignant, and completely true science stories from several of his award-winning books. Topics covered include the joys of the periodic, the perils and promise of the human genome, and the enduring mysteries of neuroscience, as well as Sam's path as a science writer. Book sales and signing to follow.
Assay Development and Screening
Industrialization of drug discovery: How automation and standardization are accelerating high throughput operations
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Open to view video.  |   Closed captions available Recursion is a clinical-stage biotechnology company industrializing drug discovery by decoding biology. The company harnesses cutting-edge technologies like robotic automation and machine learning algorithms to conduct up to 2.2 million wet-lab experiments every week, which continue to expand one of the world’s largest proprietary biological and chemical datasets. However, the reality of the day-to-day execution of live cell assays in a high throughput environment to ensure scalable, reliable, and relatable data is challenging. By applying principles from GXP and out-of-the-box engineering solutions, Recursion was able to increase success rates across its high throughput operations from ~60% to >85% in 2022. This presentation will delve into the best practices needed to achieve this outcome, from engaging employees in a production work environment to efficiently using a Quality Management System in a discovery environment.
Morphology and gene expression profiling provide complementary information for mapping cell state
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Open to view video.  |   Closed captions available In a phenotypic drug screen, a scientist treats cells with various perturbations and measures an unbiased phenotype. Currently, the two most common and cost-effective assays for phenotypic drug screening are Cell Painting and L1000. Cell Painting measures cell morphology, while L1000 measures gene expression. We collected these two assays in identical platemap designs for over 1,300 drug perturbations across six doses in multiple replicates. All data and processing pipelines are publicly available. We determined that the two assays capture some shared and some complementary information in mapping cell state. In the Cell Painting assay, machine learning predicted cell health phenotypes, like DNA damage and cell cycle arrest, induced by these perturbations. We also developed an open-source software tool called pycytominer to perform reproducible bioinformatics pipelines for Cell Painting data.
Immuno-assay platforms at AstraZeneca for Oncology Cell Therapy functional genomics
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Open to view video.  |   Closed captions available "The modification of T cells to express a chimaeric antigen receptor (a.k.a. CAR-T cells) has shown remarkable responses in patients with certain types of blood cancers. Whilst this success has galvanised efforts around Cell Therapy in Oncology, the next great challenge for the field is to achieve efficacy in solid tumour indications. The targeting of solid tumours will involve creating cellular therapies that can cope with the myriad immunosuppressive conditions that are found in the tumour microenvironment (TME), and as such the challenge for target identification and validation is to recreate model systems that reflect the TME and maintain suitability for screening. Using techniques such as pooled and arrayed CRISPR screening coupled to relevant immunoassays, we have been working to discover new strategies which we can use to modify CAR-T cells to overcome features of the immunosuppressive microenvironment. This has involved the development and use of robust miniaturised 2D co-cultures of target cells and CAR-T cells, 3D models such as spheroids and organoids and also external collaborations to investigate the role of the extracellular matrix and its effect upon CAR-T cell behaviour. These models allow us to capture the increased complexity of the solid tumour TME whilst also enabling scalable screening cascades and measurement of multiple endpoints. Taken together, the continued development of all of these discovery platforms will help to realise our goal of effectively targeting solid tumours using cellular therapies."
High-throughput method to analyze the cytotoxicity of CAR T Cells in a 3D tumor spheroid model using image cytometry
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Open to view video.  |   Closed captions available Chimeric antigen receptor (CAR)-T cell therapy is an antigen-dependent cellular therapy that has gained considerable traction in the field of cancer immunotherapy. CAR-T cell therapy involves specifically engineering T cells to attack tumor cells by binding a tumor antigen and inducing T cell activation resulting in intracellular signaling and cytokine release. Currently, there are six FDA-approved CAR-T cell therapies, which all target the CD19 or BCMA antigens for hematologic B cell malignancies. In the recent years, a strong focus has been placed on CAR T cell therapy discovery for solid tumors, which may better recapitulate physiological conditions, thereby potentially improving the selection of CAR construct candidates. Immune cell trafficking and immunosuppressive factors within the tumor microenvironment increase the relative difficulty in developing a robust CAR-T cell therapy against solid tumors. Therefore, it is critical to develop novel methodologies for high-throughput phenotypic and functional assays using 3D tumor spheroid models to better assess CAR-T cell therapies against solid tumors. Recently, plate-based image cytometry has emerged as a method to investigate and characterize CAR T cell functions in a high-throughput manner. Image cytometry has demonstrated capabilities in analyzing transduction efficiency, cell proliferation, and cytotoxicity for CAR T cell therapy. With the development of 3D spheroid models, image cytometry may provide the necessary tools and applications for CAR T cell therapy discovery geared towards solid tumors. In this work, we discuss the use of CAR-T cells targeted towards PSMA, an antigen that is found on prostate cancer tumor cells, the second most common cause of cancer deaths among men worldwide. Herein, we demonstrate the use of high-throughput plate-based image cytometry to characterize PSMA CAR-T cell-mediated cytotoxic potency against 3D prostate tumor spheroids and simultaneously monitor location of the T cells in vitro. We were able to kinetically evaluate the efficacy and therapeutic value of PSMA CAR-T cells by analyzing the cytotoxicity against prostate tumor spheroids. Furthermore, the T cells are fluorescently labeled with a tracer dye to visually locate the cells on the tumor spheroids. The proposed image cytometry method can overcome limitations placed on traditional methodologies to effectively assess cell-mediated 3D tumor spheroid cytotoxicity and efficiently generate time- and dose-dependent results.
A robotized 1500+ compound screen in a perfused 3D microfluidic angiogenesis assay
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Open to view video.  |   Closed captions available Drug discovery requires highly physiologically relevant in vitro models that can be utilized in a screening setting. We report an organ-on-a-chip platform that has been designed for screening compatibility, combining 3D perfused tubules with automated liquid handling and imaging. The high-throughput organ-on-a-chip setup was utilized to assess the inhibitory effect of over 1500 protein kinase inhibitors in an angiogenesis assay. We cultured more than 4000 micro vessels under continuous perfusion and exposed them to a cocktail of pro-angiogenic factors in the presence of the different protein kinase inhibitors. Automated imaging and morphometric analysis was used to determine efficacy in the form of inhibition of sprout formation. In the same images, changes in morphology and integrity of the main micro-vessel where quantified as measure of toxicity. The screen yielded 53 hits that showed both high efficacy and low toxicity, of which 44 were previously unassociated with angiogenic pathways. This studies shows the utilization of organ-on-chip technology at an unprecedented scale, unlocking true implementation of highly relevant model for early stage compound and target discovery.
Genome-Wide Optical Pooled Screens Identify Regulators of Host-Pathogen Interactions
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Open to view video.  |   Closed captions available Currently, genetic screens are critical for the systematic identification of genes underlying cellular phenotypes. Pooling genetic perturbations greatly increases screening throughput, but is not readily applied to high-content imaging of complex and dynamic cellular phenotypes. To bridge this gap, we have developed optical pooled screening, linking pooled genetic perturbation screening with associated visual phenotypic outcomes in mammalian cells. Using targeted in situ sequencing, libraries of genetic perturbations are demultiplexed following image-based phenotyping. Applying improved sample preparation, in situ sequencing by synthesis, and microscopy protocols, we have established this approach at a genome-wide scale.In this work, we leverage optical pooled screening to perform a genome-wide CRISPR knockout screen of cellular responses to Sendai virus infection. This single-cell resolution, multiparameter screen assayed seven markers of interest (DNA, IRF3, RIG-I, MDA5, peroxisomes, mitochondria, and Sendai virus), and identified sgRNA sequences in >10 million cells. Following our genome-wide screen, we identified 51 confirmed regulators of IRF3 translocation through two independent secondary screens. Among the hits, we found that ATP13A1, an ER-localized P5A-type ATPase, is essential for viral sensing and is required for targeting of MAVS to mitochondrial membranes necessary for effective signaling through RIG-I.We have also applied optical pooled screening at the genome-wide scale to assay responses to Ebola virus, a BSL4 RNA virus, measuring both host and viral proteins as well as integrating RNA FISH into our optical pooled screening pipeline for the first time and measuring responses in tens of millions of cells. Finally, we have assessed genome-wide responses to exogenous DNA by profiling STING trafficking in tens of millions of cells. By applying machine learning and deep learning techniques, we have extracted rich information from these three high-content, genome-wide single-cell optical pooled screening measurements and have revealed critical regulators of responses to exogenous RNA and DNA stimuli.
Functional genomics is (finally) fulfilling its promise
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Open to view video.  |   Closed captions available Ten years ago, Science published an editorial entitled Use and Abuse of RNAi to Study Mammalian Gene Function, in which the author lamented that "the honeymoon is now over, and although some new discoveries have been made, the yield has fallen far short of expectations." Functional genomics was at a nadir. Fortunately, three weeks later saw the publication of Doudna & Charpentier's seminal description of CRISPR technology. Here, we will discuss how this Swiss army knife of genomic tools has reinvigorated the field, with its robust activity, high specificity, and wide range of derivations and applications.
Next-generation CRISPR screening platforms for insights into human disease biology
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Open to view video.  |   Closed captions available The ability to conduct genome-wide screens using CRISPR-based tools has enabled significant advances in our understanding of biological pathways, developmental processes, and disease-relevant molecular mechanisms. However, the cell models, applications, and scope of readouts available in a screening-ready format are currently limited in terms of scale and biological relevance. We describe systematic strategies for generating disease-relevant primary and induced pluripotent stem cell (iPSC)-derived models at the scale and efficiency required for use in genome-wide CRISPR screens, which, combined with advances in functional genomics tools and assays, allow for multiparametric phenotypic readouts to gain deep insights into mechanistic disease-relevant pathway biology. To address the current limitations around human cell models suitable for large-scale functional genomics screening applications, we have developed systematic strategies for generating disease-relevant primary and iPSC-derived models with long-term maintenance of functional CRISPRi and CRISPRa machinery. Using these foundational tools, we developed profiling approaches to identify and test candidate transcription factors for lineage-specific deterministic differentiation protocols. In parallel, we developed strategies to identify factors whose levels can be modulated to enhance transduction efficiency of iPSC-derived cells. We demonstrate applications of these sophisticated screening-ready models in multiple next-generation platforms, including co-culture screens to model cellular interactions and organoid-based screens to replicate human tissue biology. To complement advances in model development, we improved guide library quality to minimize skew ratio, allowing for pooled screens with equivalent hit calling and readout depth at a 10-fold lower cell coverage than the current standard in the field. To advance our ability to probe complex molecular pathways, we have optimized methods to perturb multiple genes simultaneously and to perform epigenetic editing for long-term stable gene silencing or activation. We also developed dynamic array-based microscopy screening readouts along with scalable and cost-effective single cell approaches for deep phenotyping.Combining next-generation models, high-quality libraries, and single cell readouts allows for new approaches to accelerate our understanding of disease biology. In one example, we implement a human iPSC-based hematopoietic progenitor cell model to screen for regulators of gene editing outcomes in disease-related stem cell populations. We also use a chronic kidney disease model to study how disease-relevant SNPs in non-coding regions affect gene expression to drive cellular phenotypes, which allows us to link GWAS-identified disease loci to therapeutic targets and probe the molecular pathways involved. Beyond these examples, we apply screening approaches to outstanding questions in immune disease, oncology, and neurodegeneration via a combination of pooled screens, array-based imaging screens, and screens with single cell readouts. With these technological development and disease applications, we demonstrate how large-scale screening platforms can be further improved to broadly provide unprecedented insights into genes involved in human disease.
Expanding the Scope of DNA-Encoded Libraries
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Open to view video.  |   Closed captions available The use of DNA-encoded library (DEL) as a technology in hit identification has enabled the rapid screening of a target protein of interest against millions of molecules in one well. The power of this technology is derived in part from the small molecules in the library: each molecule is uniquely tagged with a DNA sequence via combinatorial “split-and-pool” synthesis. The uniquely labeled molecules can be tested at once in an attrition-based screening process. After the non-binding molecules have been removed, the remaining molecules are sequenced and with data analysis, the structure of the binding molecules can be deconvoluted. While DEL has provided a method for rapid, relatively inexpensive testing of small molecules, there are still several key limitations surrounding this technology. As an affinity binding screen, the hits which result from a DEL screen may be binding but have no functional purpose, leading to a significant attrition of molecules. Additionally, there are several protein classes which are not compatible with the DEL screen process such as DNA-binding proteins. Further, the vast number of molecules which are input into the DEL selection can result in a low percentage of consistency between replicates. At Anagenex, we are successfully developing methods via both Machine Learning and in-lab experimental design. Herein, we will discuss how our new methods have enabled us to leverage both active and inactive molecules towards the drug discovery pipeline as well as establish binding compounds for a wide range of protein classes including DNA-binding proteins.
High-throughput phenotypic screening by machine vision-based cytometry
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Open to view video.  |   Closed captions available "Current high-throughput CRISPR screening approaches are heavily reliant on plate-based imaging using conventional high-resolution microscopy, which is multi-instrument intensive and prohibits scale-up to screening large genomic libraries. Here we present a novel drug screening approach using high-throughput machine vision-based cell sorting (Ghost Cytometry (GC)) to study the effects of drugs and genetic perturbations on cellular morphological phenotypes by flow cytometry. GC combines high-speed morphological profiling in flow with artificial intelligence (AI) to identify and sort cells exhibiting phenotypes of interest. We show the ability of GC to identify complex immune cell phenotypes used in small and large molecule drug screening including B-cell activation, T-cell health (glycolysis level, viability, exhaustion level) and macrophage polarization. For functional genomics screening, we demonstrate application of GC in a pooled CRISPR screening workflow to identify genes regulating the nuclear translocation of nuclear factor kappa B (NF-κB) in a human leukemia monocytic cell line (THP-1) using fluorescent mode. We screened a pathway-specific library of 7,290 sgRNAs targeting 729 kinase genes in a pooled format in one day. Using the embedded AI in a GC-powered device, LPS (a TLR4 agonist) stimulated Cas9-expressing THP-1 cells transduced with the kinase CRISPR library were sorted based on subcellular morphological changes and the approach identified enrichment of sgRNAs targeting known genes downstream of TLR4 signaling including MAP3K7, IRAK4, IKBKB, and IKBKG. Furthermore, by employing the multi-parametric, label-free mode, we also performed the large-scale screening to identify a gene involved in macrophage polarization. Especially the label-free platform can enrich target phenotypes without invasive staining, preserving untouched cells for downstream assays and unlocking the potential to screen for the cellular phenotypes even when suitable markers are lacking. Here we present GC as a novel method well-suited for next-generation high-content and large-scale pooled CRISPR screening. The approach provides significant advantages over traditional arrayed screens including: (1) scalability to large screening libraries (2) applicability to a diverse repertoire of complex morphological phenotypes in both adherent and suspension cells (3) and compatibility with commercial sequencing platforms to identify target gene perturbations in functional genomics screens."
Putting the dynamics into compound profiling: using fluorescent ligand kinetic assays to shape early stage drug discovery
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Open to view video.  |   Closed captions available Drug action often occurs within a highly dynamic context in vivo. The concentration of the drug in the vicinity of the target continually changes based on its pharmacokinetic properties, it may be in competition for the target protein with rapidly fluctuating levels of receptor messengers or enzyme substrates, and for receptor agonists the therapeutic effect itself may depend on a particular pattern of downstream cellular signalling over time. Under such circumstances, measurement of binding rate constants defining the kinetics of drug-target interaction can be valuable in selecting desired functional properties. The benefits of optimising on and off rates during early stage compound profiling will be briefly reviewed, including duration of action and generation of kinetic selectivity, together with emergence of non-surmountable properties for slowly reversible inhibitor and antagonist effects even in the presence of high concentrations of substrate or stimulating messenger. In practical terms, application of resonance energy transfer technologies, such as TR-FRET, in combination with fluorescent ligands is a powerful approach to generate real time assay formats to assess the kinetics of binding both for isolated recombinant proteins, and receptors in a native membrane or cellular context. Successful screening assay development for such approaches will be discussed with reference to case studies for G protein coupled receptor orthosteric and allosteric ligand binding sites, and recombinant purified enzyme targets. Finally, the extension of TR-FRET kinetic binding methodology to probe ligand behaviour at defined receptor signalling complexes will be explored.
A suite of arrayed CRISPRn assays in primary respiratory cells for the identification and validation of new targets for COPD.
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Open to view video.  |   Closed captions available Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide and although there are several treatments for this disease, they only slow the progression and therefore new therapies for COPD are required. COPD is characterised by inflammation and loss of epithelial cell integrity in the small airways leading to reduced airflow in the lungs. One of the major causes of COPD is cigarette smoke, the DNA damage caused by cigarette smoke and other pollutants induces a type of premature aging of the lung, which is thought to contribute to the onset and progression of the disease. One hallmark of premature aging is the presence of senescent cells. Senescent cells have undergone a process of cell cycle arrest; this is accelerated in many diseases including COPD. The aim of this project was to identify novel regulators of cellular senescence for the identification of new targets for the treatment of COPD. We have designed and executed an arrayed CRISPRn screening cascade in two primary human cell types relevant to COPD: fibroblasts and small airway epithelial cells (SAECs) with multiparametric imaging endpoints to measure cellular senescence. The cascade was initiated by a whole genome CRISPRn screen in primary lung fibroblasts to identify gene knockouts that inhibit DNA damage induced senescence. A prioritised hit list was taken into the secondary assay, developed in SAECs to assess DNA damage induced senescence in this cell type. In these assays, DNA damage was induced by etoposide and several senescence endpoints were measured including nuclear p21 expression, enlarged morphology, cell number, cell cycle and phospho-yH2AX foci as a marker of DNA damage. Together these assays led to the identification of 9 hits that are currently under investigation for further target validation and a new target proposal in the respiratory portfolio for the treatment of COPD.
High Throughput Kinetic Characterisation
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Open to view video.  |   Closed captions available "It has long been appreciated that the majority of new medical entities exhibit non-equilibrium kinetic mechanisms, of which a thorough understanding is key to predicting the translation to cellular and in-vivo efficacy. Despite this awareness, the throughput of the assays required is often low, meaning that mechanistic characterisation is often carried out late in the development process. This presentation highlights some of the recent advances in experimental techniques, lab automation and the scalability of data analysis, which have enabled high throughput kinetic and mechanistic characterisation of numerous hit series immediately post hit identification.
Selective degradation of c9ALS/FTD r(G4C2) repeat expansion by small molecule-ribonuclease recruitment in vivo
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Open to view video.  |   Closed captions available A hexanucleotide repeat expansion in intron 1 of the C9orf72 gene is the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia, or c9ALS/FTD. The RNA transcribed from the expansion, r(G4C2)exp, elicits pathological phenotypes through a variety of key mechanisms including intron retention, aberrant translation producing toxic dipeptide repeat proteins (DPRs), and sequestration of RNA-binding proteins (RBPs) within RNA foci. Herein, we describe a small molecule that selectively and potently degrades r(G4C2)exp via targeted ribonuclease recruitment. The compound displays potent binding uniquely to the r(G4C2)exp hairpin and recruit endogenous nuclease onto the target, provoking removal of the transcript by native RNA quality control mec hanisms. In c9ALS patient-derived spinal neurons, the compound selectively degraded the mutant C9orf72 allele with limited off-targets and reduced quantities of toxic dipeptide repeat DPRs translated from r(G4C2)exp. Two weeks following a single intracerebroventricular (ICV) injection in a mouse model of c9ALS, the described compound was successfully reduced the abundance of both the mutant allele harboring the repeat ex pansion and DPR proteins, demonstrating the first example of small molecule-mediated RNA degradation in a brain.
Direct-to-Biology Accelerates PROTAC Synthesis and the Evaluation of Linker Effects on Permeability and Degradation
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Open to view video.  |   Closed captions available A platform to accelerate optimization of proteolysis targeting chimeras (PROTACs) has been developed using a direct-to-biology (D2B) approach with a focus on linker effects. A large number of linker analogs─with varying length, polarity, and rigidity─were rapidly prepared and characterized in four cell-based assays by streamlining time-consuming steps in synthesis and purification. The expansive dataset informs on linker structure–activity relationships (SAR) for in-cell E3 ligase target engagement, degradation, permeability, and cell toxicity. Unexpected aspects of linker SAR were discovered, consistent with literature reports on “linkerology”, and the method dramatically speeds up empirical optimization. Physicochemical property trends emerged, and the platform has the potential to rapidly expand training sets for more complex prediction models. In-depth validation studies were carried out and confirm the D2B platform is a valuable tool to accelerate PROTAC design–make–test cycles.
The Fast Track to Thermodynamics: Multiplexed Profiling with High Throughput Surface Plasmon Resonance
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Open to view video.  |   Closed captions available Surface Plasmon Resonance is an established and widely used biophysical technology in screening and lead development campaigns for novel drug candidates. The real-time, label-free analysis of interactions offers additional insights into kinetics. Besides the value of a kinetic profile, the thermodynamic profile of potential lead candidate is equally important as it may give hints in steering the subsequent medicinal chemistry efforts to a more successful lead.The thermodynamic profile of lead candidates is commonly determined with Isothermal Titration Calorimetry (ITC). This solution-based system is notoriously known for its low throughput of maximally a few dozen compounds per day and a high protein consumption, especially for weak binders such as lead candidates. Hence, ITC-measurements are often performed at a later stage in lead development with small numbers of molecules, thus, preventing insight into earlier candidates. We investigated the applicability of the multiplexing SPR Pro series for thermodynamic profiling of small molecules against proteins. Three different assay modes for a model case with a set of compounds against a single protein were analyzed first and the assay modes compared with respect to comparability and reproducibility. Subsequently, the thermodynamic profile of a set of eight compounds against three different proteins was determined in a single assay set-up. This information aided in understanding the underlying selectivity and affinity profile of the compound set in an automated approach with a single experiment. Consequently, the thermodynamic profile could be analyzed faster and at a substantially lower sample consumption of only 20-50 ug protein.We herewith present an automated and high-throughput optimized approach for thermodynamic profiling of an interaction by SPR. Thus, the extension of typical parameters from a SPR experiment by a thermodynamic profile allows for a better understanding in lead development at an earlier stage than currently feasible.
Differential screening to discover mutation-mediated neo-protein-protein interactions as cancer-specific targets for precision medicine
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Open to view video.  |   Closed captions available Comprehensive sequencing of patient tumors has revealed driver mutations across tumor types. Oncogenic mutations represent cancer-specific features that offer unprecedented opportunities for mutation-directed therapeutic strategies. To systematically discover such mutation-enabled neo-protein-protein interactions (neoPPI), we developed a quantitative High Throughput differential Screening platform. The comparative binary interaction screening of WT and mutant counterparts with a library of cancer-associated proteins in live cells revealed a landscape of gain-of-protein interactions mediated by driver mutations in both oncogenes and tumor suppressors. Systematic analysis of the established neoPPI network suggests unique oncogenic re-wiring mechanisms driven by distinct mutant alleles and candidate neoPPIs for therapeutic perturbation. Validated neoPPIs implicated in oncogenic pathways have been selected for small molecule modulator discovery with robust HTS assays. For example, the recurrent BRAF V600E lesion led to a neoPPI with KEAP1 and created a BRAFV600E-KEAP1 signaling axis and a collateral vulnerability for a combination therapeutic approach. A TR-FRET-based HTS assay has been developed to identify BRAFV600E-KEAP1 inhibitors. Our work presents a new dimension of the cancer genome to inform variant-directed neoPPI-targeted therapeutic strategies for precision medicine and offers a panel of HTS assays for the discovery of neoPPI inhibitors.
CRISPR dissection of human regulatory T cell identity and function
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Open to view video.  |   Closed captions available Regulatory T cells (Treg) play a critical role in human immune homeostasis by suppressing inflammation and autoimmunity. Treg cells must maintain suppressive functions even in pro-inflammatory microenvironments, and this maintenance is in large part controlled by transcriptional regulation. The transcription factor (TF) FOXP3 is known to be crucial for the establishment and maintenance of Treg cell identity. The complete set of critical transcription factors in human Treg cells and their downstream transcriptional targets remain unknown. Using both pooled as well as arrayed Cas9 ribonucleoprotein (RNP) in vitro screens in primary human Tregs under pro-inflammatory conditions we identified TFs that regulate expression of key Treg and effector T cell markers. We then deeply profiled a subset of these TFs by single-cell RNA sequencing (scRNA-seq) of edited human Treg cells, revealing distinct gene modules that preserve Treg transcriptional identity. These modules highlighted key genes of Treg cell functions regulating cytokine secretion, transcriptional regulation and metabolism in Treg cells. We find that FOXP3 and PRDM1 individually regulate independent gene modules, while FOXO1 and IRF4 co-repress their own. We have also discovered that HIVEP2—which has not been previously implicated in Treg cell functions—participates with SATB1 in co-activating yet another gene module. Comparing these “Treg cell modules” to CD4 effector T cells (Teff) by integrating CRISPR-engineering, ATAC-seq and RNA-seq data we can now identify conserved transcriptional patterns between Treg and Teff cells as well as subset-specific networks regulating for example pro- and anti-inflammatory cytokine production as well as FOXP3 expression. By identifying key genetic programs controlled by individual TFs that shape Treg or Teff cell identity, we gain knowledge that could be used to ultimately engineer improved adoptive cell therapies in the future.
Image-based Morphological Profiling of the Reprogramming of Human Macrophages
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Open to view video.  |   Closed captions available Changes in cellular morphology often reflect underlying changes in complex cellular pathways. Cell painting is an unbiased, morphological profiling assay that multiplexes several fluorescent dyes to reveal cellular components and organelles. Phenotypic features extracted from microscopy images of cells treated with different perturbagens can be used to identify biologically changes among samples without focusing one specific pathway or biochemical mediator. This work leverages morphological profiling to evaluate polarization of primary human monocyte-derived macrophages in response to chemical and genetic perturbations. As a part of the workflow, traditional image analysis techniques are compared with machine learning analysis. This includes deep convolutional neural networks (CNNs) to extract numeric features from single cells, as well as assess image quality and robust cell segmentation. This method gives higher sensitivity detection of biological signals than classical features extraction methods using Columbus. Our recent data show that small molecules as well CRISPR KO can inhibit M1 polarization and shift/keep cells in an M0 state. Phenotypes detected by cell painting analysis were confirmed by cytokine profiles and the changes in the expression of the M1 marker PDL-1. Cell painting combined with multiparametric data analysis enables the creation of a screening platform to identify novel tools, targets and pathways that modulate macrophage polarization.
A Perspective on the Discovery of Enzyme Activators
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Open to view video.  |   Closed captions available A Perspective on the Discovery of Enzyme Activators Antonia Turberville1, Hannah Semple2, Gareth Davies2, Delyan Ivanov1 & Geoffrey A Holdgate2 1Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK2 Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Alderley Park, UK Enzyme activation remains a largely under-represented and poorly exploited area of drug discovery. There are few examples of the successful identification and application of enzyme activators despite the attractiveness of restoring or increasing enzyme activity in certain therapeutic interventions. Enzymes have evolved over millions of years to be optimal for specific biological functions and so identifying small molecule activators to further improve the catalytic rate can be challenging. An opportunity arises when enzymes lose catalytic function through mutation and activation to restore activity to wildtype levels may be attempted. However, the robust identification of small molecule activators targeting mutant enzymes in high-throughput screens is not necessarily straightforward. Here we present the background theory and discuss the challenges of hit identification for enzyme activation compared to inhibition. Finally, we present our perspective on some approaches that may provide utility in overcoming these challenges and improve our chances of identifying useful chemical start points.
Navigate Your Chemistry And Explore The Biology - Case Studies Of CETSA®
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Open to view video.  |   Closed captions available "CETSA® (Cellular Thermal Shift Assay) is a powerful technology for investigating target engagement and the mechanism of action for compounds in the native cellular environment. CETSA can be performed in a targeted fashion, allowing for rapid confirmation of target engagement on a specific protein of interest. When combining CETSA with quantitative LC-MS based proteomics, it not only monitors direct protein-ligand interaction, but also allows for measurement of compound-induced changes in the cellular proteome. We strive to continuously develop CETSA as an applicable, feasible, versatile, and reliable method being relevant in both drug discovery as well as clinical settings in therapeutics and diagnostics. Here, we will show how the different formats of CETSA can be applied in various stages of drug discovery to provide data that is both actionable and biologically relevant."
Cell Morphological Profiling using Cell Painting Enables Phenotypic Assessment of PROteolysis TArgeting Chimeras (PROTACs)
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Open to view video.  |   Closed captions available PROteolysis TArgeting Chimeras (PROTACs) are bifunctional molecules that induce target protein degradation via the ubiquitin-proteasome system for therapeutic benefit. PROTACs have attracted great attention for their potential to address protein targets previously considered intractable or undruggable with conventional small molecule approaches. However, robust methods to assess and profile potential safety risks of novel compounds as early as possible in pre-clinical discovery are lacking. Here we explore the use of Cell Painting, an unbiased, multiplexed high-content imaging assay to identify phenotypic biosignatures of PROTACs. In this study, we have tested 341 PROTACs and 149 non-PROTAC compounds (including small molecule inhibitors, E3 ligase ligands and reference compounds with know mitotoxicity) in the Cell Painting assay. We demonstrate that phenotypic profiles of PROTACs do not necessarily correlate with individual components (i.e. the protein-of-interest ligand and the E3 ligase ligand), indicating that the phenotypic effect of an individual PROTAC can be distinct from the sum of its parts. Morphological profiles were then utilised to train supervised machine learning models to predict mitotoxicity of PROTACs and other molecules. Our data suggests that clustering of PROTACs based on phenotypic similarity and the use of morphological profiles for mitotoxicity prediction can provide insights into mechanism of action and safety assessment of novel molecules.
Evaluating target engagement of a focused lead-like and pan-assay interference compound collection using affinity selection mass spectrometry
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Open to view video.  |   Closed captions available "Studying protein-ligand interactions using mass spectrometry (MS) offers a high-throughput label-free biophysical characterization toolbox. Conventional biophysical assays are either label-based or often labor intensive and require mobilization, limiting analysis of large compound libraries. To tackle this, we have now adopted affinity selection mass spectrometry (ASMS) into our daily high-throughput screening (HTS) operations at Pivot Park Screening Centre (PPSC). With ASMS, compounds that bind to the target are separated from any unbound compound by in-plate size exclusion chromatography (SEC) in 384-well format. The complex is then denatured and the ligands can be identified by MS. We selected thrombin, a well-studied protease to establish ASMS-based screening in our lab and compare its output relative to a functional assay. To this end, we setup a biochemical MALDI-TOF and a biophysical ASMS assay for thrombin and screened the robustness compound collection that is comprised of various classes of compounds with assay interfering properties and non-drug-like mode-of-action such as autofluorescence, aggregation, chelation, chemical reactivity, and redox activity, as well as a focused lead-like subset for which no obvious interferences were expected. In total five compounds were identified as potential binders to thrombin in ASMS assay, of which two were also active in the biochemical MALDI-TOF setup, while in total ten compounds were active in a biochemical MALDI-TOF setup. Eight compounds active in the biochemical setup that were not identified by ASMS likely due to low ionization and being in the detection limit of the MALDI-TOF. Finally, we examined the specificity of the five ASMS actives by comparing their binding to Bovine Gamma Globulin (BGG). Three compounds that were only picked up by ASMS showed binding to both thrombin and BGG, and as such were considered as aspecific binders. The two compounds showing inhibitory activity in the biochemical setup and binding to thrombin in ASMS were confirmed to bind specifically to thrombin by ASMS. During our journey of setting up ASMS for target engagement profiling, we learned that the technique is associated with relatively large standard deviation ( > 15 %) as compared to our general HTS standards ( < 10 %) and having more datapoints to perform statistics is very important for ASMS to separate true hits from the background noise. Furthermore, confirming the specificity of the actives by ASMS allows to discriminate hits from false positives as shown by our model system. In my presentation, I’ll discuss the pros and cons of ASMS as a semi-quantitative label-free method and its application a powerful tool for evaluating target engagement for hit prioritization."
Automation Technologies
Automating Optical Pooled Screening to Enable Genome-scale CRISPR Screening
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Open to view video.  |   Closed captions available Genetic screens can be used to establish links between genes and cellular phenotypes; this knowledge of human genes and their functions can influence drug development strategies and processes. Optical Pooled Screening (OPS) (Blainey, et al 2019) is a novel screening method that uses optical phenotyping and in situ sequencing to study multiple genes in parallel across millions of cells making this a useful approach to correlate phenotype with genomic perturbation. Because OPS is more laborious compared with classical pooled CRISPR screening methods, OPS has several steps that could benefit from automation. Here we demonstrate the application of automation and custom engineering to the in situ sequencing portion of the process. Double digit cycles of temperature-controlled washing, reagent addition, and imaging are required for complete data capture. Our team has applied an in-house instrument integration and control software to automate this process. A custom washer was built to optimize fluid delivery and removal in 6 well plates. Six well plates are used to maximize the number of cells per plate but can limit 'off the shelf' liquid handling for this well density. An existing multi-fluid internal dispenser was used for reagent dispensing. Both were constructed by starting with internal core technologies (motion control, perfusion interface plates, instrument control architecture). A core technology approach can decrease development to implementation timelines. A multi contact microscope positioning system was incorporated onto to the platform of a Nikon Ti-2e microscope, to eliminate the pre-analysis steps for image position correction prior to full image analysis. These devices are accessed by a stationary Precise Flex collaborative robot for plate movement and the control software allows the user to program operations at both the device and protocol level for in situ assay execution. In summary, we have used a variety of custom in-house software and labware infrastructure solutions to enable automation of optical pooled full genome screens.
Do it yourself: software and equipment for biomedical research
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Open to view video.  |   Closed captions available The process of drug discovery and development is complex and varied, especially in early research and development. There is a constant need for innovation to drive progress towards helping patients. To this end, automation and digitalization are employed to help our researchers to reduce manual labor, increases throughput and generate high quality data required for ML/AI. While many of our needs are met by external vendors, internal teams, aided by an explosion of easy-to-use cobots, vision systems, SILA drivers, rapid oursourced prototyping and other new technologies, are able to delivery working systems expeditiously. Given that research changes so rapidly, quick fixes are what is needed to test ideas, rather than long formal development journeys. In this talk, I will present some of our devices developed in house (automated vision guided flask filling, microscope slide processing, NMR tube filling, peptide synthesis, tablet dissolution analysis, powder sample preparation, closed loop Bayesian optimization of systems) and show how they are in use; hopefully, it will encourage more researchers to DIY in the future!
Machine learning-based architecture for autonomous decision making in automated cell culture
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Open to view video.  |   Closed captions available The generation of cell culture model systems through genome engineering such as CRISPR KO/KI strategies is foundational for drug discovery and development. Despite the widespread adoption of automation technology in many research sectors, particularly in high throughput screening (HTS), cell culture and its associated workflows such as the production of lentiviral particles and subsequent transduction, clonal isolation, and characterization are still performed manually. The lack of automated alternatives to manual labor significantly limits the speed of lifesaving research and the manual character of current workflows leads to diminished efficiency and experimental reproducibility. One main culprit in the lack of available automation for cell culture is the high barrier to entrance to the field of automation. Robotic instruments are non-trivial to integrate into a single robotic online system and commercially available integration platforms are not well-suited to end user driven integration of peripherals, particularly from varying manufacturers with varying communication protocols. Another issue is a lack of integration of machine learning (ML) approaches in automation which would enable the system to make low- and high-level autonomous decisions (i.e. treat with antibiotics, replace media, passage cells) and free up valuable resources and time. To address this problem, we have developed a fully autonomous, automated cell culture system which uses Python-based equipment communication and ML image analysis to conduct cell line maintenance and propagation. The physical implementation of this system is composed of a programmable liquid handler, automated incubator, and a robotic arm with a plate gripper all enclosed in a walk-in biosafety cabinet. Software is implemented entirely in Python and includes a recurrent neural network to measure confluency and growth kinetics of cell lines from phase contrast images as well as seamless communication between all system modules, enabling continuous monitoring and maintenance of dozens of SBS plates with cell lines of interest. Integrating machine learning image analysis with automation technology via high-level programming language like Python provides a rationalized approach for commonplace cell-based workflows. This platform therefore greatly reduces cell culture-related workloads in the laboratory, provides 24/7 monitoring of cell lines, and improves experimental repeatability. It is possible to also equip the cell culture system with capabilities such as a camera mounted on the robotic arm and a messaging system that notifies when errors are detected on the system, enabling remote correction while maintaining access security. In the future further capabilities will be programmed, including cell transfection and transduction, selection, and single clone expansion. Truly automated cell culture represents a key innovation in the field of HTS by streamlining one of the most variable and critical components of biomedical research.
Performance Evaluation of Automated Solid Dispensing Platforms for Use in High-Throughput Automated Workflows for Pharmaceutical Applications
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Open to view video.  |   Closed captions available "As the demand grows for innovative and time-saving workflows in pharmaceutical drug development, implementation of commercially available instrumentation to enhance high-throughput experimentation is critical. A key bottleneck to these workflows is the ability to quickly and precisely dispense the active pharmaceutical ingredient (API) for large batch screens. Often in early screening stages for small molecule candidates, minimal quantities of the API are available ( < 500 mg), yet the need for testing a variety of physicochemical properties including organic solubility, stability, and crystallization strategies remains paramount to progressing drug development. There is currently a multitude of solid dispensing platforms on the market for this purpose, but the performance of such platforms varies based on the experimental goals. The primary goal of this work was to compare the powder dispensing capabilities of four automated solid dispensing units: the Chemspeed SWILE, Chemspeed GDU-Pfd, Chemspeed CRYSTAL, and the Mettler-Toledo Quantos QB5. These systems excel at low dose dispenses yet vary in performance depending on the required tasks and powder properties. Performance metrics evaluated included not only dispensing accuracy and precision, but also the time required to complete the targeted dispense. A collection of powders with varying physical properties were used in the performance evaluation. A secondary goal of this work was to explore the capabilities of the newly released Chemspeed CRYSTAL platform. To provide context for solid dispensing within pharmaceutical applications, a case study was performed utilizing a fully automated organic solubility workflow for a small molecule drug candidate. This case study illustrates the utility of synchronized automation technologies for drug discovery by combining the powder dispensing capabilities of the Chemspeed CRYSTAL, solvent dispensing of the Unchained Laboratories Freeslate CM3, sample handling and dilution protocols of the Hamilton Nimbus, and concentration determination using the Agilent 1290 Infinity II UPLC."
Automation At GSK: Our Journey To The Lab Of The Future
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Open to view video.  |   Closed captions available With this talk we want to showcase GSK’s ambition to embed automated processes across all phases of drug development by first intent. The presentation will focus on selected case studies with a particular focus on data management aspects to enable more efficient data-driven decisions.
The Small Scale Antibody Expression System at GSK; meeting the increasing requirements of modern biopharmaceutical discovery through a new, fully automated antibody expression and purification platform
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Open to view video.  |   Closed captions available As antibody discovery technologies evolve and new selection techniques come online, the number of selection outputs of interest increases. To enable screening of larger panels of antibodies, we have fully automated our transient mammalian and yeast expression processes, both increasing our throughput to up to 1000 clones per run but also improving our product quality and the integrity of our data. Our new Small Scale Antibody Expression System will be described as well as successes and learnings from the project.
Insights through Data, Connecting Lab Automation to Decisions
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Open to view video.  |   Closed captions available How do we make meaningful decisions from data? Nearly every instrument has a log, and movements on robotic platforms are also recorded. How do we extract what’s meaningful and how do we store this information to enable real-time, data-driven decisions? First we must ask ourselves - what questions do we want answered, what will bring the most value to advance projects, and how can the data be used to increase robustness of our screening systems? Operationally, we might be interested in learning:How many of each consumable have we used and how many do we need to order for next quarter?How many successful runs completed by each screening platform? How many errors were seen and which machines or users had the most errors?When was QC last performed on each instrument? - Where are the results of that QC?How many liquid transfers happened on each liquid handler? How many plates were read? How are these numbers trending?Once we know the first few questions we want answered we focus on how to get this data. At Ginkgo Bioworks we have a custom infrastructure in place to link our LIMS with HRB (HighRes Bio) Cellario workcells. This enables us to pass in vital metadata while also extracting runtime information from every Cellario Event using the API. We next push all data from a run into Snowflake (Data Lake / SQL). From there we pull this information back down into Spotfire (Tibco / Perkin Elmer Informatics). We are able to track every plate that runs through our workcellsand have taken an extremely flexible system and standardized specific, useful views of the data. Using this information we combine 6-7 different SQL tables into a cohesive data package as well as joining other information from our internal LIMS Systems. This lets us know things such as which wells failed during an Echo transfer and allows a user to submit those samples for retesting. It lets us know 500 Echo PP-0200 were used in Q1 on 1 platform alone, and providing this info to procurement will allow us to be prepared for Q2 and Q3. Having the data in a structured format has allowed us to answer increasingly specific questions about what’s running on our workcells, how the machines are performing, and what insights can be extracted from our screening campaigns. Importantly, we’ve created a highly scalable data infrastructure that will grow for every new system or modification that will continue to let us learn more. New systems are added in a matter of minutes compared to the weeks required for the initial implementation.
High throughput CRISPR screen using hydrogel Picobeads
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Open to view video.  |   Closed captions available Fluorescence activated cell sorting (FACS) is a major workhorse for high throughput analysis of single-cells that can screen tens of millions of single-cells per day. Recent advancements in droplet microfluidics have enabled the interrogation and enrichment of new phenotypes on FACS such as secreted products and proliferation. Here, we present a hydrogel droplet platform that can be used to assay ~1 million cells in picoliter-scale hydrogel beads, or Picobeads. Cells infected with CRISPR libraries are singulated into Picobeads using a droplet microfluidic device at thousands of beads/sec. Picobeads are then assayed in their independent reaction volumes, sorted based on encapsulated cellular phenotypes using FACS, and their associated CRISPR guides are then recovered on the backend. Using this workflow, the Picobead platform has the potential to unlock new types of screens on FACS, such as for non-autonomous and microenvironment effects on gene expression.
Development of an Automated Open-Port Sampler for High-Throughput Mass Spectrometry.
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Open to view video.  |   Closed captions available Acoustic-ejection mass spectrometry (AEMS) has demonstrated the value of sample dilution in limiting signal suppression in electrospray ionization mass spectrometry (ESI-MS). Systems capable of achieving comparable dilution factors should have utility in screening applications that may not be well suited for AEMS but benefit by not needing complete LC separations.We have developed an automated sampling platform comprised of a pneumatic fluid pump (Air Infinity, Adaptas) and an industrial robotic arm (Meca500, Mecademic), integrated with an Open Port Interface (OPI) for direct quantitative sampling via mass spectrometry. Two distinct workflows were developed. In the first, a stainless-steel needle (0.0625 in. outer diameter and 0.02 in inner diameter) was mounted on the Meca500 to enable aspiration and dispense (A-D) sampling (2-10µL) from a 96W reaction plate. Once aspirated, sample dispense was aided by a pneumatic pulse of pressure that served to ‘eject’ the low volume sample to the OPI. Sample dispense was positioned off-axis to the OPI orifice. In this position the volume captured was reduced, a 5 µL ejection transferred ~ 250 nL to the MS. This approach further diluted the sample thereby reducing signal suppression and aiding ESI-MS analysis.In the second, an OPI needle was fixed at a specific location within the work envelope of the robotic arm. The OPI was configured in a manifold that allowed two solvents to be scheduled during each sampling cycle. The Meca500 was used to pick up a reaction plate and move it under the OPI needle for well-to-well sampling by row. Aqueous or organic solvent was delivered to each well via AI pump programming such that a specific reaction chemistry could be optimized. The cycle time was 2-5 sec per sample dependent on the application.The robotic platform was tested by comparison of IC50 values obtained for biochemical assays that used gradient LC/MS/MS methods for analysis. The targets were, TMPRSS2 (its native peptide substrate and +6 labeled internal standard were monitored) and NNMT (its N-Methyl-Nicotinamide metabolite was monitored). Automated sampling was scheduled using a combination of Python and LUA coding.
Using NMR advancements for richer results in automated synthesis DMTA cycles
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Open to view video.  |   Closed captions available For identifying and quantifying the components of organic mixtures, the use of NMR as a first pass, generalized analytical method with automated workflows is increasingly becoming practicable due to recent developments in NMR experiment pulse sequences, data analysis workflows, and associated NMR technologies. Accurate and precise quantitation of unreacted starting materials, intermediates, products, side products, and byproducts is crucial to providing clearer feedback to AI-based reaction condition recommendation, to reaction optimization algorithms, and to understanding comparative effects of different instrumentation choices in automation. This talk will discuss how NCATS is using these advancements to tackle the distinct challenges in DMTA cycles for chemistry refinement, automation development, and for target synthesis.
High-throughput single cell screening using nanowell-in-microwell plates
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Open to view video.  |   Closed captions available Microwell-based assays are vital experimental tools in life science research, which typically involve seeding thousands of cells in microwells to measure a bulk response to stimulus. However, since response at the single cell level are often heterogeneous, the bulk approach can obscure important behaviour and functions for a subpopulation of the sample. Single cell assays can capture the heterogeneity of cellular response. These assays are frequently performed by confining individual cells in arrays of nanoliter wells (nanowells). Current approaches for fabricating nanowells using polydimethylsiloxane (PDMS) cannot provide a glass bottom surface, which limits the quality of microscopy imaging, as well as compatibility with available infrastructure for high-throughput imaging. Here, we used laser micropatterning of polyethylene glycol diacrylate (PEGDA) to produce monolithic nanowells inside a standard glass-bottom microwell in a 384-well imaging plate. The nanowells can be as small as 50 x 50 µm, allowing ~2,100 nanowells to be patterned in each microwell. These patterned hydrogel nanowells exhibit stable adhesion to glass with minimal protein absorption, which enables high-resolution image-based assays. Furthermore, nanowells can retain both cells and beads during reagent exchange, enabling simultaneous profiling of phenotyping and single cell secretion via immunostaining. We used these nanowells to perform three types of single cell experiments. First, we measured the proliferation of single CHO cells in nanowells to assess the variability in cell proliferation rate. Imaging cell growth every 24 hours for 10 days, we categorized single cell colonies into fast growing group that doubled every ~12 hours, as well as a slow growing group that doubled every ~24 hours. Second, we measured the motility of single cancer cells to measure their response to cytokine stimulants and anti-cancer drugs. Using the human breast cancer cell line, MDA-MB-231, we tracked cell positions in nanowells for 24 hours after exposure to TNF-????. We found heterogeneous cell motility change in response to external cytokine stimuli, where one group shows significant increase in motility, while the other group shows similar motility as control cells. This experiment demonstrates the potential to perform drug screening on primary cell samples that may be heterogeneous. Finally, we assessed the cytolytic activity of CAR-T cells by depositing single CAR-T cells with multiple target cells in nanowells. We found that a small group of CAR-T cells demonstrated a “serial killer” response to target cells, while other CAR-T cells had limited or non-existent killing activity. Together, high throughput single cell screening using a nanowell-in-microwell plate enables single cell spatial-temporal tracking, which could greatly expand the potential applications of existing high throughput microwell plate screening platforms and could potentially be adapted to screen primary and heterogenous cell samples using existing infrastructure for high-throughput and high-content screening.
Economy in the Scale: Biological Relevance, Reproducibility, 2D and 3D Cell Biology and Automation from Nano-litre to Litre Volumes.
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Open to view video.  |   Closed captions available "Cell biology has been transformed by the rapid advances in Automation, Informatics, Analysis and Reagent technologies. However, despite the availability of these highly advanced and valuable research tools our current working practises in Cell and Tissue Culture have largely remained unchanged since the 1950’s. Despite the fact that these conventional methods and working practises have served us well for many decades, there is now an increasing awareness that these tried and trusted techniques must be developed and improved to meet the rapidly evolving needs of Biomedical research and bio manufacturing communities. In this presentation we will showcase the results of a decade of intensive research and development. During this time, we have aimed to predict and address many of the future unmet needs in the field of Cell and Tissue culture in both the research and manufacturing sectors. Our primary focus over this period has been the maintenance and culture of cells at Nano Litre to Litre Scales whilst improving biological relevance, reproducibility. Another key aspect of our work has been to ensure our technologies are forwardly compatible with all commonly used, new and emerging analytical and laboratory automation platforms. Our technologies have been developed for both in 2D and 3D cell culture and falls into 3 main categories (i) Liquid cellular scaffolds for 3D cell culture, (ii) solid state environmental buffering technologies and (iii) highly advanced bioreactor systems what are currently in development for large scale muscle cell culture. Finally, we will present a range of compelling results from our own labs and those of our research partners, in the form of Biochemical, imaging, HCA and gene expression data. Demonstrating the utility and robustness of our technologies in a broad range of research settings."
Automating a Next Generation Ultra-High-Throughput Screening Platform
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Open to view video.  |   Closed captions available Automating a Next Generation Ultra-High-Throughput Screening Platform Craig M. Schulz Ph.D.Head of AutomationTerray Therapeutics Terray Therapeutics is a drug discovery and development company working to propel drug discovery into the information age. Terray’s proprietary integrated computational and experimental platforms generate massively scaled, powerfully agnostic chemical data that are purpose-built to power computational learning and reveal new interactions. The Company’s core experimental technology leverages ultra-high throughput small molecule screening against a vast array of therapeutic targets. Our core process technologies have been constructed and automated in-house and encompass the design, optimization, and build of our diverse combinatorial libraries on nanoscale supports. In addition, we have optimized and built technologies for DNA sequencing and high throughput/high resolution microscopy. Finally, our process integrates rapid microscale resynthesis of small molecule compounds for hit confirmation using automated biochemical and cellular assays. Our physical wet lab processes are complimented by our capabilities to conduct experiments in silico and to optimize our chemical synthesis using machine learning to efficiently feed our predictive AI models. This talk will cover an overview of the physical means and automated technologies we at Terray employ to screen potential therapeutic molecules at a rate of ~70M per minute.
Novel approach to drug discovery for Chagas disease
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Open to view video.  |   Closed captions available Chagas disease is a zoonotic infection caused by the protozoan Trypanosoma cruzi. Most infected patients fail to clear the infection in the acute phase and remain chronically infected, with 30–40% of them developing life-threatening heart or gastrointestinal sequelae. In addition to the burden of disability and economic impact, Chagas disease causes about 14,000 deaths annually in Latin America, being a relevant public health problem. The available treatments are nifurtimox or benznidazole, but both drugs have undesirable side effects. Additionally, these drugs have variable and generally low efficacy, and parasite dormancy is hypothesized as an obstacle to treatment [1]. At Calibr, in partnership with the University of Georgia, Athens, we are undertaking a drug discovery program targeting Chagas disease by selecting active compounds against non-replicative intracellular amastigotes. As part of this effort, we have developed a multi-parameter high content imaging assay using a cell trace proliferation dye to identify non-replicative parasites. Using this cell-based phenotypic high-throughput assay we screened the 12,000-compound ReFRAME repurposing library [2] and Calibr’s 300,000 compound chemical diversity collection. Active compounds were selected by multiple criteria including decrease in percentage of infected cells, the number of non-replicative amastigotes, and compound selectivity. Establishment of the high-throughput assay and early results of our screens will be discussed.
The use of integrated robotics platforms to automate advanced cellular assays for drug discovery
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Open to view video.  |   Closed captions available Advances in cellular models are enabling the generation of more disease relevant data for drug discovery. In order for these physiologically-relevant models to be utilised for high-throughput drug screening and profiling, there is a need for the miniaturisation and automation of complex cell-based assays. We have designed and built integrated robotics platforms for the automation of assays in a range of physiologically-relevant models, including primary human hepatocyte spheroids, primary human T cells and patient-derived organoids. These automated platforms will increase the throughput of these complex assays, enable kinetic sampling, ensure accurate timing control of critical experimental steps and reduce resource burden. Importantly, when combined with multiparametric readouts, these automated cellular screens can provide a wealth of disease-relevant data for the drug discovery field.
A novel platform for automated and efficient handling of scaffold-free 3D cell-culture models enables well-controlled large-scale 3D in vitro drug screening
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Open to view video.  |   Closed captions available Drug discovery and screening require reliable model systems mimicking physiological characteristics of a disease. In this direction, in vitro studies with three-dimensional (3D) cell-culture models, like spheroids or organoids, show high relevance. Additionally, screening on patient-derived organoids allows the examination of the individual drug response. The difficulties to standardize study conditions, such as properties and numbers of 3D cell clusters as well as variations due to handling, offset the great potential of 3D in vitro models and limit the reproducibility. Moreover, large-scale feasibility is complex due to a lack of automation technology.To overcome this, we developed an automated workflow based on our in-house built 3D cell-culture platform, capable of generating spheroids in a highly reproducible manner, selectively processing and transferring 3D cell clusters (spheroids or organoids), and performing drug treatment.The platform generates spheroids via the hanging drop method. A thin capillary transfers cell suspension from a reservoir to a non-contact piezo-electric droplet dispenser via capillary forces. Constant and gentle mixing of the cell suspension in the reservoir maintains a homogeneous cell distribution over long periods without damaging the cells. The droplet dispenser prints nanoliter droplets on demand in order to create drop arrays with a desired volume. Both, the well-controlled volume scalability and gentle mixing result in uniform large-scale spheroid generation with adjustable sizes. The formation success rate is over 95% and size variation is below 10%.The processing module can prepare the generated spheroids, but also various types of organoids for a drug screening assay. For that, the sample is placed in a petri dish and an image-based computer vision module is used to detect, for example, suitable spheroids of a specific size. A thin capillary actively aspirates these spheroids and transfers them to the droplet dispenser in a pipeline-like manner. Multiple spheroids are transferred simultaneously through the capillary with a rate of up to one spheroid per second without reducing the viability. The spheroids are then placed individually at a target position, for example into a microwell plate. The adjustable number of spheroids and their sizes per individual well allows tailoring the treatment study and increasing efficiency. Afterwards, the droplet dispenser can add drugs with nanoliter resolution. The investigation of the size- and spheroid concentration-dependent drug response to cisplatin demonstrated the capabilities of the instrument.Our platform represents a powerful tool to eliminate sources of unwanted variations and to precisely assess the drug response. The optical monitoring of the sample before processing reduces loss rates and provides a low-labor workflow for 3D cell culture without the necessity of extensive sample preprocessing. The reliable and automated handling of 3D in vitro models pushes drug screening to a new level and enables the expansion of personalized therapy approaches.
A high-throughput ex vivo ovulation screening platform to identify novel non-hormonal contraceptive candidates
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Open to view video.  |   Closed captions available The conventional hormonal birth control pills effectively inhibit ovulation but also cause undesired side effects, such as cancers, depression, stroke, and obesity. There is now an urgent unmet need to develop novel non-hormonal contraceptives. We have previously established a 3D in vitro ovarian follicle culture system, termed encapsulated in vitro follicle growth (eVIFG). The eVIFG faithfully recapitulates key ovarian functions, including folliculogenesis, hormone secretion, oocyte maturation, and ovulation. Here, we aim to develop a high-throughput mouse follicle ovulation screening platform starting from eIVFG for discovering novel non-hormonal contraceptives. Based on our recently established closed vitrification system for cryopreserving immature mouse ovarian follicles, we first used fresh and vitrified antral follicles grown from eIVFG for single-follicle RNA sequencing (RNA-seq) analysis and demonstrated that vitrified follicles had comparable follicular cell transcriptomic profiling to fresh follicles, indicating that vitrification conserves molecular signatures of gonadotropin-dependent folliculogenesis and ovulation. We next used the vitrification method to build a high-content mouse ovarian follicle biobank and also developed a tiered high-throughput compound testing and ovulation screening pipeline. In Tier 1, fully-grown mouse preovulatory follicles from eIVFG were treated with 10 IU/L human chorionic gonadotropin (hCG) for the ovulation induction; meanwhile, follicles were co-treated with candidate compounds at a single high dose of 10 mM. The ovulation success was evaluated 15 hours post-hCG treatment. Follicles with inhibited ovulation were cultured for an additional 48 hours to allow for luteinization and progesterone secretion. Compounds that effectively inhibited follicle ovulation without affecting progesterone secretion were advanced to the Tier 2. In Tier 2, we performed a similar ovulation screening experiment to the Tier 1 except that follicles were treated with a wider concentration range of candidate compounds. Compounds that inhibited ovulation in a concentration-dependent manner without disrupting progesterone secretion were further advanced to the Tier 3, which includes molecular target identification and in vivo mouse validation. Using this three-tiered ovulation screening pipeline, we have demonstrated found that chlorpromazine (CPZ) and proprotein convertase inhibitor (PCI) significantly inhibited mouse follicle rupture during ex vivo ovulation with interfering with ovarian hormone secretion, indicating that CPZ and PCI involved/targeted molecular pathways are essential for follicle rupture and ovulation, presenting attractive druggable targets for the development of non-hormonal contraceptives. Taken together, our studies demonstrate that the tiered high-throughput ex vivo ovulation screening platform is a powerful model for discovering ovulation-based non-hormonal contraceptive candidates.
Implementing advanced microscopy modalities including FLIM, FRET, quantitative phase contrast and super-resolved microscopy in an open source modular automated multiwell plate platform
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Open to view video.  |   Closed captions available "We are developing an open multidimensional fluorescence imaging platform [1] building on a range of instruments developed in our laboratory, including fluorescence microscopy, high content analysis (HCA), endoscopy, and optical projection tomography (OPT). Believing that the application of any microscopy technique to systematic studies of cell biology would benefit from the statistical power, lack of operator bias and uniformity of sample preparation inherent in HCA, we have particularly worked to implement and widen access to fluorescence lifetime imaging (FLIM) and Forster resonant energy transfer (FRET) HCA [2,3], and are extending this to super-resolved microscopy [4] and quantitative phase imaging. I will review our work on FLIM and FRET HCA, including its integration with a novel single-shot semiquantitative phase imaging technique [5] that can be implemented on almost any fluorescence microscope to provide label-free cell segmentation, morphometrics and tracking for single cell resolved studies, e.g., of heterogeneity in the response to drugs. The low phototoxicity enables high temporal sampling for cell tracking over multiple cell cycles without the phototoxicity associated with fluorescence readouts. I will also present our work towards super-resolved HCA, developing automated multiwell plate easySTORM [4,6], providing low-cost, large FOV SMLM together with accelerated open-source SMLM analysis parallelised on a high-performance computing cluster [7]. For our current and future fluorescence microscopy and HCA, we are developing a modular open-source microscopy hardware platform, both to widen access for lower resource settings and to enable cutting edge laboratories to accelerate prototyping of new instruments. This platform is based on openFrame, a low-cost, modular, microscope stand. We have utilised openFrame to prototype a novel multibeam multiphoton multiwell plate (M3M) microscope for 3D HCA of organoids and other 3D disease models We are developing and curating cost-effective components to implement automated open microscopy for a range of HCA modalities, including a novel optical autofocus module [4], and are exploring the utility of newly available low-cost cooled CMOS cameras for fluorescence imaging including SMLM. [1] see, e.g., or [2] Margineanu et al., Sci. Rep. 6 (2016) 28186; [3] Görlitz et al., J. Vis. Exp. 119, (2017) e55119, [4] Lightley et al., J Microscopy (2021); [5] Kalita et al., J Biophotonics (2021) e202100144; [6] Kwakwa et al., J. Biophotonics 9 (2016) 948; [7] Munro et al., J. Micros. 273 (2019) 148; "
Automated production of spheroids by magnetic cell assembly for drug response profiling
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Open to view video.  |   Closed captions available Cells grown in a 3D environment more accurately recapitulate the in vivo situation of native tissues. 3D models, therefore, show a higher physiological relevance in terms of proliferation, differentiation, metabolism, and gene expression. Many 3D cell culture methods have been developed with great potential for use as more realistic models in tissue engineering, drug development, and basic research.One approach to achieving 3D cell culture is using in vitro aggregation of cells to generate spheroids, and this has become an essential tool in research today. However, there are currently challenges in spheroid production related to uniformity, variations in size, and compatibility with automation for high throughput screening applications. In addition, tissue thickness and plate geometry can impair the quality of imaging-based readouts.  Here, we outline an automated workflow to tackle these limitations, using magnetic 3D cell culture (M3D) for the rapid generation of spheroids in a highly reproducible manner. Cells are magnetized with nanoparticles (Nanoshuttle, Greiner Bio-One), which adhere to the cell membrane electrostatically. Magnetized cells are then seeded into cell-repellent flat microplates sitting on a magnet array, accelerating the formation of size uniform spheroids. This approach can be easily incorporated into an automated workflow, as demonstrated in this study showcasing spheroid generation using a Fluent Automation Workstation (Tecan).To highlight the applicability of these spheroids in compound screening, a D300e Digital Dispenser (Tecan) was used to dispense low-volume concentration gradients across a microplate of magnetized spheroids. The combination of the Fluent workstation, D300 dispenser, and M3D speeds up the workflow, reducing the time and amount of material required. Image-based quality control was performed during the growth phase using a Spark Cyto imager plate reader (Tecan) to ensure reliable screening results. The effects of compound concentration and spheroid size were assessed by live/dead analysis and luminescent cell viability readouts.  The combination of controlled and reproducible spheroid formation, high-quality imaging in flat bottom cell-repellent plates, and an automated workflow can potentially increase the reproducibility and accuracy of drug screening with 3D cell cultures. Such systems allow researchers to evaluate drug effects in a physiologically-relevant environment, facilitated by magnetic 3D cell aggregation techniques in combination with automated liquid handling and imaging/detection capabilities. Overall, this workflow addresses and overcomes some of the challenges and limitations of 3D cell culture high throughput screening.
Using multi-OMICs approaches to drive target discovery.
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Open to view video.  |   Closed captions available The Victorian Centre for Functional Genomics is a technology platform that supports researchers Australia-wide to perform sophisticated assay development technologies together with high content imaging-based cellular phenotyping. Using liquid handling automation we have developed a screening pipeline for embedding patient-derived cells in scaffold matrices, enabling 3D organisation and drug screening. We have automated fixing and staining methodologies to deliver phenotypic cell painting in 3D resolution, enabling deep learning strategies to identify targets of specific interest across numerous patients. In parallel, we have developed barcoded high throughput transcript profiling of 3D cultures in 384 well format to characterise patient material expression over time, and to correlate phenotype with genotype. This presentation will show highlights of these technology applications with a specific focus on prostate carcinoma.
Extracellular vesicle (EV) biogenesis, diversity, and fate: Prospects for high throughput screening assays
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Open to view video.  |   Closed captions available All cells release extracellular vesicles (EVs) carrying molecular cargo that can interact with nearby or distant cells and affect their function. EVs and their cargo are thus attractive as potential biomarkers and delivery vehicles, but our mechanistic understanding of EV biogenesis and uptake is limited by a lack of tools for the measurement of individual EVs and their interactions with cells. Single cell and single vesicle cytometry can provide the quantitative measurements required, but EVs are small, dim and difficult to measure using conventional instruments and assay approaches. In this presentation I will review the needs for single vesicle analysis, summarize recent advances in instruments and assays for high throughput single EV analysis, and highlight future prospects for high throughput screening of EV biogenesis and uptake by single cells.
Engineering an automated platform for high-throughput production of plasmid DNA without in-process cross-contamination
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Open to view video.  |   Closed captions available "The global demand for plasmid DNA has risen dramatically since the advent of cell and gene therapies (CGT) and has experienced hyper-growth following the outbreak of the COVID-19 pandemic. These cutting edge therapies come in many forms but all of them rely on plasmid DNA at some point either in their manufacture or mechanism of action. Unfortunately, scaling up manufacturing capacity for plasmid DNA is a difficult operation and it has become a bottleneck for the CGT industry. Contract development and manufacturing companies (CDMOs) can no longer meet the demand for high quality plasmid DNA due to substantial backlogs and the lack of automated solutions for plasmid manufacturing. This can significantly impede R&D pipelines and harm the expectations of the market, and most importantly that of the patients who are waiting for these therapies. Viral vectors form the backbone of CGT and despite their considerable promise they are still beset by manufacturing challenges. The low yields of functional capsids containing the desired genetic payload remains a hurdle. Empty capsids require much larger doses to be delivered and this can provoke a strong immune response. New approaches in capsid engineering can yield millions of variant capsids which are screened for desirable properties. To systematically screen variants and scale up to 100mg-1g quantity of DNA for preclinical testing requires high-throughput plasmid manufacturing capabilities that almost all CGT companies presently lack. Here we present GenScript’s new high-throughput automated plasmid production platform designed to produce 1000 ultra-low endotoxin plasmids at the mg scale per day. This is an integrated platform bringing the best of industrial automation to a biological manufacturing process. The platform consists of six industrial robot operated modules encompassing inoculation, incubation, lysis, chromatography and solvent extraction. It can operate continuously with in-process cleaning to prevent cross-contamination. We also present a new paradigm for bacterial culture and lysis in single-use bottles instead of flasks or fermenters. We have demonstrated that we can obtain plasmid yields of 1mg with endotoxin levels < 0.05EU/μg and supercoiled content >90%. Our platform can produce transfection-grade plasmid libraries for capsid and vector screening, genome-wide CRISPR libraries, and in vitro transcription (IVT) templates for mRNA production for the CGT industry. GenScript will accelerate the commercialization of new CGT products by providing high quality plasmids with a two-day turnaround time. "
Rapid arrayed CRISPR guide RNA library cloning to enable large-scale arrayed screens
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Open to view video.  |   Closed captions available Pooled CRISPR screens have improved the quality and power of functional genomics experiments, yet this approach is limited to one-dimensional phenotypes, such as cell survival or the expression of a single reporter gene. Arrayed CRISPR screens would expand the number of accessible assays, but collections of arrayed guide RNA clones are limited. For example, genome-wide Cas9 RNP-based screening libraries are commercially available but require delivery through electroporation that is difficult to perform in a high throughput manner. Additionally, RNP libraries only exist for CRISPR nucleases and are not compatible with CRISPR inhibition and activation screens. To facilitate the creation of arrayed CRISPR clone libraries, the LGR developed a pooled-to-arrayed guide RNA cloning procedure that leverages acoustic liquid handling and next generation sequencing. This process is fast, flexible, and relatively inexpensive and can be used to create large high quality guide RNA arrayed libraries for any CRISPR application.
Reduction of Plastic Waste Through the Use of Automated Pipette Tip Washing
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Open to view video.  |   Closed captions available Operations of scientific laboratories are largely built upon the accepted use of disposable products. Every day, massive amounts of pipette tips, microplates, cell flasks, and much more are consumed and thrown away after a single use only to be incinerated or tossed into a landfill, in turn, negatively impacting our environment. Ideally, we would minimize this detrimental effect by reducing the amount of waste generated from the assays conducted in our labs while maintaining the integrity of the data produced. Over the last 7 years, the National Center for Advancing Translational Sciences (NCATS) has been working towards minimizing waste from our high throughput screening systems through in-house process adjustments, as well as by evaluating and integrating eco-friendly peripheral devices into our various screening platforms. An example is a pipette tip washer with the capability of cleaning and drying a large variety of pipette tip sizes and brands found in most lab settings. To this end, we have integrated the Grenova TipNovus Mini onto our Wako Automation cherry picking robotic platform in order to automate 384-pipette-tip washing which has helped us to dramatically reduce the waste being generated during siRNA screening library preparation and assay-ready plate stamping in an efficient and cost-effective matter. Comparing siRNA screening results from assay-ready plates prepared using new versus washed pipette tips containing the same samples and run in the same assay demonstrates that the data are unaffected by the use of washed pipette tips. Incorporating pipette tip washing into the workflow allows us to maximize the runtime of this robotic system and increases its functionality, thus allowing us to adopt the same methodology of tip washing to other processes. Integration of this pipette tip washer has helped us to take a significant step towards operating in a more environmentally conscious manner while continuing to produce reliable high-quality data.
Micro-Nano Technologies
Quantitative biology with droplet microfluidics
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Open to view video.  |   Closed captions available Many questions at the forefront of biology depend on the interactions of millions of single cells. My lab develops technologies for studying large numbers of single cells. In this talk, I will describe our approaches for sorting cells based on genomic and transcriptomic markers, and performing multi-omics analysis of single cells that allow simultaneous characterization of genomic, transcriptomic, and proteomic signatures. I will also describe how we are adapting these techniques to integrate genomics with other single cell measurement approaches, including imaging, mass spectrometry, and atomic force microscopy. Finally, I will describe how we are using these techniques to build cells into controlled consortia for microbiological studies and bottom-up tissue synthesis.
Integrative, functional multi-omics for the discovery and development of immune cell redirection therapeutics
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Open to view video.  |   Closed captions available Novel multi-modal, multiplexed technologies have significantly enabled the discovery and development of immuno-oncology (IO) therapeutics, where a functional understanding of cancer cells in the context of their tumor immune microenvironment is critical. Currently, the most advanced analytical technologies allow for high-content phenotyping and parallel -omics analyses for split patient samples; however, most approaches only provide a static snapshot and/or do not allow for truly integrated multi-omic analyses of dynamic primary cocultures ex vivo. The combined multi-omic analysis of the same cells is particularly challenging for suspension and immune cells due to their non-adherent nature and susceptibility to shear forces. We developed a microfluidic platform enabling complex ex vivo cocultures of cancer cells in an autologous immune microenvironment characterized by fully integrated, multi-omic readouts, including high-content, single-cell fluorescence microscopy imaging, soluble protein proteomics, and downstream transcriptomics analysis. This truly multi-omic platform yields an unprecedented depth of information to understand underlying cancer disease biology and evolution for the discovery and development of next-generation IO therapeutics.
Elevating & Automating Cell Purification with Digital Magnetic Sorting
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Open to view video.  |   Closed captions available Purification of specific cell populations from a sample or donor biomatrix is a critical capability across almost every biotechnology sector. Through extensive interviews with tool users, stakeholders, and key opinion leaders in the precision medicine field our team has learned that cell separation technologies have a fundamental tradeoff between their precision/modularity and speed/scalability. High precision sorting platforms like FACS can isolate cells with high specificity but have limited scalability for processing large samples. Conversely, magnetic cell sorting is highly scalable but its binary nature limits purification based on multiple markers and isolating rare cells from large backgrounds. Ferrologix has pioneered a novel cell purification technology called Digital Magnetic Sorting (DMS) that leverages the scalability and gentle nature of magnetic sorting but augments it with quantitative capabilities more like FACS. With DMS technology we have demonstrated improved purity in isolation of rare cell populations as well as fractionating T cell populations based on multiple markers. We believe that our DMS platform can support scaling and automation efforts in medical research, clinical sample preparation, and cell therapy manufacturing.
Intestine-On-Chip As An Analytical Assay Platform
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Open to view video.  |   Closed captions available Organ-on-chips are miniaturized devices that arrange living cells to simulate functional subunits of tissues and organs. These microdevices provide exquisite control of the tissue microenvironment for the investigation of organ-level physiology and disease all while using human primary tissue. A range of intestine-on-chip devices were developed as bioanalytical platforms for assay of microbiome-behavior, drug-delivery and transport, pharmaceutical screening, tissue repair and regeneration and other intestinal functions. Simple monolayer systems populated with either differentiated or stem/proliferative cells provide high throughput with direct and facile readouts. 3D systems recapitulate the in vivo gastrointestinal epithelial architecture and physiology providing lower throughput but high content assays. Patterned 2D systems possess intermediate properties and are of particular value for studies of tissue regeneration. In all of these systems, primary human intestinal cells are cultured on a planar, patterned, or shaped hydrogel scaffold. Example applications of each of these systems will be presented. Monolayer systems enriched for enteroendocrine cells (critical regulators of body weight, food intake, and blood glucose levels) have supported compound screens for induction or inhibition of serotonin or GLP-1 secretion. A patterned planar, self-renewing human intestinal platform or 2D crypt model, has been developed to screen compounds to assess quantitatively compound effects on cell density, proliferation, migration, viability, and the abundance and localization of post-mitotic lineages as a function of time. The model has been used to perform a small-scale screen of compounds, including signaling molecules, endogenous hormones/cytokines, and microbial metabolites on tissue homeostasis. Highly sophisticated 3D intestinal models possess an array of crypt-like structures replicating the intestinal architecture including a stem-cell niche and differentiated cell zone. All 3 systems can support a protective mucus layer as well as an oxygen gradient across the tissue. The oxygen gradient provides an anaerobic luminal tissue face so that the obligate anaerobes found in the normal human large intestine can be co-cultured with the intestinal tissue. Intestinal biopsy samples can be used to populate these constructs to produce patient-specific tissues for personalized medicine and disease modeling.
h-VIOS: A novel human organ-on-a-chip platform using vascularized biomaterials
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Open to view video.  |   Closed captions available Organs-on-chips and tissue engineering have revolutionized the way we think about modeling human physiology and pathology in vitro. However, a significant challenge has posed a limitation in the advancement of these models: the ability to introduce vasculature into tissues, which is crucial for cell survival and function. 3D Systems technology enables the creation tissues out of materials that mimic the extracellular matrix, containing a vascular network that provides nutrient delivery and waste removal. Using 3D Systems 3D printing and bioprinting technologies, Systemic Bio has invented the h-VIOS platform, enabling scalable production of vascularized hydrogels compatible with a variety of cell types, from healthy and diseased cell lines to stem cells and human primary cells, which can be used for drug testing. In this presentation, we will go over the h-VIOS system and how it has been used to model different organ and disease functions in vitro.
3D multicellular intestine-on-a-chip model for disease modeling and drug discovery
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Open to view video.  |   Closed captions available "Intestinal barrier disruption resulting from inflammatory conditions such as inflammatory bowel disease (IBD) or due to drug-induced toxicity can lead to life-threatening conditions. Current in vitro 2D intestinal models lack key features of the in vivo settings like tubular structure or perfusion, resulting in low translatability to the human situation, fail in clinical translation and cease drug discovery. Microfluidic techniques are increasingly recognized as an important toolbox to add physiologically relevant cues to traditional cell culture. These cues include long term gradient stability and continuous perfusion. Microfluidic technology also allows patterning of cell layers as stratified co-cultures that are devoid of artificial membranes, helping to capture complex tissue architectures found in vivo. Previously, we have introduced the OrganoPlate® microfluidic platform that accommodates up to 64 independent microfluidic chips in a microtiter plate format, allowing growing 64 independent intestinal barrier tissues as perfused tubules. These gut tubules are suitable for high-throughput screening of compound effects through real time imaging of transport and barrier integrity. Additionally, we developed the OrganoTEER instrument that allows determining the Trans Epithelial Electrical Resistance (TEER) of barrier tissues in Organ-on-a-Chip models in a fast and sensitive manner. TEER values can be determined simultaneously for all intestinal tubules and the instrument can be placed within an incubator to enable automated long-term monitoring of TEER over the entire duration of an epithelial integrity study. Different levels of intestinal complexity can be achieved in OrganoPlate through co-culture of gut epithelium with supporting cells, vasculature, and immune cells. This technology allows plug and play modularity of models to mimic different biological complexities to study inflammatory processes found in conditions like IBD. We established a unique intestine-on-a-chip model where inflammation was induced by addition of proinflammatory triggers and effects were assessed by measuring TEER and secretion of proinflammatory cytokines at the apical and basal sides. The cytokines induced an inflammatory state in the culture, as demonstrated by the impaired barrier integrity and increased cytokine secretion. We also assessed the applicability of the model in screening anti-inflammatory compounds by using the well-known anti-inflammatory drug TPCA-1. Exposure to the drug prevented an inflammatory state in the model. In summary, our results highlight the suitability of our in vitro microfluidic intestine-on-a-chip model to mimic key physiological aspects of the intestine and offers novel ways for studying the organ physiology as well as inflammatory disease mechanisms. This intestinal inflammation model can be applied in large-scale screening in the search for novel treatments."
Rational Vaccinology: In Pursuit of the Perfect Vaccine
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Open to view video.  |   Closed captions available Spherical Nucleic Acids (SNAs) are a new class of therapeutic architectures, consisting of oligonucleotides radially conjugated to a nanoparticle core. This three-dimensional architecture imparts novel properties to its constituent nucleic acids, making SNAs extremely useful in a wide array of biomedical applications, from gene regulation to cancer immunotherapy, and vaccine development. The emergent properties of SNAs are revolutionizing the way we study, track, and treat disease and in the process, laying the foundation for a new field of rational vaccinology: elucidating and leveraging the structure-activity relationships of SNAs to arrive at the most potent immunostimulatory construct. My group is advancing this vision forward by treating solid tumors with immunostimulatory SNAs that activate immune response against cancer cells. Additionally, because of their modular and programmable nature, SNAs can be designed to incorporate many types of antigens associated with either cancer immunotherapy (e.g., tumor-associated antigens and neoantigens) or infectious diseases (e.g., the spike protein of Covid-19). We have found that the composition and architecture of immunostimulatory SNAs (i.e., the choice and spatial organization of each component in the SNA scaffold) can transition the vaccine from mildly effective to curative. This presentation will highlight these advances and illustrate how rational vaccinology may improve human lives.
Accurate Binding Kinetics of Biological Nanoparticle Analytes
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Open to view video.  |   Closed captions available Interferometric reflectance imaging sensor (IRIS) technology is based on interference of light from an optically transparent thin film—the same phenomenon that gives rainbow colors to a soap film when illuminated by white light. IRIS has two modalities: (i) low-magnification (ensemble biomolecular mass measurements) allowing for multiplexed affinity measurements and (ii) high-magnification (digital detection of individual nanoparticles). Single-particle IRIS has been demonstrated for detection and characterization of individual biological nanoparticles (BNP) such as virions and extra-cellular vesicles. Low magnification IRIS offers large field of view and ability to simultaneously quantify binding of analytes to highly multiplexed probe molecules arrayed on the sensor surface. However, accurate characterization of large analytes (50-150nm size) presents challenges due to non-linearity of the optical interference signal with surface binding of sparse BNP analytes.In this presentation, we will discuss our innovations in the design of imaging optics and co-optimization of illumination and sensor ship parameters to perform detection and phenotyping of large analytes, such as virions, extracellular vesicles (EVs) and antibody-conjugated gold nanoparticles (mAb-GNPs). We demonstrated how the improved IRIS platform can bridge the gap between single-particle detection (’digital’ configuration) and ensemble reflectance measurements (’analog’ configuration), creating a new ’hybrid’ system (h-IRIS), providing a substantial improvement in sensitivity, improving the limit of detection by three orders of magnitude. This new configuration of IRIS combines the advantageous features of high-magnification and low-magnifications modalities providing high sensitivity along with large field-of-view enabling highly multiplexed binding kinetics. With the high multiplexing capability, we have demonstrated the ability to vary the capture probe density on the chip surface over more than an order of magnitude. In this manner, both multi-valent and single-valent binding properties of BNP analytes can be tested against a multitude of antibody probes. Furthermore, the new modality allows for estimation of the size of target analytes. We will discuss the theoretical consideration of IRIS technology and experimental results showing multiplexed kinetic characterization of BNP analytes. This technology will have a significant impact on characterizing viral vectors for gene therapy applications as well as extra-cellular samples paving the way towards effective diagnostic and therapeutical advances.
Nano-based antibody targeting CD99/FLT3 in AML
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Open to view video.  |   Closed captions available "Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by the block of differentiation and uncontrolled proliferation of myeloid cells. The 5-year survival for patients with AML is < 30%. FLT3-ITD mutations, observed in ~30% of AML are associated with even shorter survival. Our lab reported CD99 is also overexpressed in FLT3-ITD AML, making these receptors viable targets. Here, we developed elastin-like polypeptide (ELP) fusion proteins capable of assembling antibody-based nanoparticles that target both CD99 and FLT3 receptors. These were produced by bacterial expression in ClearColiTM. We compare their therapeutic potential to fusion proteins targeting a single receptor. To assess the effects of our FLT3-A192 and CD99-A192 fusion proteins, we treated FLT3-ITD+/CD99+ AML cells (MV4-11, MOLM-13), FLT3WT+/CD99+ (THP-1), FLT3-/CD99+ cells (U937) with 5μM of our construct and observed a significant decrease in cell viability after 72 hours. MV4-11 cell viability was significantly reduced in treatment groups; however, what was more interesting is that a dual-targeted, co-assembled FLT3/CD99 therapy far out-performed controls [(FLT3-A192 vs. FLT3/CD99 co-assembled, p < 0.001, 49% decrease) (CD99-A192 vs. FLT3/CD99 co-assembled, p < 0.0001, 50% decrease) (FLT3-A192 + CD99-A192 versus FLT3/CD99 co-assembled, p < 0.0001, 38% decrease)]. Similarly, MOLM-13 cell viability significantly decreased in the co-assembled group vs. controls [(FLT3-A192 vs. FLT3/CD99 co-assembled, p < 0.02, 19% decrease) (CD99-A192 vs. FLT3/CD99 co-assembled, p < 0.007, 22% decrease) (Combination (FLT3-A192 + CD99-A192) vs. FLT3/CD99 co-assembled, p < 0.004, 24% decrease)]. There was no difference in FLT3-ITD negative cell lines (U937, THP-1) cells between the treatment groups and controls. Additionally, there was no difference observed between a control vehicle A192 and the untreated groups, signifying that A192 (ELP without the scFv fusion) alone has no effect as a carrier. The survival of NSG mice engrafted with 2.5 x 106 MOLM-13 and treated at day 7, 10, 13, and 16 was also examined. Four groups were administered 175 mg/kg of either control A192, FLT3-A192, CD99-A192, and a combination of both FLT3-A192 and CD99-A192 at 87.5 mg/kg of each. This study showed the survival times in mice in the combination group survived longer than either the FLT3-A192 or the CD99-A192 groups. To explore the mechanistic relationship between both FLT3 and CD99 we examined the effect of FLT3 surface level expression after treatment with CD99-A192. MOLM-13 cells treated with 10μM CD99-A192 resulted in an increase in FLT3 surface level expression after 2 hours of treatment (p < 0.05, 46% increase). However, this effect was not seen in THP-1, which express wild type FLT3 but not the FLT3-ITD mutation. This effect was not seen in U937 cells (FLT3 negative), further illustrating the benefit of leveraging the interaction between FLT3 and CD99. Our findings suggest that dual targeting of FLT3-ITD and CD99 on an antibody-based nanoparticle results in a greater therapeutic output than targeting each receptor alone."
Image-based screening of pooled genetic libraries
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Open to view video.  |   Closed captions available Pooled genetic screens have been critical for the systematic identification of genes underlying cellular processes, but have largely been limited to phenotypes defined by cell viability, flow cytometry, or single-cell molecular profiling. Recently, we developed optical pooled screens to make pooled libraries compatible with the rich set of spatially and temporally resolved phenotypes accessible to high-content microscopy by using targeted in situ sequencing to demultiplex genetic perturbations. This is now one of several methods that enable image-based pooled screening in cell lines and tissue. As these approaches are combined with diverse perturbation modalities, multimodal profiling, and machine learning, we expect that image-based pooled screens will serve as a next-generation platform for high-throughput biological discovery and target identification.
Advances in Bioanalytics & Biomarkers
Deep, Unbiased and Quantitative Plasma Protein Biomarker Discovery using Proteograph Suite and Multiplexing Mass Spectrometry
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Open to view video.  |   Closed captions available "Human blood plasma is a widely accessible sample that carries biological information from all organs of the human body and therefore offers unbeatable possibilities for clinical biomarker development. However, the large dynamic range of circulating proteins combined with the diversities of proteoforms present in plasma have limited the comprehensive characterization of the plasma proteome in a high throughput manner. To address such challenges current plasma proteomics workflows combine immunodepletion of high abundance proteins and peptide fractionation prior to mass spectrometry analysis. Recent advancement in sample preparation such as Seer’s ProteographTM Suite coupled with improved mass spectrometry instrument sensitivity and speed, enabling to quantify thousands of proteins from plasma without compromising throughput or reproducibility, creating a unique opportunity to further unlock protein biomarkers for complex diseases. In this presentation we evaluate the performance of state-of-the-art analytical sample preparation methods (immunodepletion vs Proteograph platform) combined with mass spectrometry proteomics using either label-free or multiplexing tandem mass tag (TMT) technology. The presentation will touch upon our insights and lessons learned from a recent study aiming to detect protein biomarkers in COVID-vaccinated individuals.
A New Frontier in Neurodegenerative Disease Diagnostics – Translation of High Throughput Assays for NfL and pTau181 in Blood into Clinical Utility
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Open to view video.  |   Closed captions available "Elevated levels of phosphorylated Tau protein at threonine 181 (pTau181) and neurofilament light chain (NfL) in cerebral spinal fluid (CSF) and blood have been shown to be indicative of neurodegeneration. pTau181 has been identified as a potential marker of Alzheimer’s disease while NfL has demonstrated elevation in a range of neurodegenerative diseases including Alzheimer’s disease, multiple sclerosis, amyotrophic lateral sclerosis, Parkinson’s disease, and Huntington’s disease. In addition, traumatic brain injuries (e.g. concussions) have been shown to cause elevated levels of NfL. Although these analytes have demonstrated promising clinical utility, access to measurements are not readily available to physicians. This is a result of two barriers: the greater burden to acquire CSF samples from patients and the availability of high sensitivity assays that can measure these analytes at the levels they are found in blood. Due to this unmet need in diagnosis of neurodegenerative diseases, Roche Elecsys® immunoassays were validated for measurement of pTau181 and NfL in serum or plasma on the Roche cobas® high throughput clinical analyzer platform. Studies were performed, using guidance from the Clinical and Laboratory Standards Institute (CLSI), to assess assay performance (e.g. imprecision and measurement range) and stability of samples. Paired sample measurements were also made using the new assay as well as existing assays, which were used to demonstrate the clinical utility of pTau181 and NfL measurements. As a strong correlation (R > 0.9) was observed between measurements on each assay, the clinical utility is preserved through the identification of elevated levels of each analyte with the respective Elecsys assays. Through generation of de novo reference intervals for each analyte, the assays are ready for widespread adoption and utilization.
Data automation for pooled and singleton clinical PCR testing using the R ecosystem
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Open to view video.  |   Closed captions available Pooling of virology samples for the purposes of increased analytical throughput presents numerous technical challenges from the perspective of sample tracking and data automation, especially given that there may be multiple instruments in the analytical workflow. We will present our solution for COVID sample pooling throughout the liquid handling, extraction, amplification and filing processes - all based on freely available open-source software. We will also discuss strategies, including machine learning, we employed to divert samples away from pooling when the positivity rate climbed in the fall of 2020. Finally, we will highlight the use of R, RShiny, Shinyproxy, Docker and Docker Swarm for stable, reliable deployment on premises or in cloud for application to a clinical environment. Since go-live in September 2020, the software has, in continuous daily use, permitted the automated resulting (and avoided human transcription) of more than 600,000 result on 250,000 virology specimens and has been extended to cover all virology results from non-interfaced instruments in Providence Health.
Biomarkers: A Roadmap from Bench to Bedside to Business
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Open to view video.  |   Closed captions available Personalized medicine requires the development and deployment of biomarkers to deliver the right treatment to the right patient at the right time. Biomarkers can include imaging, laboratory results, or any other measurable state of a biological condition. Biomarkers provide value in multiple contexts, from aiding drug discovery and development to guiding individual patient care. To develop and execute a sustainable business model for biomarker development, one must navigate diverse regulatory requirements and market dynamics. This presentation will include an overview of potential biomarker use cases including clinical scenarios, regulatory requirements, and potential partners. The goal is to impart several roadmaps to guide biomarker development from discovery to clinical implementation.
Affinity Selection Mass Spectrometry: Hit Validation Tool and a Promising High Throughput Screening Platform for Complex Targets
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Open to view video.  |   Closed captions available "Affinity selection mass spectrometry (ASMS) is a solution-based ligand binding assay that allows rapid screening of new chemical matter against complex targets, without the need for target immobilization or labeling. Unlike conventional HTS techniques, ASMS relies on the sensitivity and selectivity of mass spectrometry to enable multiplexed screening of compound mixtures with few false positives. DNA encoded chemical libraries (DELs) have become an integral platform technology to provide diverse and complementary chemical matter for challenging targets. However, owing to DNA artifacts and the complex nature of DELs, off-DNA synthesis of hits and subsequent validation with appropriate analytical techniques is often required. In this poster we will present the implementation of ASMS as an orthogonal biophysical tool for validation of DEL hits. We have developed robust and sensitive LC-MS/MS methods, using triple quadrupole-based MRM workflows, for analysis of off-DNA hits from our DEL screening campaigns. A single point calibration allows us to mitigate ionization efficiency effects that typically confound MS quantitation, and accurately measure ligand-protein binding with high sensitivity. Examples of the strategic impact of ASMS to hit validation workflows will be highlighted. For ASMS screening studies, two methods were explored (Magnetic beads and plate-based SEC) for isolation of target-ligand complex from solution prior to MS analysis. For magnetic bead workflows using CA II binders and non-binders, a Kingfisher Flex (96-well plate) magnetic particle processing system was used to test and optimize reagents and processes. For plate-based SEC workflows (384 well plate format), critical parameters pertaining to efficient isolation of target-ligand complex were optimized. Compatibility of the magbead and plate-based SEC workflows was also tested using the novel IRMALDESI-MS platform. Good correlation was observed for CA II ligand binding between LC-MS and IRMALDESI, providing an orthogonal and high-throughput alternative for ASMS screening via IRMALDESI. Both protocols were further explored to screen an EGFR target with an FDA plus 2K compound library (approved on marketed drugs). For these experiments compounds were pooled (10 per well) and incubated with 10uM EGFR. For UPLC-HRMS analysis, a ‘fast’ (75 second) method was developed. The LC-MS data was analyzed using MGears (ASMS data analysis brick from Mesternova), and the IRMALDESI ASMS data was analyzed using custom-built software created at AbbVie. Good correlation was obtained between these two approaches highlighting the robustness, flexibility, and ability to interface either method with multiple MS platforms.
Transforming Small Molecule Biomarker Discovery and Translation with Speed, Scale, and Specificity
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Open to view video.  |   Closed captions available "Greater use of small molecule biomarkers in drug development is needed to transform efficiency and success rates, by driving deeper understanding of how non-genetic factors influence biological processes, disease progression, and drug responsiveness. There are tens of thousands of molecules circulating in human blood – thousands of which could represent robust biomarkers – but their discovery has been limited to date by bioanalytical constraints.   In this session, Sapient will discuss how next-generation mass spectrometry-based approaches enable rapid, nontargeted, large-scale small molecule biomarker profiling, measuring >11,000 circulating factors per biosample to identify key molecules of interest, including yet-unmapped chemistries, across thousands of samples at a time. We will discuss how these discoveries are then validated through an integrated discovery pipeline using biocomputational methods, large-scale human datasets, and technologies for targeted profiling, supporting the identification and translation of novel small molecule biomarkers at speed, scale, and with high specificity.
From Digital Biomarkers to Digital Endpoints: The FDA Perspective
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Open to view video.  |   Closed captions available "Digital biomarkers have significant potential to transform device and drug development, but only a few have contributed meaningfully to bring new treatments to market. There are uncertainties in how they will generate quantifiable benefits in clinical trial performance and ultimately to the chances of success. This presentation will provide an overview of the following: 1. The rationale behind developing digital biomarkers and digital endpoints 2. The gaps in evidence requirements 3. An overview of verification and validation frameworks 4. An overview of digital technologies used for remote data collection in clinical trials
Creating Consensus for advancing Digital Health Technologies for Parkinson’s Disease
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Open to view video.  |   Closed captions available Digital health technologies (DHTs) hold promise in identifying and quantifying early signs and symptoms that impact people with Parkinson’s in their daily lives. A rich and promising list of drug candidates is currently in development for the treatment of PD, yet tools are needed to assess the impact of novel drugs in development on slowing disease progression. The “Digital Drug Development Tools” (3DT) workstream of the Critical Path for Parkinson’s consortium (CPP) was established in 2019 to advance the use of digital health technologies in PD clinical trials. 3DT collaborators include industry members, academic experts, clinicians, patient advocacy organizations, regulatory agencies, and people with PD all of whom work pre-competitively to share data, knowledge, and costs to accelerate progress. The members agreed to focus on a case study, Wearable Assessments in the Clinic and Home in Parkinson’s Disease (WATCH-PD) to engage with regulators in unique ways. WATCH-PD is a 12-month multi-center observational study that evaluates multiple digital devices in individuals with early, untreated PD. The study enrolled 82 individuals with PD and 50 control participants without PD. In clinic, participants wore inertial sensors (APDM Mobility Lab), an Apple Watch, and an iPhone while performing motor tasks (e.g., MDS-UPDRS Part III). At home, participants use the Apple Watch and iPhone to complete motor and cognitive tasks every 2 weeks. Participants also complete QoL/ADL questionnaires at each visit. Early and frequent interactions with health authorities are necessary to address all the regulatory challenges in the field of DHTs. 3DT requested a Critical Path Innovation Meeting (CPIM) with the FDA and an Innovations Task Force (ITF) meeting with the EMA to discuss the protocol and design of the WATCH-PD study; an observational longitudinal study of de novo PD patients using DHT to measure both motor and non-motor features of PD. Regulators provided feedback on security issues involving DHT technology use, interoperability of device platforms, the need for transparency of data analytic platforms and algorithms, metadata, sources of variability, engaging patients in DHT trials, and use of normative data. The WATCH-PD study is generating valuable data that promises to lead to new, objective measures and endpoints that could be used in future clinical trials in Parkinson’s disease. CPP’s 3DT effort has made significant progress on the goal of reaching a shared understanding of the open regulatory and scientific issues in the use of digital health technologies as endpoints in PD clinical trials, using the WATCH-PD study as a case example. By seeking regulatory agency feedback on this case study, multiple sponsors have been informed on issues to attend to for optimizing the use of digital health technologies in future clinical trials. Future 3DT strategies are underway to respond to regulatory feedback and achieve success.
Single cell phenotypic analysis of circulating CD4+ and CD8+ T cells reveal predictive biomarkers for clinical response to checkpoint blockade in chronic hepatits B
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Open to view video.  |   Closed captions available Functional cure of chronic HBV infection is defined by a sustained off-treatment loss of HBV surface antigen (HBsAg) and current treatment modalities are designed to elevate HBV-specific immune responses to achieve this objective. To identify biomarkers that may correlate with clinical response to checkpoint blockade in chronic hepatitis B (CHB), we characterized longitudinal peripheral blood mononuclear cell (PBMC) and serum samples collected from subjects that exhibited a clinical response or did not respond to treatment. CHB subjects were treated with a single dose of the PD-1 inhibitor nivolumab with or without the vaccine GS-4774. To determine if immune composition prior to treatment predicted response, we compared immune cell populations in response groups. Flow cytometry and single cell sequencing were used to analyze baseline and on-treatment (4 and 24 weeks following nivolumab treatment) PBMCs from two responding (R1 and R2; characterized by an HBsAg decline of >0.5 log10 IU/ml) and two non-responding (NR1 and NR2) subjects. Subject R1 achieved HBsAg negative status and developed significant anti-HBs titers during treatment. CD8+ T cells from subject R1 had elevated baseline levels of naïve T cells (Tn) and stem-like memory T cells (Tscm) with marked expression of the transcription factors LEF1, TCF7 and CCR7. At on-treatment timepoints, the frequencies of CD8+ Tn and Tscm were reduced and increases in CD8+ effector (Teff) and effector memory (Tem) T cells were detected for subject R1 but not the other participants. Similar results were obtained for CD4+ T cells with a reduction in Tn and increases of Tem and terminally differentiated effector memory T cells. T cell clones also emerged (>30 clones with frequencies < 10) at the week 24 timepoint for subject R1 and mapped to a Teff/Tem phenotype. Amplification of specific B cell clones after-treatment was observed in both responding subjects. A pronounced peripheral baseline CD8+ and CD4+ T cell Tn/Tscm signature and the capacity to transition to a Teff/Tem phenotype may be associated with clinical response to checkpoint blockade in CHB patients. Furthermore, on-treatment expansion of peripheral B and T cell clones could also inform treatment outcome.
Application of pharmacodynamic and patient phenotyping biomarkers to early- stage clinical studies in Parkinson’s Disease patients
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Open to view video.  |   Closed captions available "Neurodegenerative diseases such as Parkinson’s Disease (PD) and Alzheimer’s Disease (AD) represent a large and growing unmet medical need. Progress in treating these diseases requires development of biomarkers to quantify target and pathway engagement to inform dose selection and derisk long term dosing studies, as well as patient selection biomarkers to appropriately match the patients to the right therapeutic mechanism of action. Variants in leucine-rich repeat kinase 2 (LRRK2) are one of the most common genetic risk factors in PD, and many pathogenic coding variants in LRRK2, including the most common LRRK2 pathogenic variant, G2019S, have increased kinase activity. LRRK2 inhibition has long been an attractive therapeutic approach in both PD associated with LRRK2 genetic variants and sporadic PD. We will present case studies of biomarker implementation in the clinical and preclinical setting for Parkinson’s Disease that illustrate the successes and challenges of biomarker development in neurodegenerative disease therapeutics. We recently completed Phase 1 healthy volunteer (HV) and Phase 1b PD patient studies with a small molecule inhibitor of LRRK2, BIIB122 (DNL151). Pharmacodynamic analysis showed a robust biomarker response in both HVs and PD patients at doses that were generally well-tolerated. These findings support continued investigation of LRRK2 inhibition with BIIB122 for the treatment of PD. Many approaches are being taken to molecularly phenotype PD patients, both to understand the dysfunctions underlying PD and identify patient subgroups that are biochemically defined that could respond to different treatment approaches. We will present our progress on one such approach, a metabolomic characterization of plasma samples from the Parkinson Progression Markers Initiative (PPMI) in which 298 metabolites were measured by liquid chromatography coupled to mass spectrometry in 629 participants selected based on PD diagnosis and genetic status. Pharmacodynamic analysis in our Phase 1 and Phase 1b clinical studies successfully demonstrated target and pathway engagement and supported further development of LRRK2 inhibitors for PD. We and others in the field are applying diverse experimental strategies to the development of patient selection, stratification, and treatment response biomarkers.
Circulating miRNAs as biomarkers for testicular injury in rat preclinical studies: past, present & future
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Open to view video.  |   Closed captions available The first nonclinical biomarkers were qualified by the FDA in 2008, supporting voluntary use in Good Laboratory Practice (GLP) studies to detect compound-induced nephrotoxicity in rats. Conversely, there remains a lack of peripheral biomarkers for compound-induced testicular toxicity, leaving immense potential to improve related discovery compound attrition. A testis safety biomarker must ideally identify toxicity, evaluate progression, and reversibility of compound-induced injury across species. Selected blood-based biomarkers (e.g., Inhibin B) have been used for diagnosis of testicular toxicity in humans and monkeys, but these parameters provide limited utility in rodent toxicity studies. Characterization of hormones and semen analysis to determine sperm concentration, motility, and morphology can be performed but these parameters are relatively insensitive and display wide animal-to-animal variability. More recently, circulating MicroRNAs (miRNAs) have been used to detect damage to testis in both humans and animals. The goals of this presentation are 1) to highlight past, present, and future applications of circulating miRNAs, 2) to summarize salient findings of peer-reviewed literature on human and animal model testis miRNA atlases, and 3) to describe adverse outcome pathways (AOPs) as a tool to support the utilization of miRNAs, when monitoring for compound-induced testicular toxicity. Additionally, case examples of time dependent miRNA expression level changes associated with compound-induced testicular injury will be described. Collectively, this information provides a compelling weight of evidence for the use of circulating miRNAs as safety biomarkers of testicular injury in rat preclinical studies.
Cellular Technologies
A new Barrier-on-Chip system based on the SBS format for improved drug development
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Open to view video.  |   Closed captions available Organs-on-chip is a new technology able to replicate the smallest functional units of organs to better model human physiology in vitro. When it comes to recapitulating different organ barriers, with their sophisticated and dynamic microenvironment and cellular complexity, there are multiple challenges. Aside the advanced biology, there are challenges in terms of integrating such new technology into existing laboratory workflows including handling and read-outs. Using the AXBarrier-on-chip system allows to recreate the dynamic microenvironment of different organ barriers like lung, gut, etc. This is done by integrating key aspects of the barrier microenvironment: dynamic motion, ultra-thin, porous, elastic, and soft cell culture membrane. The AX12, the consumable used to create the barriers-on-chip, allows easy cell seeding and read-out possibilities while having an SBS footprint for simple integration into existing workflows. Further, the unique chip design read-outs to be tailored for accurate in vitro to in vivo translation: use of Trans barrier Electrical Resistance (TER) and permeability assays to assess e.g. lung edema, vascular leak, and virus or bacterial-induced barrier disruption. Perform ELISA/proteomics, using the up-concentrated supernatant, to assimilate secreted biomarkers or immune-mediated cytokine storm. Conduct Single-cell transcriptomics to estimate accuracy with in vivo populations. Use automated real-time and high-resolution imaging to visualize and better understand the dynamic biological process. Supported by the unique design, the simple workflow integration, and the different read-outs possibilities, the new AXBarrier-on-chip system facilitates an improved drug development process. Our data in the field of assessing the safety and efficacy of new drug candidates support the potential of this new barrier-on-chip system to better assist decision-making and speed up the drug development pipeline while minimizing the need for animal testing.
Innovative imaging and tissue culture platforms allow true laboratory automation in experiment, image and data acquisition and analysis.
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Open to view video.  |   Closed captions available Modern research approaches become more complex and allow higher throughput with every commercialized innovation. Classic tissue culture is being replaced with more complex 3-dimensional tissue models, perfusable, highly accessible and transparent for convenient imaging. Labelling and detection of colors has become more streamlined with many new fluorophores, stronger excitation, labelled antibodies and better detection limits of faster cameras. However, high-quality high content imaging as study read-out still is often work- and time intensive, manual labor with automated imaging systems being rare or cost-intensive. To date, classic imaging processes present a substantial bottleneck for efficient research.Automated imaging systems, ideally paired with automated tissue culture and liquid handling would be the optimal platform for future preclinical research, drug discovery and drug development. Moving to that direction, modern automation of tissue culture and image analysis offer substantial improvements for throughput and analysis quality. Comprehensive imaging software uses built-in protocols for assays such as Live/Dead, cell motility and proliferation, cell count, intensity analysis and wound healing, but still allows fur custom assay development. The creation of pre-programmed "JOBs" in NIS-Elements image analysis software allows for automated image acquisition and analysis, all in the same routine. Implementation of analysis routines that include AI capabilities allow the software to make intelligent decisions with regard to, for example, detecting rare events such as detection and analysis of localized patches on cell membrane, keeping live bacteria in the field of view using motorized stages, automated screening technology to image 100s of fish per experiment and much more. Lastly, automated analysis Tools such as signal tracking, 2D/ 3D measurements, use of masks and segmentation to analyze structures, puncta, growth and movements, all contribute to highly efficient image acquisition and analysis with minimal manual efforts and substantial time savings. In parallel, modern tissue culture technologies have come a long way from petri dishes. They now include more complex tissue architecture with 3-dimensional collagen scaffolds, polarized cells with basolateral and apical sides grown at collagen-fluid interfaces, and perfusable channels creating physiological shear forces. Moreover, they function mostly autonomously once set up, with minimal needs for manipulation during the culture periods, all the way to the endpoint and data acquisition. By design, they allow for readouts stretching from basic toxicology and viability assays, visualization of marker expression patterns, to barrier studies and more complex PK/PD analysis, including collection and read-out of effluent and supernatant, all in one automated process.Connecting these modern tissue culture approaches with Nikon's innovative image acquisition and analysis software platform completes the outline of future, automated laboratories.
Automated platform to generate iPSC-pancreatic organoids for population-scale modeling of type 2 diabetes
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Open to view video.  |   Closed captions available Type 2 diabetes (T2D) is a genetically complex disease that requires analyzing large cohorts of patient-derived cells to establish defined disease phenotypes. Although progress has been made towards large-scale production of pancreatic beta cells, current protocols for beta cell production use spinner flasks, which are not amenable to population-scale disease modeling. We leveraged the NYSCF Global Stem Cell Array(R), our automated platform for iPSC derivation, to develop a fully automated, high-throughput platform for the directed differentiation of human pluripotent stem cells into pancreatic organoids that include functional beta cells and other hormonal cells. This approach improves the molecular maturity of differentiated tissues, yielding higher expression of canonical markers than the manual approach throughout the differentiation (PDX1+/NKX6+ at progenitor stage, ratio of INS+/GCG+ after maturation stage). We also leveraged automated procedures for assessing 2D culture morphology and organoid dimension to enable careful monitoring of iPSC differentiation into pancreatic organoids. Moreover, we implemented automated flow cytometry analysis to evaluate developmental marker expression profiling at every stage of the differentiation. The uniformity facilitated by our automated platform is illustrated by immunofluorescence analysis, which reveals a homogeneous population of beta cells forming organoids across a genetically diverse cohort. Finally, we demonstrated organoid functionality: Glucose-Stimulated Insulin Secretion (GSIS) assays showed consistent fold induction across our cohort. Taken together, these results establish that our automated platform for the derivation of functional pancreatic beta-cell organoids is optimized for detecting diverse phenotypes in population-scale disease modeling of diabetes. This sets the stage for cohort-scale, precision drug screening applications.
Microfluidic control technologies for massively parallel robot scientists driven by artificial intelligence and machine learning for automated systems biology and biotech process optimization in microbial and mammalian cells
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Open to view video.  |   Closed captions available Automated high-throughput screening technologies, optimized for simple “seed-expose-read” drug discovery workflows, require infrequent fluidic access to each well of a multiwell plate. Long-term, batch-fed well-plate cultures require regular media replacement and must be repeatedly removed from incubators. While multi-pipette-based fluid handling is the mainstay of these approaches, such intermittent feeding is unsuitable for chemostats, organ chips, and other perfused microbioreactors requiring nearly continuous media delivery and proportional removal. Just as intra-incubator imaging has demonstrated the value of not removing well plates for imaging, we have shown how microfluidic, 24- and 96-well MicroFormulator systems can use time-division multiplexing (TDM) to provide continuous control of media composition and hence different pharmacokinetic profiles for each well in a well plate, entirely within an incubator (Singh, 2022, We have now extended our technologies to create more complex systems that support uninterrupted, long-term perfusion of multiwell chemostats and multiple perfused microbioreactors. In contrast to the adherent cells grown in our 24- and 96-well MicroFormulators, microbial cells grow sufficiently quickly that TDM formulation of the milliliter volumes in our yeast microchemostats is impractical, so our 12-well microchemostats utilize pairs of intermediate reservoirs that are either being filled by an input TDM MicroFormulator or emptied and delivered without interruption to downstream wells or microbioreactors by a pair of our 12-channel spiral microfluidic peristaltic pumps. Culturing suspended yeast or CHO cells to high density utilizes active stirring of each well by 12 independent motors driving magnetic stir bars. A 12-channel output pump withdraws cells and media from each well through an autocalibrating multichannel optical density detector and deposits the samples into individual wells for off-line analysis. A second 12-channel output pump connected to our multiport sensor valves allows off-line, serial sample extraction from one well while effluent from others is sent to respective downstream destinations. The microprocessor-controlled stepper motors that drive each pump and valve are coordinated by an integrated software system that can receive instructions from artificial intelligence/machine learning software that enables the entire system to operate as a robot scientist (Coutant, 2019, The current architecture is being expanded from 12 to 48 wells by creating pumps and valves with higher channel counts. Our demonstrated ability to continuously formulate, deliver, remove, and analyze media at flow rates of 1 to 100 microliters/minute from each of dozens of wells represents a major advance in cell-culture fluid handling. While currently being developed for yeast chemostats and CHO cell bioreactors, our technology is ideally suited for supporting dozens of organ-chip bioreactors that utilize fluid height differences between input and output reservoirs to drive gravity perfusion. Our multichannel pumps and valves maintain required height differences, deliver drugs, and remove samples without introducing bubbles into sensitive microfluidic organ chips.
High-Throughput, Microfluidic Tissue Models for High-Fidelity Therapeutic Efficacy, Metabolic, Biomarker, and Toxicity Screening
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Open to view video.  |   Closed captions available Organ-on-chip technologies continue to advance rapidly, spurred by the need for higher fidelity platforms more representative of human in vivo responses, and for reductions in cost and in reliance on animal models for preclinical drug development. Keys to further progress include successful demonstration of clinical validation for high priority disease areas, development of higher throughput systems, compatibility with pharmaceutical workflows and robust and manufacturable materials and processes. To this practical end, Draper has developed several tunable flavors of a multiplexed microfluidic-based tissue platform (PREDICT96) that incorporates 96 independent human and animal primary-based cells and tissues per plate with integrated dynamic fluid flow and real-time biological sensing. Several high impact applications related to drug discovery and efficacy testing, biomarker discovery, and toxicity testing will be overviewed within gastrointestinal, upper/lower airway, kidney, vascular, and oral mucosa tissue contexts. Among these principal applications discussed will be an air-liquid-interface (PREDICT96-ALI) system directed toward modeling clinically-relevant SARS-CoV-2 infection with successful implementation in a high containment BSL-3 laboratory, a proximal tubule model capable of granularly tracking real-time drug-induced shifts in metabolism and toxicity, a vascular model enabling high fluid shear to the endothelium for drug toxicity testing and clinically validated biomarker discovery, and complex biopsy-derived gastrointestinal culture These and other applications demonstrate the potential power of precision microfluidics-based, standardized, sensing-integrated, and good-throughput culture platforms for rapid deployment in the drug development and discovery process.
Tmod cell therapy with NOT-gate Boolean logic distinguishes tumor from normal cells in autologous and allogeneic treatment
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Open to view video.  |   Closed captions available On-target/off-tumor toxicity has been one of the challenges for adoptive cell therapy against solid tumors. Loss of heterozygosity (LOH) is commonly observed in many solid tumor types. To exploit such irreversible genetic difference between tumor and normal cells, we have developed a cell therapy that utilizes a combination of tumor-specific target and HLA deletion to focus cytotoxicity on cancer cells. The engineered T cells contain a dual-receptor system (Tmod): (i) an activating CAR that binds tumor-specific targets and (ii) an inhibitory LIR-1 based receptor (blocker) that binds HLA-A*02. Tmod cells have comparable potency to CAR-T cells but have striking selectivity for A*02(-) tumor over A*02(+) normal cells in vitro and in vivo. Examples of Tmod therapies with successful preclinical results for autologous and allogeneic treatment will be discussed. For instance, carcinoembryonic antigen (CEA)-targeting immunotherapies have caused severe toxicity in clinical trials due to its expression on normal cells even though it is an attractive tumor-associated antigen with overexpression in a variety of solid tumor types, including cancers of the lung, colon, and pancreas. To overcome this hurdle, we developed CEA Tmod by pairing a CEA-specific CAR (activator) with an HLA-A*02-specific blocker. CEA Tmod cells are designed to kill tumor cells with LOH at the HLA-A*02 locus while protecting normal cells. In addition, the blocker module is able to block the activation of endogenous TCRs triggered by HLA mismatches, which can be utilized to control graft-versus-host disease (GvHD) for allogeneic cell therapy. To further develop the system into an off-the-shelf therapy, HLA expression in the adopted Tmod cells is knocked down by a B2M-targeting shRNA to minimize rejection by the host T cells. Preclinical data for Tmod cells will be discussed which illustrate their advantages in differentiating tumor vs. normal target cells and their potential for both autologous and allogeneic treatment in the future.
Primer on the Biology of γδ T Cells and Their Uses to Treat Cancer
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Open to view video.  |   Closed captions available Targeting T cells to recognize and kill cancer cells using T cell redirecting bispecific antibodies or chimeric antigen receptor (CAR) T cells has been a highly effective approach to treating hematological cancers. However, challenges, such as target antigen loss, treatment-related toxicities, and poor efficacy in treating solid tumors, remain. One strategy to address these challenges is to target γδ T cells and harness their intrinsic antitumor activities. γδ T cells, which are defined by the expression of the T cell receptor (TCR)γδ heterodimer in their TCR complex, have established roles in tumor surveillance and immunity. In fact, tumor infiltrating γδ T cells are the most significant, favorable, prognostic immune cell population across multiple hematological and solid tumors. γδ T cells, via co-expression of TCR and natural killer cell receptors, monitor and maintain tissue integrity through recognition and destruction of stressed, infected, and transformed cells. Importantly, their ability to recognize and kill tumors cells using a range of activating receptors may act to limit tumor escape. Here, we discuss why γδ T cells are an attractive candidate for cancer immunotherapy, focusing on their unique biology and how this biology can be leveraged to produce novel therapeutic products. In addition, we present an overview of the current landscape of the γδ T cell-based products that are currently being evaluated in clinical trials.
New frontiers for drug development in cell therapies
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Open to view video.  |   Closed captions available The success of chimeric antigen T (CAR-T) cells in heme malignancies has led to a significant investment in CAR-T cells and cell platforms beyond CAR-T paving the way for an immense innovation and drug development opportunities. This session will: 1) review the current state of the cell therapy field, 2) introduce principles which differentiate aspects of cell therapy development from other therapeutic modalities, and 3) highlight new frontiers in cell therapies and its molecular engineering. Specifically, this presentation will highlight advances in the innate and adaptive cell therapy platforms, beyond CAR-T, as well as discuss the implications for novel disease treatment and patient outcomes for this novel but promising modality. Although there are several challenges which are being actively investigated, the cell therapy field is at the leading edge of innovation to leverage cells as a product in drug development.
Adapting to the science—automation solutions for discovery research in a growing CAR-T company
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Open to view video.  |   Closed captions available Conventional small molecule drug discovery process has benefitted tremendously from automation by enabling defined, standardized, and scalable workflows such as sample management, reagent preparation, and high-throughput screening. For discovery of new cell-based therapies, synergies attained through automation is not so readily apparent. Much of the process involves molecular and cellular engineering with multiple components and cell types. For instance, the process to design our dual-receptor T cell therapeutic (TmodTM) candidate, which comprises separate molecules to regulate activation and inhibition, starts with construct identification, binder cloning, screening, and transfection, prior to functional assessment. Although we house a library of constructs, the selection process is usually focused and idiosyncratic with emphasis on the finer details of potency/selectivity of the engineered effector cells. Implementing automation in this setting can be challenging as progress is not necessarily limited by sample quantity but rather by variables in experimental inputs. Therefore, we must justify overhead in automation over manual workflows and potential tradeoffs in flexibility. We will present how we address these challenges in sample management, molecular cloning, cell line generation, and high-content functional assays to harness the power of automation for better sample integrity, data quality, and experiment throughput.
Engineering next generation organoids for biomedical research and drug development
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Open to view video.  |   Closed captions available Three-dimensional organoids derived from human induced pluripotent stem cell (iPSC) hold great promise to improve understanding of human biology and disease, transform drug development, drive precision medicine, and ultimately, develop transplantation-based therapies for end-stage diseases. Their ability to recapitulate facets of normal human development during in vitro morphogenesis produces tissue structures that re-create the architecture and physiology of human organs in remarkable detail. Despite considerable success in establishment of organoids representing wide range of organs in a dish, challenges remain to realize their full potential and to achieve real-life applications. Current organoid derivation protocols, while useful for many applications, have relevant technical and conceptual limitations. Oftentimes they rely on the stochastic nature of in vitro self-organization and cell fate choices resulting in high line-to-line, batch-to-batch and well-to-well variability hampering the translatability of organoid systems. Moreover, the reductionist approach of organoid culture limits the full potential of this method as organoids lack more complex interactions with non-parenchymal cells such as immune cells, stroma and mechanical forces that are present in the native tissue microenvironment. At the Center for Stem Cell and Organoid Medicine (CuSTOM) at Cincinnati Children’s Hospital Medical Center (CCHMC) we have engineered next generation organoids with cellular complexity, mechano-physiological parameters and higher-order functions similar to native tissues (e.g. innervated intestinal organoids experiencing peristaltic contractions), as well connectivity with other organs (e.g. hepato-biliary-pancreatic multi-organoid system). In addition, we have implemented workcell automation and high content imaging solutions to fulfill a need to standardize experimental techniques, provide scalability, improve robustness of organoid protocols, and allow in situ characterization of the manufactured cell products. The resulting fully automated, HTS-compatible organoid-based platforms can be used to evaluate drug effects at single organoid level via high content imaging and 3D analysis as well as multiplexed assessment of soluble biomarkers indicative of organoid health and function. All together, these new advancements bring us one step closer to realize the full potential of organoids in drug development, personalized and regenerative medicine.
A Model Of Human Neuroinflammation Utilizing Induced Pluripotent Stem Cell-Derived Neural Organoids Incorporating Microglia
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Open to view video.  |   Closed captions available Neuroinflammation is a complex response to brain injury and disorders involving activation of the innate immune response, release of inflammatory mediators, and the generation of reactive species resulting in downstream effects including vascular compromise, oxidative stress, and neurotoxicity. Neuroinflammation is a critical component in the etiology and progression of many diseases including neurodegenerative diseases such as Alzheimer’s disease (AD), stroke, trauma, seizures, neuropsychiatric disorders, and brain cancers. There is an urgent need to develop advanced neural microphysiological systems (MPS) that can model human neuroinflammation and bridge the gap between simplistic cell models and clinical data. Stem Pharm has leveraged its proprietary synthetic hydrogel matrix to enable the formation of complex, highly reproducible induced pluripotent stem cell (iPSC)-derived neural organoids containing microglia and vascular cells. These organoids are well-suited to study neural inflammation in a physiologically relevant context. The neural organoids are formed in 96-well plates from iPSC-derived neural precursor cells, microglia, endothelial cells, and mesenchymal stem cells and are ready for screening as soon as 21 days after initial plating. Single cell transcriptional analysis demonstrates that the organoids are cell-type diverse, containing multiple neuronal subtypes, astrocytes, microglia, and endothelial cells. Bulk and single cell RNA-seq analysis demonstrates high intraclass correlation and low coefficients of variation between biological replicates. Incorporated microglia tile uniformly throughout the organoids, display ramified morphology resembling in vivo morphology, and demonstrate a gene expression signature that strongly correlates with human in vivo microglia expression. The microglia in the neural organoids retain physiologic immune responses to inflammatory stimuli. Modulation of microglia within the organoids to pro- and anti-inflammatory phenotypes was validated through stimulation with lipopolysaccharides (LPS), interferon gamma, TGFβ & IL-10, or IL-4 & IL-13, amyloid beta (Aβ) oligomers and incorporation of patient-derived glioblastoma cells. When stimulated with Aβ oligomers, the neural organoids elicit a microglial-dependent inflammatory response. Specifically, Aβ drove significant inflammatory transcriptional responses in TNFα, IL1α and CHI3L1. CHI3L1 has been shown to be an upregulated gene in AD patient microglia and elevated in AD patient cerebrospinal fluid. This demonstrates a clear difference between Stem Pharm’s neural organoids and mouse models of AD, where CHI3L1 is primarily expressed in rodent astrocytes. These data demonstrate that the neural organoids have microglial-dependent and independent immune responses to inflammatory stimuli and, importantly, that the microglia maintain their immune surveillance functions when integrated into the organoids. Thus, Stem Pharm’s neural organoid can model features of human AD not observed in rodent models. These data suggest that Stem Pharm’s neural organoids can be a useful tool for studying disease-associated inflammatory changes in vitro and highlight their promising application to facilitate translation between pre-clinical and clinical development in the active area of neuroinflammation.
A novel approach for label-free drug efficacy analyses of pancreatic cancer organoids using high-content imaging
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Open to view video.  |   Closed captions available Cancer remains one of the leading causes of death in the 21st century. Despite the latest advances in oncology, most cancer patients lack tailored therapeutic approaches with lasting benefit.Measuring the impact of anticancer compounds and their combinations is only possible on ex vivo assays. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient models for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. However, the translation of organoids in screening applications has so far been hampered by the lack of homogeneity and difficult handling and automatability. Moreover, they are randomly distributed across the culture which complicates subsequent readouts and images analyses.To overcome these challenges, we set up a screening workflow on PDOs using Gri3D, a ready-to-use platform for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a microwell array patterned in a cell repellent hydrogel. On Gri3D, organoids are robustly generated in the microwells and are located in the same imaging plane. This greatly facilitates quantitative analyses in high content image-based screens. Furthermore, the pipetting port enables automation of cell seeding, media exchange and compound incubation with liquid-handlers, thus increasing assay reproducibility.In the presented work, we exposed human pancreatic cancer PDOs to a panel of anti-cancer compounds at different doses and followed their response to the drugs with single-plane brightfield images on an ImageXpressGri3D Micro Confocal. Using an AI-based approach (IN Carta), we efficiently detected each single organoid and extracted phenotypic features which correlate with cytotoxicity. We further validated the approach by comparing the obtained results to traditional multi-plane fluorescence-based Live/Dead assay.The data demonstrate a new approach for label-free drug efficacy analyses on organoids by combining high-density microcavity arrays and a high content imaging system together with machine-learning algorithms. The assay does not require incubation with any dye and requires less time and less data storage as well as less phototoxicity than traditional Live/Dead assay. Moreover, it can be performed in an automatable high-throughput fashion.
Data Science and AI
The Path from Research to Medical Device - Commercializing AI in Medical Imaging
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Open to view video.  |   Closed captions available One of the goals of developing medical technology in a research environment is to create something that can be used to directly improve patient outcomes - but bringing a medical device to market and enabling widespread clinical use is an immensely challenging and complex process that includes science, technology, business and regulatory efforts.This presentation will walk through the story of the development of TRAQinform IQ by AIQ Solutions, a medical device startup with headquarters in Madison Wisconsin. TRAQinform IQ is a cloud-based software medical device that uses AI and advanced analytics to assist oncologists in optimizing treatment for patients with complex diseases such as metastatic cancer. The presentation will discuss the process of obtaining FDA and international regulatory clearance for clinical use, including methods for training, validating and incorporating AI models into the product, and will describe how AIQ Solutions built a high-performing cross-functional team to efficiently and quickly deliver new models and applications worldwide.
Piximi: an in-browser tool for easy deep learning
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Open to view video.  |   Closed captions available Creation of machine learning networks for biological imaging tasks often suffers from a crucial gap: the subject matter experts who understand the images well are not typically computationally comfortable training neural networks, and lack simple ways getting started to do so. We therefore present here Piximi (, a free, open-source "Images To Discovery" web app designed to make it easy to train and deploy neural networks directly in the web browser, meaning users face no installation hurdles and can access web accessibility features such as in-browser translation. Piximi allows users to upload 8-bit or 16-bit images that use common image formats such as png and tiff; it supports arbitrary channel numbers as well as arbitrary numbers of Z planes. Uploaded images can be saved to a json-backed project file, allowing for multi-session use and encouraging reproducibility/sharing. All images uploaded stay local on the user's machine, and training happens inside the browser; no data is transmitted to a central server. Due to this architecture, Piximi can even be run offline from a locally hosted Docker container.Once loaded into Piximi, images can be classified into any number of categories the user wants; Piximi additionally allows users to train based on a small subset of their data and then predict on a larger number of unclassified images, simplifying the identification of difficult-to-classify images and allowing their subsequent addition to the training set for future training runs. Hyperparameters can be tuned in a simple interface but are hidden by default, making it easy for less computationally comfortable users to get started using Piximi. Piximi classification can be run on any device with a web browser, including mobile devices often unsupported by scientific software. Models trained by Piximi can then be exported and run on any other device/context that uses Tensorflow, meaning networks trained in-browser on smaller subsets of data can then be applied to arbitrarily large data sets that would not be appropriate for the browser. Piximi also allows users to train segmentation models for object(s) of their choosing. Piximi contains an in-app annotation tool which supports both arbitrary channels and Z planes - lookup tables and brightness can be easily adjusted and the settings transferred from one image to the rest of the image set. Piximi contains 9 annotation tools, from simple bounding boxes to sophisticated color annotation. Annotations can then be used in Piximi to train segmentation networks or exported in one of several common formats for training in other applications, meaning Piximi can also serve as a stand-alone annotation tool.In summary, we believe this tool will thus help close the gap between scientists who want to use neural networks, and those who can, accelerating bioimage-based science in many domains.
Our Journey to Innovate in a Risk Averse Industry
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Open to view video.  |   Closed captions available In 2018, our company recognized the need to seek growth opportunities for both top and bottom-line results. Knowing that profitable growth comes from innovative technologies and differentiation, we sought innovative technologies that could leverage our deep experience in pharmaceutical contamination control and environmental monitoring. Along the way, we learned about a novel technology developed by the University of Colorado Boulder and Ursa Analytics. Using deep machine learning and computational statistics, this solution analyses images of subvisible particles and protein aggregates captured from various imaging modalities and delivers quantitative data to inform formulation development and manufacturing of biologic drugs. We recognized this technology would bridge a significant technology gap in the currently approved method for testing drugs prior to lot release. Regulatory agencies require successful testing using light obscuration (LO) for all injectable drugs prior to shipment. Our team has ~50 years of combined experience in manufacture, service, and application support for LO instrumentation. As a result, we are uniquely qualified to bring this innovative technology to market. This talk focuses on our ongoing David vs. Goliath mission to innovate in a risk averse industry. We will discuss challenges ranging from funding to leaving our LO and hardware focused history behind and to become “software people” who understand deep machine learning, subvisible particles and protein aggregation.
Integrating Data Sciences Into All of R&D
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Open to view video.  |   Closed captions available Research and Development has gotten more complicated and at times more siloed due to needed specialization.  The world can not do adequate science without the right culture, technology, data and some art.  Data sciences has the ability to severely augment new discoveries and progress.  When done right data sciences isn't a band-aid but a force to be reckoned with.  This talk will outline how to structure an IT and Informatics approach that leverages data sciences for all of R&D.
How not to break the bank: lessons learned on integrating 100s of Terabytes of data for ML/AI and massive analytics for 10 major biopharmas
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Open to view video.  |   Closed captions available In this presentation, we’ll discuss the current modus operandi for data analysis teams with the frequent caveats of: the cost of generation of data should be the greatest cost, just collect the data and we’ll figure the rest out later, re-using data is a great idea but we don’t know how. Examples of how to implement comprehensive strategies for data analysis from multi-omics to wearables that enable customers to implement FAIR data management systems, deliver ease of use and maximize the return on investment will be presented.
How leveraging internal applications can make automation faster and easier to scale
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Open to view video.  |   Closed captions available At Moderna, we have more than 40 Hamilton liquid handlers and a team of 5 automation engineers who are programming them. Most of these robots have different configurations and deck layouts. As we grow automation internally, we want to make it easier to scale as we are expanding fast. We worked with our internal software engineering team to come up with a way where we can run a single method on all 40 instruments independent of their deck configuration and the instruments attached to it, and without any automation engineer intervention.With their help, we improved the following ways to make it scalable. The same method can run with different tip configurations, such as stacked vs non-stacked. We were able to implement auto-recovery, so that if a method aborts mid-run for any reason, then it can start from where it left-off without any intervention.We also improved log parsing and error logging which can help us solve problems in the method and on the machine. With all this internal data we now can visualize it on Tableau and make smarter decisions such as what machine to use more of and log when and which method is erroring more frequently. The next step of evaluation is to create an AI model where it can predict the run time of methods based on different parameters.With all these great features we are in a place where we can scale our automation to the next level. We can release methods faster and track their progress and all of this is possible with the help of our internal LIIMS and the great team effort of our software engineers.
Tackling the JUMP CP dataset: best practices in data analysis to navigate high content multiparametric data.
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Open to view video.  |   Closed captions available "There is a growing interest in adopting image-based phenotypic profiling for target and drug discovery processes. Such high content approaches yield rich phenotypic data that can reveal critical holistic insights into mechanisms of candidate drug action and toxicity. Much of the growth has been driven by the use of Cell Painting, a standardized high-content profiling method originally developed at the Broad Institute. The method has been adopted so widely that the JUMP (Joint Undertaking in Morphological Profiling) Cell Painting (CP) consortium has been established to generate a large public reference Cell Painting dataset, aiming to create a new data-driven approach to drug discovery. This high-content imaging dataset (~3 million images, ~75 million single cells, 5000+ features) has been generated using ~140,000 different genetic and small molecule perturbations. The JUMP-CP dataset has the potential to be an outstanding resource for drug discovery. However, the size and complexity of the dataset make it challenging for users outside of the initial consortium to leverage it for their research. As the consortium started to incrementally release the data end of last year, we will present our findings in accessing and analyzing the JUMP-CP data, and demonstrate a robust and iterative data analytics workflow for the evaluation of this phenotypic dataset. Specifically, we will cover the basics of detecting redundant data, quality control, data pre-processing, and, finally, determining phenotypic profiles and grouping samples accordingly. We will demonstrate how this enabled us to unravel underlying biological processes. Furthermore, we will touch upon some other challenges researchers face in taking full advantage of this resource - such as computational power - and show how we were able to overcome them using cloud computing. Taken together, we show the importance and feasibility of a robust cloud-based analytics workflow, which will help make this unprecedented resource more accessible to researchers outside of the consortium.
GEARS: Predicting transcriptional outcomes of novel multi-gene perturbations
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Open to view video.  |   Closed captions available "Cellular response to genetic perturbation is central to numerous biomedical applications from identifying genetic interactions involved in cancer to methods for regenerative medicine. However, the combinatorial explosion in the number of possible multi-gene perturbations severely limits experimental interrogation. Here, we present GEARS, a method that can predict transcriptional response to both single and multi-gene perturbations using single-cell RNA-sequencing data from perturbational screens. GEARS is uniquely able to predict outcomes of perturbing combinations consisting of novel genes that were never experimentally perturbed by leveraging geometric deep learning and a knowledge graph of gene-gene relationships. GEARS has higher precision than existing approaches in predicting five distinct genetic interaction subtypes and can identify the strongest interactions more than twice as well as prior approaches. As CRISPR-based screens become ubiquitous for discovering drug targets, GEARS is uniquely positioned to exponentially multiply the information gained from these screens and also guide the design of experiments."
A Review of Unique Data Science use cases within the Clinical Research Environment
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Open to view video.  |   Closed captions available This presentation will review several data science use cases from within the Clinical Research space.
Which will move data science further and faster, technology or culture?
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Open to view video.  |   Closed captions available It's been said that data is the new oil -- the world's most valuable commodity. As such, data have been commoditized and access to data is restricted. Yet for health care data about people, the real owners of the data are rarely the ones gaining direct benefit from its value. Systems have been developed to give patients more control over their own data, while at the same time more and more legal regulations on data sharing are being put in place. It is an open question about how much of their healthcare data most people want to share and how well they understand the potential benefits and risks of sharing and the complexities of the consenting process. Navigating this system and gaining access to crucial data is challenging even for data professionals. Poor access to data creates one of the biggest bottlenecks to advancing treatments for diseases. There are both technological and cultural solutions this problem, but how much of a difference will they make, and will change come fast enough? This presentation will summarize the current state of patient level data sharing and critically examine potential solutions. Audience participation is welcome!
Accelerating drug discovery with deep learning imputation: supporting better decisions with limited data
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Open to view video.  |   Closed captions available "The full value of an organization’s data is realized through the insights and decisions it informs. Drug discovery data is typically sparse (often >95% unmeasured) and uncertain, making it challenging to make data-based decisions with confidence. We miss opportunities because there are insufficient data on which to base decisions, or we are led astray by artefacts and anomalies. Deep learning imputation fills in the gaps in a discovery organization’s database with high-quality predictions, providing a rich matrix of data to guide projects’ progression. Illustrated by three collaborations from biotech, fragrances and agrochemicals, we will discuss the value this brings to support decision-making, ultimately reducing the time and cost of discovery cycles. These values include: 1. Accurate prediction of complex endpoints, even where traditional machine-learning approaches fail 2. Highlighting interesting, high-value results, such as activity cliffs, for further exploration 3. Planning experiments to increase return on investments in expensive downstream assays
Dynamic CD8+ T cell responses to cancer immunotherapy in human regional lymph nodes are disrupted by metastasis
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Open to view video.  |   Closed captions available CD8+ T cell responses are critical for anti-tumor immunity. While extensively profiled in the tumor microenvironment (TME), recent studies in mice identified responses in lymph nodes (LN) as essential; however, the role of LN in human cancer patients remains unknown. We examined CD8+ T cells in human head and neck squamous cell carcinomas, regional LN, and blood using mass cytometry, single-cell genomics, and multiplexed ion beam imaging. We identified progenitor exhausted CD8+ T cells (Tpex) that were abundant in uninvolved LN and clonally related to terminally exhausted cells in the TME. After anti-PD-L1 immunotherapy, Tpex in uninvolved LN reduced in frequency but localized near dendritic cells and proliferating intermediate-exhausted CD8+ T cells (Tex-int), consistent with activation and differentiation. LN responses coincided with increased circulating Tex-int. In metastatic LN, these response hallmarks were impaired by immunosuppressive cellular niches. Our results identify important roles for LN in anti-tumor immune responses in humans.
Profiling states of the human immune system in disease using single-cell omic methods
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Open to view video.  |   Closed captions available The advent of high-dimensional single-cell technologies, including mass cytometry (CyTOF) and single-cell sequencing (scRNAseq, CITEseq), has enabled the study of the complex and dynamic cell types of the immune system from acquired patient samples. These tools have been applied to the study of a variety of diseases and can be used to improve our understanding of treatment responses, disease severity, and outcomes. Here I will review how we've applied these approaches to study patients hospitalized with COVID-19 at UCSF hospitals. We have created a curated database of multi-omic data acquired from patients that enables the sharing and analysis of these complex datasets. I will present one application, in which we used this data to study the compartment-specific effect of dexamethasone on patients with severe COVID-19 both systemically (in blood) and at the sight of infection (from tracheal aspirates).
Exploring functional protein covariation across single cells
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Open to view video.  |   Closed captions available Biological functions are reflected in the natural variation of proteome configurations across individual cells. Single-cell proteomics methods may decode this variation and empower inference of biological mechanisms with minimal assumptions. This promise is beginning to be realized by scalable sample preparation methods (allowing simultaneous preparation of thousands of single cells per batch) and sensitive mass-spectrometry methods. Specifically, prioritized single-cell mass-spectrometry analysis (pSCoPE) allows for consistent and sensitive analysis of thousands of proteins of biological interest, while multiplexed data independent acquisition methods (plexDIA) afford high throughput and data completeness. These methods have allowed us to interpret protein covariation in different biological systems, including primary macrophages and melanoma cells expressing markers for drug-resistance priming. The focus of the talk will be on conceptual innovations and strategies for data acquisition and interpretation that make single-cell protein analysis accessible, robust and highly quantitative.
SARS-CoV-2 neutralizing antibodies discovered across three individuals following vaccination and infection target diverse epitopes across virus spike protein.
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Open to view video.  |   Closed captions available The immune system of an individual contains the capacity to produce trillions of unique antibodyproteins. Identifying the antibodies involved in a particular immune response is key tounderstanding the acquired immunity to disease and crucial for future antibodytherapeutic development. While immunosequencing via next-generation sequencing of B and T cells has expanded our understanding of adaptive immunity, the molecular composition of the antibodies secreted in serum has only recently been investigated using mass spectrometry-based proteomics.We developed Alicanto for the purpose of identifying antibodies from patient serum. Alicanto integrates immunosequencing data with mass spectrometry measurements of serum antibodies to create a map of an individual’s immune response to disease. Alicanto identifies candidate antibodies from the map using a proprietary machine learning model.In this study, serum antibodies from three individuals who had been fully vaccinated against SARS-CoV-2 and subsequently infected with the virus were analyzed by Alicanto. Serum antibodies were fractionated based on binding to the receptor-binding domain (RBD) and those binding to non-RBD sites on the spike protein. Concurrently memory B cells reactive to spike protein were enriched and sequenced via next-generation sequencing. A subset of the B cell sequences were identified among the serum antibodies.We identified individual antibodies from each donor from each fraction and recombinantly expressed them. Antibodies were evaluated for inhibition of ACE2 binding to RBD and in pseudovirus neutralization assays. The sequences of serum antibodies and spike protein-reactive B cells were analyzed based on CDR sequence and organized into clonal lineages. In addition, we compared our newly discovered antibody sequences to those published by other groups of antibodies raised against earlier variants of the virus. Recent reports of neutralizing antibodies reveal shared sequence signatures among RBD-binding antibodies, and these were compared to our antibody sequences.Individual antibodies are observed as members of expanded lineages that share the same germline gene rearrangement event but have accumulated mutations as a result of somatic hypermutation. Higher quality therapeutic candidates can be mined from the lineage of a validated antibody in a process called hit expansion. For our best candidates, we will explore the lineage and characterize the distinct properties of the family members in terms of affinity and neutralization.
Harnessing the Power of Multiomics from a Single Sample with Advanced Automation for Sample Handling and Processing
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Open to view video.  |   Closed captions available The omics era has greatly expanded the repertoire of approaches available for researchers and clinicians to unravel the complexity underpinning human health: Next Generation Sequencing (NGS) approaches can characterize genomes, epigenomes, transcriptomes and proteomes. Advanced DNA barcoding and automated microfluidics can take this to the next level, enabling multiomic characterization of single cells. Peripheral blood mononuclear cells (PBMCs) offer a window into the immune system that, when combined with these omics tools, can provide a near holistic view of immune processes across patient cohorts. Here we detail a workflow using a single blood draw to rapidly produce a diverse set of multiomics results including genomics, epigenomics, transcriptomics and proteomics. This starts with automated sample handling and processing of the primary blood draw to ensure high viability and yield of PBMCs, along with simultaneous plasma separation and collection. These samples are then aliquoted and simultaneously processed for automated and semi-automated whole exome sequencing, single cell RNA sequencing, epigenetic characterization and Olink proteomic assays. With this robust workflow and advanced robotics for sample handling and processing to minimize potential batch effects, all these datatypes can be produced within days of primary sample collection using minimal sample amounts. High throughput integrative omics workflows, as described here, drive greater insights in human health, allowing for a rapid combined approach to address the biological questions at hand.
Strategies on scaling a multi-modal blood-based IVD-grade test for detection of colorectal cancer
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Open to view video.  |   Closed captions available Blood-based colorectal cancer (CRC) screening tests can improve adherence to screening guidelines, yet current commercially available options have poor sensitivity and specificity preventing effective implementation into routine clinical care. To this end we have developed a multi-modal blood based IVD-grade test, for the detection of CRC and advanced colorectal neoplasia, capable of processing millions of samples annually. This talk will provide a high-level overview of Guardant’s CRC screening test and discuss considerations for building laboratory automation and software at various scales to support the lifecycle of a complex IVD test, from early feasibility to data generation to large scale clinical testing.
Cancer-specific Orphan Noncoding RNAs (oncRNAs): A Novel Analyte for Liquid Biopsy
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Open to view video.  |   Closed captions available "Liquid biopsy testing based on circulating tumor (ct)DNA has become increasingly used in clinical practice. Mutations detected in ctDNA guide therapy selection in late-stage cancer, while other aspects of ctDNA — such as methylation status and fragmentation patterns — are utilized for early cancer detection and for minimal residual disease applications. However, ctDNA has limitations as an analyte. Because ctDNA is mainly released into the bloodstream upon cell death as one genome per cell, ctDNA quantities in blood are limited. Consequently, ctDNA-based liquid biopsy testing tends to have limited analytical sensitivity and requires relatively large volumes of blood for adequate test performance. Liquid biopsies based on cell free RNA (cfRNA) overcome these disadvantages. A given RNA transcript can be present at a high copy number within the cell. Further, RNA can enter the bloodstream via several mechanisms that do not involve cell death, including active release of RNA in extracellular vesicles, such as exosomes. As a result, cfRNA is more abundant in blood than ctDNA, which enables cfRNA-based assays to achieve greater analytical sensitivity with smaller sample volumes. Exai Bio was founded based on the discovery of a novel class of thousands of small RNA sequence species that are highly associated with cancer and are largely absent in healthy individuals. Exai Bio uses these RNAs, termed orphan non-coding RNAs (oncRNAs), as biomarkers in combination with artificial intelligence (AI) for liquid biopsy analysis in a variety of cancer types. In a longitudinal study of treatment-naive breast cancer patients, oncRNA levels were reduced by treatment, and greater reduction in oncRNA levels predicted better long-term survival. In a case-control study of colorectal cancer (CRC) patients, the Exai Bio machine learning model predicted CRC at sensitivities of 92% for each of cancer stages I, II and III, and 88% for stage IV, at 90% specificity. Similarly, sensitivities were ≥ 88% across T1–T4 categories of tumor size/extent."
Automation of an Early Detection Pancreatic Cancer Test Using 5-Hydroxymethylation Profiles
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Open to view video.  |   Closed captions available "Background Pancreatic cancer is one of the deadliest cancers, with up to 80% of cases diagnosed at late stages of disease. The five-year survival of pancreatic cancer has shown to improve from 10% to 40% if detected in early-stage disease compared to late-stage disease. The major barrier to better outcomes is the lack of early-detection molecular tools to enable timely intervention. We have developed a test that enables the detection of pancreatic cancer from a simple blood draw. The test incorporates a novel, genome-wide DNA sequencing-based epigenomics detection method of 5-hydroxymethylcytosine (5hmC) employed as a stable biomarker for the early cancer detection including pancreatic cancer. The test has been designed to be fully automated using multiple liquid handlers and provides a platform technology that utilizes the same streamlined laboratory workflow to deliver multiple early detection cancer tests at scale. Methods The test utilizes Hamilton STARs for cell-free DNA (cfDNA) extraction from plasma isolated from whole blood, Beckman Biomek i7s for library preparation of 5hmC and low-pass Whole Genome Sequencing (WGS), and Hamilton Starlets for post-PCR cleanup, and NovaSeq6000s for sequencing. The library preparation method alone incorporates over 400 pipetting techniques and liquid transfers with minimal human intervention. The test also employs logistic regression algorithms using 5hmC feature sets combined with DNA fragments profiles to distinguish cancer from non-cancer samples. Training of an algorithm was accomplished using a cohort of 132 pancreatic cancer (PaCa) cases and 528 non-cancer controls. A discrete cohort of 2,150 individuals consisting of 102 PaCa and 2,048 non-cancers was subsequently tested to provide robust analytical validation. Results Cross validation of the training model yielded an overall sensitivity of 65.9%,(95% CI, 57.2%–73.9%), early-stage (stage I-II) sensitivity of 57.1% (95% CI, 44%–69.5%) using a specificity threshold of 98%. The model was further validated in a separate, non-overlapping set of blinded and independently processed samples and yielded an early-stage sensitivity of 68.3% (95% CI, 51.9%–81.9%) and a specificity of 96.9% (95% CI, 96.0%–97.6%). Conclusion These results demonstrate that plasma-derived cfDNA 5hmC profiles enable the accurate detection of early-stage PaCa with a fully automated laboratory process, providing a scalable, and highly clinically necessary, non-invasive tool to help diagnose pancreatic cancer at early stages of disease. Additionally, the platform allows the rapid future validation of additional early cancer detection tests."
A universal workflow for automated sample preparation in large-scale proteomics
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Open to view video.  |   Closed captions available Mass spectrometry-based proteomics allows the comprehensive and accurate identification and quantification of proteins in an unbiased manner across large sample cohorts. The sample preparation for mass-spectrometry specimen is a multi-step process which includes many liquid transfers and timed incubations and is critical to ensure sensitivity and reproducibility. Hence, large-scale studies are often limited by labor-intensive workflows which introduce and propagate technical variability.Here we present a fully automated proteomic sample preparation which autonomously processes samples from biological input to MS-ready peptide output. The sample preparation platform is equipped with an 8-channel liquid handler and is robotically linked to different devices (including ultrasonication, absorbance measurement, sealing, peeling) which allows to perform the entirety of the sample preparation without any human interaction. The implemented method includes all preparation steps including sample denaturation, protein concentration determination, reduction, alkylation, proteolytic digestion, peptide clean-up, concentration determination and normalization. The method is designed for parallelized processing of two 96-well plates in a single run and provides a high degree of flexibility to work with different sample inputs such as cultured cells, lysed tissues or biofluids.The implemented method was evaluated on different levels. We processed a complex sample matrix of 192 samples to test the methods functionality, sensitivity and reproducibility. The matrix consisted mainly of HeLa lysates with varying protein loads and multiple replicates. For example, processing of 50 µg protein input and subsequent single-shot injections with FAIMS-Data-Independent-Acquisition (DIA) acquisition revealed on average 8300 protein groups (n = 6) identified with a median coefficient of variation of 4.1%. Processing of as little of 100 ng of protein input resulted in the identification of 5515 protein groups (n = 6) demonstrating the high sensitivity of the workflow. Furthermore, the assessment of intra- and inter plate variability with technical replicates showed a stable number of protein identifications with a high Pearson correlation (r = 0.998, n = 24) among the samples. Moreover, a longitudinal evaluation of technical replicates (n = 5) showed minimal effects by the time of processing (which in our experience is one of the major sources of variability), demonstrating the high-degree of standardization and overall reduction of technical variability. We obtain comparable number of protein identifications and quantification precision to our internal gold standard semi-automated protocol. The implemented end-to-end workflow drastically increases laboratory efficiency by reducing human input by more than 90% while maintaining sample output quality and achieving better reproducibility across preparations over time.In summary, the established workflow for fully-automated proteomics sample preparation significantly reduces hand-on time, minimizes quantification variability and improves longitudinal reproducibility.
Precision Medicine and Diagnostics
A high-throughput organoid screening platform for functional precision medicine
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Open to view video.  |   Closed captions available Sarcomas are a family of rare malignancies. Given the scarcity of tumor models for bone and soft tissue sarcomas, studying the underlying biology and identifying effective therapies remain difficult. Patient-derived tumor organoids (PDTOs) are representative of the native physiology of tumors across an array of malignancies, including sarcoma (Phan et al, 2019; Al Shihabi et al, 2021). Our goal is to leverage our established pipeline for facile, high-throughput organoid screening to identify individual sensitivity and resistance patterns across sarcomas within a week from surgery. We successfully generated organoids from over 100 samples originating from primary, recurrent, and metastatic lesions of bone and soft tissue sarcomas. PDTOs closely resemble the tumor of origin in their histology and molecular features. We observe tumor-specific susceptibilities with high heterogeneity both across and within sarcoma subtypes and identify patterns of response with respect to prior treatment, patient age, lesion type and disease trajectory.
TIMING: a platform for dynamic single-cell analysis and discovery of functional biomarkers for cancer cell therapy
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Open to view video.  |   Closed captions available Despite advances in sequencing technologies, mapping the functional heterogeneity within cell populations is a barrier to discovering disease biomarkers and predicting therapeutic response. To overcome this barrier, we developed a platform using time-lapse imaging microscopy in nanowell grids (TIMINGTM). Using machine learning algorithms, we mine TIMING datasets to observe, quantify and correlate behaviors of thousands of individual cells with functional readouts in every single experiment. Using a robotic cell selector, we retrieve individual cells with desired characteristics for downstream molecular profiling. The TIMING platform has been successfully leveraged to identify biomarkers of patient-derived CAR T cells that maintain proliferation, serial killing capacity, and sustained anti-tumor activity in vivo. In addition to a mechanistic understanding of disease, TIMING has been used to identify biomarkers on CAR T cells that predict complete response to CAR T cell therapy in patients with refractory or relapsed large B cell lymphoma. We have also applied the TIMING platform to show that convalescent SARS-CoV-2 patients have persistent serial-killer T cells that recognize an antigen conserved across variants of concern. We are now extending the applications of TIMING by using dynamic morphological and functional characteristics of cells and subcellular organelles to deepen the mechanistic understanding of cellular functions, identify disease biomarkers and optimize cell therapy products in immuno-oncology, infectious disease and other disease settings with major unmet clinical needs.
Patient-Derived Micro-Organospheres Enable Precision Oncology
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Open to view video.  |   Closed captions available Patient-derived xenografts (PDX) and organoids (PDO) have been shown to model clinical response to cancer therapy. However, it remains challenging to use these models to guide timely clinical decisions for cancer patients. Here we used droplet emulsion to rapidly generate thousands of Micro-Organospheres (MOS) from low-volume patient tissues, which serve as an ideal patient-derived model for clinical precision oncology. A clinical study of newly diagnosed metastatic colorectal cancer (CRC) patients using a MOS-based precision oncology pipeline reliably predicted patient treatment outcome within 14 days, a timeline suitable for guiding treatment decisions in clinic. Furthermore, MOS capture original stromal cells and allow T cell penetration, providing a clinical assay for testing immuno-oncology (IO) therapies such as PD-1 blockade, bispecific antibodies, and T cell therapies on patient tumors. Lastly, we demonstrate an ultra high-throughput MOS screening platform that provides “virtual clinical trials” to capture patient diversity for determining drug efficacy.
Accelerating the use of iPSC-derived organoids in drug discovery and personalized medicine
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Open to view video.  |   Closed captions available One of the biggest hurdles for improving drug efficacy and discovery has been the lack of relevant pre-clinical model systems that recapitulate human pathophysiology. Together, advancements in generating patient-derived induced pluripotent stem cells (iPSCs) and iPSC-derived organoids provide progress towards more complex cellular models that replicate molecular and physiological properties of human organs, including patient-specific aberrations. However, the workflows associated with establishing and differentiating iPSCs into 3D organoids are inefficient, manually labor-intensive, and suffer from limitations of heterogeneity and throughput, limiting their utility in pre-clinical assays. Using the CellRaft AIR Technology, we developed a user-friendly, automated platform for generating iPSC-derived organoids that solves these key challenges, allowing for 1) streamlined workflows, 2) reliable imaging of every organoid throughout differentiation, 3) user-defined identification of organoid populations based on phenotypic and morphologic characteristics, and 4) automated retrieval of single organoids of interest for continued growth, or downstream analysis, including multiomics and drug screening. We demonstrated that single iPSCs seeded in suspension in extracellular matrix on the 3D CellRaft Array can be differentiated into multiple organoid types, including kidney, cerebral, and choroid plexus. To demonstrate the ability of the CellRaft AIR System to interrogate heterogenous iPSCs, two populations of edited iPSCs, one red fluorescent protein (RFP) and one green fluorescent protein (GFP) positive, were seeded on the CellRaft Array for cerebral organoid differentiation. iPSCs were cultured on the array for the first three phases of cerebral organoid differentiation, embryoid body formation, neural induction, and expansion, and serial images were captured after cell seeding and every 24 hours to monitor phenotypic and morphologic changes throughout differentiation. Using the CellRaft Cytometry software, we identified three populations of cerebral organoids: single cell-derived mono-fluorescent, RFP or GFP positive, organoids, and organoids derived from multiple cells that expressed both reporters. At day 10, size-selected cerebral organoids were isolated into 96-well plates into organoid maturation media using the CellRaft AIR System with more than 95% efficiency. Cerebral organoids were maintained in the 96-well plates for maturation out to day 40, where they continued to increase in size and developed neurite outgrowth, allowing them to be used for drug screening assays. Using iPSC-derived organoids pre-selected for features such as size, morphology, and fluorescence reporters, we have demonstrated the ability to generate custom iPSC-derived 96-well plate arrays for downstream drug screening assays. These results validate the ability of the CellRaft AIR System to provide a solution for otherwise challenging workflows that will be broadly applicable to the field of personalized medicine for tissue specific diseases and will accelerate the utility and reproducibility of iPSC-derived organoids.
Next Generation of Logic-Gated CAR T Cells to Revolutionize the Treatment of Cancers
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Open to view video.  |   Closed captions available "Solid tumors comprise >90% of cancers. Non‐small cell lung cancer (NSCLC), colorectal cancer (CRC), and pancreatic cancer (PANC) are the leading causes of cancer‐related mortality (metastatic 5‐year survival rate of 8%, 15%, and 3% respectively) [1]. Chimeric antigen receptor (CAR) T‐cell therapy has demonstrated clinical outcomes in hematologic malignancies [2,3]. However, translating engineered T‐cell therapies to solid tumors proves difficult due to a lack of tumor‐specific targets that distinguish cancer cells from normal cells. In previous studies, the use of carcinoembryonic antigen (CEA) T‐cell receptors and mesothelin (MSLN) CARs both resulted in dose‐limiting on‐target, off‐tumor toxicities [4‐6] Tmod™ CAR T‐cell is a logic‐gated cell therapy that addresses these challenges by leveraging dual receptors capable of killing tumor cells while leaving healthy cells intact [7]. Tmod platform technology is a versatile system that may be applied to T cells and natural killer cells in autologous and allogeneic settings. A2B530 is a CEA‐directed and A2B694 is an MSLN‐directed Tmod construct both utilizing a leukocyte immunoglobulin‐like receptor (LIR) 1‐based inhibitory receptor (blocker) targeting HLA‐A*02. Human leukocyte antigen loss of heterozygosity (HLA LOH) may provide a means to distinguish between tumor and normal tissue in a definitive manner due to this irreversible, clonal loss within tumor cells [7,8]. The 2 receptors of the Tmod CAR T‐cell platform comprise an activator that recognizes an antigen present on the surface of normal and tumor cells and a blocker that recognizes a second surface antigen from an HLA allele lost only in tumor cells. Based on the Tempus xT real‐world database, LOH occurs in 12.2% to 26.0% of advanced solid tumors with an average of 16.3% in 10,867 samples tested [9]. BASECAMP‐1 is an ongoing study with the following key objectives: 1) To determine and identify patients with somatic HLA LOH eligible for Tmod CAR T‐cell therapy and 2) subsequent leukapheresis and manufacturing feasibility for future Tmod CAR T‐cell trials. Eligible patients identified in BASECAMP‐1 will be referred to the EVEREST-1 A2B530 CEA Tmod and EVEREST-2 A2B694 MSLN Tmod interventional studies. References 1. American Cancer Society. Cancer Facts & Figures 2022. Atlanta: American Cancer Society; 2022. 2. Neelapu S, et al. N Engl J Med. 2017;377(26):2531‐2544. 3. Maude S, et al. N Engl J Med. 2018;378(5):439‐448. 4. Parkhurst M, et al. Mol Ther. 2011;19(3):620‐626. 5. Haas AR, et al. Mol Ther. 2019;27(11):1919‐1929. 6. Tanyi JL, et al. Presented at: Cellicon Valley ’21: The Future of Cell and Gene Therapies; May 6‐7, 2021; virtual symposium. 7. Hamburger A, et al. Mol Immunol. 2020;128:298‐310. 8. Hwang M, et al. Proc Natl Acad Sci U S A. 2021;118(12):e2022410118. 9. Hecht J, et al. J Clin Oncol. 2022; 40(4_suppl):190‐190. 10. Borges L, et al. J Immunol. 1997;159(11):5192‐5196. 11. Perera J, et al. J Immunother Cancer. 2019;7(suppl 1):P103. 12. The Cancer Genome Atlas (TCGA) Research Network. Accessed June 2021. 13. Sandberg M, et al. Sci Transl Med. 2022;14(634). 14. Tokatlian T, et al. J Immunother Cancer. 2022;10:e003826.
Genomic Biomarker Development and Validation
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Open to view video.  |   Closed captions available The rapid expansion of high dimensional “omic” technologies and their rapidly falling costs have ushered in the era of precision medicine. There is a huge unmet need for biomarkers in different aspects of health and disease. However, large cohorts of samples and data are required for the training, discovery, and validation of diagnostic tests. The pace of innovation and growth in developing diagnostic biomarkers has not allowed sufficient time to generate a set of standardized and established approaches to the bioinformatic needs necessary to process genetic/genomic data toward validated biomarker signatures. Many current biomarkers have not been vetted sufficiently through accepted bioinformatics approaches. As a result, there appears to be some difficulty reaching consensus around the validation of published biomarkers. Despite the dire need for genomic biomarkers, there are clear risks associated with candidate biomarkers as potential surrogates of clinical phenotypes without a thorough understanding of, and a conceptual framework to guide, statistically sound discovery and validation in the context of high-dimensional data. The objective of this talk is to provide a set of guiding principles for the translation of high-dimensional genomic data into discovery and validation approaches that can result in clinically relevant biomarkers using two real world examples.
Amphiphilic Particle Stabilized Droplet Assays for Scalable "Swarm" Sensing Based Diagnostics
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Open to view video.  |   Closed captions available "The ability to compartmentalize reactions into extremely small (femtoliter – picoliter) volumes has enabled the study of biology with exquisite sensitivity1. Low/no crosstalk and uniformity ensure each partition serves as an individual reaction compartment with comparable conditions. Currently available compartmentalization technologies, based on droplet or microwell arrays, require specialized infrastructure to operate2. Droplet assays are also marred by surfactant enabled diffusion of reaction products leading to crosstalk3. These limit their accessibility and usability for diagnostics and research. We present 3D structured, amphiphilic particles which thermodynamically stabilize picoliter scale droplets without any surfactants4. The multimaterial particles are made of concentric layers of hydrophobic and hydrophilic polymers with a cavity in the middle. Unlike traditional emulsions, these particle-stabilized droplets of a controlled volume occupy a local minimum in the interfacial energy thus producing monodisperse compartments with simple mixing operations in a standard well plate format4. This workflow is compatible with existing laboratory automation equipment5, and can be easily adopted for high-throughput and pooled sample testing. We have also developed fabrication methods to produce multimaterial particles with various shapes by flow-sculpting streams of either inner, outer, or both polymer layers5,6. Shape-based barcodes enable multiplexed screening or pooled patient testing panels thereby reducing costs per assay. To the best of our knowledge, this method of using shape-encoded engineered particles and surface chemistries to stabilize drops while comprising functionalized surfaces for assays is the first of its kind. In our most recent work, we have leveraged these particles to measure N-terminal propeptide B-type natriuretic peptide in a droplet assay for heart failure monitoring. We achieved detection down to 100 pg/ml in serum and were able to classify cardiac patient samples from healthy controls. We also showed, with Monte Carlo simulations, utility of multiple measurements per sample, using each individual droplet as a part of a larger “swarm” of sensors, in improving statistical accuracy of quantitation. By enabling formation of multiple isolated reaction compartments in a standard well plate format, our multimaterial amphiphilic particle based technology can serve as an accessible platform for high-throughput sensitive diagnostics and screenings. These particles can be chemically modified with a variety of ligands, affinity reagents, and sensing molecules to develop a whole host of particle technologies to accelerate research and scale-up diagnostics."
Modeling Cancer Drug Resistance and Stemness with a Patient-Derived Colorectal Tumor Model
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Open to view video.  |   Closed captions available Colorectal cancer is one of the most lethal types of solid cancer. Despite targeted therapies for solid tumors using molecular inhibitors, cancer cells often adapt to the treatments and develop resistance through mechanisms such as target mutation and activation of compensatory signaling pathways. Understanding mechanisms of treatment failure is critical to develop effective therapies and improving outcomes for patients. Using our aqueous two-phase system microtechnology, we robotically microprinted tumor spheroids of conditionally reprogrammed colorectal cancer cells, originally derived from a patient, obtained through the NIH/NCI PDMR. We investigated active signaling pathways in the cells and found activation of several oncogenic signaling including MAPK and BRAF. We treated the spheroids with the different inhibitors of these pathways using a cyclic treatment and recovery regimen to mimic how patients receive chemotherapy. Despite an initial response to the first treatment round, cancer cells developed resistance during subsequent cycles and proliferated. Our molecular analysis showed activation of PI3K/Akt oncogenic pathway and MYC transcription factor. Additionally, we found that drug-resistant cells display cancer stem cells (CSCs) phenotypes and upregulate several CSC gene markers including ALDH1A3 and LGR5.Next, we examined different therapeutic strategies against the adaptive resistance of cancer cells to the treatments. We selected several drug combinations based on the activities of oncogenic signaling. Despite the anti-proliferative effects of combinations of (1) BRAF/MEK inhibitors and (2) MEK/CSC inhibitors, they were ineffective against CSCs. Considering that WNT pathway is critical for cancer stemness, we used a combination of BRAF/WNT inhibitors and successfully downregulated cancer cell proliferation, stemness, and drug resistance. Overall, our approach to use a 3D tumor model of patient-derived cells and perform high throughput screening of drug combinations to block compensatory signaling and CSC phenotypes will facilitate treatment selections to expedite progress to clinical trials and personalized medicine.
New Modalities
PROTAC-Mediated Ternary Complex Formation: Key Parameters that Influence Targeted Protein Degradation
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Open to view video.  |   Closed captions available Targeted protein degradation via hijacking the innate ubiquitin proteasome system (UPS) using proteolysis targeting chimeras (PROTACs) has been evolved as a novel therapeutic modality in recent years. However, the design of hetero bifunctional small molecules such as PROTAC is challenging due to the multiple steps involved in PROTAC-induced degradation, thus, making it difficult to establish a coherent structure-activity relationships (SARs). Here, we characterized PROTAC-mediated ternary complex and degradation activity using different assays by employing PROTACs of two different targets (SMARCA2 and BRD4) recruiting a common E3 ligase (von Hippel-Lindau). By varying different components of PROTAC architecture, binding and degradation parameters were evaluated for these molecules. Ternary complex binding affinity demonstrated good correlation with the degradation potency, whereas, PROTAC cooperativity factor correlated very well with the initial rate of target degradation. Our findings elucidate the relationship between binding and degradation parameters, which establishes a framework for SAR in designing potent and effective degraders.
Use of Fragment Libraries for New Ligase and Target Identification
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Open to view video.  |   Closed captions available Harnessing the ubiquitin-proteasome system to facilitate the targeted degradation of disease-relevant proteins is an emerging and attractive pharmaceutical strategy. Through the application of bispecific compounds and molecular glues that form ternary complexes between protein targets and E3 ligases, promising drug candidates are emerging possessing favorable efficacy and selectivity profiles. Moreover, since this strategy is dependent upon induced proximity, ligands may be selected that bind in a larger number of poses than conventional inhibitors or agonists. Since many pharmaceutical compound libraries are biased towards active site binding, using fragments and fragment-like molecules to induce degradation can provide important details on functionally relevant ligandable sites for both drug targets and E3 ligases. In this presentation, we report on the evolution of fragments capable of inducing proteasome-dependent degradation when engineered into bispecific degraders. Additionally, we will discuss the deconvolution of proteins and molecular features driving their function.
See-N-Seq: RNA Sequencing of Target Single Cells Identified by Microscopy
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Open to view video.  |   Closed captions available Single cell RNA sequencing has the potential to elucidate transcriptional programs underlying key cellular phenotypes and behaviors. However, there are many phenotypes that are incompatible with indiscriminate single cell sequencing because they are rare, transient, or can only be identified by imaging. Existing methods for isolating cells based on imaging for single cell sequencing are technically challenging and prone to cell loss because of the need to physically extract single cells. To address this challenge, we developed See-N-Seq, a simple strategy to selective sequence RNA from single cells identified by microscopy without needing to physically extract each cell.The See-N-Seq process involves (1) dividing cells among microwells, (2) fixing cell position by encapsulation in porous hydrogel thin-film, (3) imaging to select one target cell from each microwell, (4) target cell isolation by embedding non-target cells in non-porous hydrogel, and (5) selective lysis and mRNA extraction for sequencing preparation.We first investigated laser micropatterning of hydrogel porosity by polymerizing a non-porous hydrogel inside a porous hydrogel. Using a laser scanning system integrated in an inverted microscope, we achieved a minimum spatial resolution of 12 µm using 20X objectives. To confirm micropatterning of hydrogel porosity, we stained the hydrogel using 10 kDa FITC-dextran, which only stained the central circular region of the porous hydrogel. Micropatterning the non-porous hydrogel to selectively expose target cells and embed non-target cells enabled selective lysis of a single target cell, which is demonstrated by the loss of fluorescence after adding the lysis buffer. RNA isolation from target single cells were tested by qPCR, which were confirmed by the presence of the mCherry or EGFP transgenes in the appropriate target cells.To demonstrate See-N-Seq transcriptome sequencing of complex image-defined cell phenotypes, we generated an immunological synapse using model T-cells (Jurkat), antigen-presenting cells (Raji), and SEE super-antigen. Synapse cell pairs were selected based on the localization of CD3 after 0, 4, and 24 hours of incubation (S0sc, S4sc, S24sc). Controls included single Jurkat (Jsc), single Raji (Rsc), and non-synapsing cell pairs (N0Ssc, NS4sc, NS24sc). Differential gene expression analysis revealed distinct transcriptomes between Jsc and Rsc, but highly consistent transcriptomes between S0sc and NS0sc, as well as between NS0sc and merged Jsc+Rsc data sets. Transcriptomes of immunological synapses at 4 hr (S4sc) begins to diverge from synapses at 0 hr (S0sc). After 24 hr incubation, the S24sc transcriptomes diverged into two distinct groups, corresponding with Th1 (S24scG1) and Th2 (S24scG2) lineages.See-N-Seq addresses a key challenge in single cell sequencing to associate single cell transcriptome data directly with observed cell phenotypes to elucidate transcriptional programs that drive specific cellular processes.
Discovery and characterization of novel small molecule degraders of BRD4 that act through the recruitment of DCAF11
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Open to view video.  |   Closed captions available Targeted protein degradation (TPD) through the ubiquitin proteasome system (UPS) is a rapidly growing drug discovery approach to eliminate pathogenic proteins. Strategies for TPD have focused on heterobifunctional degraders in which an E3 ligase and a target protein are brought into proximity. Optimization of drug-like properties has often been challenging. Monovalent degraders represent an alternative approach, in which small molecules are designed to bind to the target protein and induce its degradation through the recruitment of an E3 ligase complex. However, until now, the discovery of monovalent degraders has relied on serendipity. Using our ultra-high throughput cell-based screening platform, which measures degradation of target proteins upon exposure to diverse E3 ligase agnostic chemical libraries, we identified several monovalent degraders of the bromodomain extra-terminal (BET) protein BRD4. Optimization of hits produced a lead compound, PLX-3618, which elicited full, rapid, and selective degradation of BRD4, strong down-regulation of the MYC oncogene, and potent anti-proliferative activity in AML. Further characterization confirmed BRD4 degradation was mediated via the UPS, and a ubiquitin ligase-focused CRISPR screen identified CUL4BDCAF11 as the E3 complex responsible for PLX-3618-mediated degradation of BRD4. Protein-protein interaction studies verified a BRD4/PLX-3618/DCAF11 ternary complex, and mutational studies provided further insights into the DCAF11-mediated degradation mechanism. Collectively, these results demonstrate the efficient discovery of novel small molecule degraders using Plexium’s proprietary platform, and subsequent characterization of the degradation mechanism highlights the discovery of DCAF11 as an E3 ligase substrate receptor amenable to redirection for neo-substrate degradation.
Base Editor Screening Platforms to Characterize Performance of the Modular Components of Horizon’s Pin-Point™ Base Editing Technology Platform.
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Open to view video.  |   Closed captions available "CRISPR base editing is the new generation of CRISPR technology. CRISPR-Cas systems introduce double strand DNA breaks at the target site and rely on non-homologous end joining to disrupt gene function. Base editing introduces a point mutation, which can turn a gene off by creating a stop codon but can also edit a causative mutation to repair a defective gene. Base editing has been used to edit point mutations that are causative of rare diseases and create CAR-T treatments for cancer, without introducing the double strand DNA breaks that are characteristic of traditional CRISPR. This significantly improves the safety of gene editing and makes cell and gene therapy a reality. The first cohort of base editing therapeutics are in clinical trials and have been approved by the FDA. Horizon’s novel Pin-Point™ base editing technology utilizes an RNA aptamer embedded within the guide RNA to target the gene of interest and recruit an effector module, e.g., a cytidine deaminase1. The modularity of the Pin-point platform enables a high degree of flexibility which allows fine tuning of critical aspects of editing behaviour including conversion efficiency, target window size and edited base position. Herein we describe the development of arrayed screens to optimize the performance of the components of the Pin-point base editing system for the target site(s) and pooled screens for high throughput guide RNA selection. Firstly, we describe an arrayed screening platform highlighting its utility in multiple cell lines, using five different cytidine deaminases and three structurally distinct guide RNA and aptamer designs, and assess each configuration of the Pin-point technology platform at 70 guide-specific genomic sites. We demonstrate significant impact upon editing efficiency, editing window size and position, and context preference with different deaminases. Secondly, we present a flexible and adaptable pooled screening reporter platform for high-throughput parallel assessment of >65,000 guides. We demonstrate the ability of the pooled screening platform to detect editing in a highly reproducible manner with a high dynamic range across multiple cell lines and time-points. These data confirm that the Pin-point base editing platform is a tuneable modular technology whose functionality can be readily adapted to address diverse editing requirements. The ability to comprehensively screen multiple iterations of the technology in a high-throughput manner promises to enable customization and optimizing of the performance of the Pin-point base editing platform for specific cell and gene therapy applications. Further, by combining Pin-point base editing with functional genomic screening, we can create an array of mutational variants providing novel insights into drug-variant interactions. This will guide and accelerate the path towards successful drug discovery and precision medicine. 1. Collantes et. al., CRISPR J, 2021;4:58-68
Small molecule modulation of mRNA processing to control gene expression and target disease drivers
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Open to view video.  |   Closed captions available REMIX Therapeutics is focused on discovering new treatments for patients through selective modulation of RNA processing for undruggable disease drivers. Specifically, we are developing novel small molecule therapies designed to reprogram RNA processing and control gene expression to treat diseases of high unmet need via the modulation of high-value, genetically validated oncology, immunology, neurology, and rare genetic disease targets. The experienced REMIX management team and scientific advisors possess deep expertise in drug discovery/development, RNA processing and oncology/neuroscience. Traditional small molecule and PROTAC drug development approaches are limited to targeting proteins with druggable pockets or ligandable proteins. In contrast, the REMIX approach unlocks undruggable targets by modulating upstream RNA processing events. In this way, compounds act independently of target protein structure or function via a well-understood mechanism of action (MOA) and can be optimized for CNS penetration. Furthermore, by co-opting RNA processing machinery it is possible, in principle, to degrade or enhance target protein expression, as well as to rescue disease-causing variants. The core of REMIX’s unique and proprietary drug discovery engine is the REMaster platform that initially capitalizes on terabytes of in-house and externally curated transcriptomic data to enable predictions of actionable RNA processing events via the use of proprietary algorithms and machine learning. Functional and genetic tools/manipulations then make it possible to validate and prioritize these events for drug discovery. Ultimately, unique, highly multiplexed screening technologies are used in conjunction with a proprietary chemical library enriched in compounds that target RNA and RNA-protein complexes to identify and optimize effective and selective small molecules. Additional key components of the REMaster platform are a growing suite of biophysical assays and the structures of key RNA-protein complexes that, collectively, facilitate a deep understanding of the MOA underlying the actions of a given compound. To date, REMaster platform technologies have been used to identify potent and selective compounds that precisely control the mRNA and protein levels for a variety of oncology and neurology targets. Ongoing large-scale and multiplexed HTS screens have begun to identify chemical matter for several high-value oncology, neurology, immunology and rare genetic disease targets. Drug discovery programs emerging from these screens are populating a broad REMIX pipeline that will target multiple therapeutic areas. A subset of these programs will be progressed through a collaborative partnership with Janssen Pharmaceuticals.
Proprietary Peptide Docking Vehicle (PDoV) –GalNAc RNAi Delivery Platform
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Open to view video.  |   Closed captions available "Sirnaomics company profile and background introduction. Sirnaomics’s HKP/dual siRNA PNP delivery platform. PDoV design for single and dual siRNA delivery to hepatocytes in the liver. Synthesis of PDoV conjugates and in vitro/in vivo validation of the platform Summary and comparison of PNP and PDoV delivery system."
Targeting extracellular and membrane proteins for degradation via lysosome targeting chimeras
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Open to view video.  |   Closed captions available "Targeted protein degradation (TPD) is a promising new therapeutic modality and a tool for probing biological pathways. Several TPD platforms have emerged over the past two decades, including PROTACs, that rely on the ubiquitin proteasome system (UPS) to induce degradation. However, the cytosolic nature of the UPS requires these degraders to be cell-permeable, restricting their target scope to proteins with accessible cytosolic domains. In order to expand the scope of TPD, we have developed lysosome targeting chimeras (LYTACs) for targeting extracellular and membrane proteins for degradation. LYTACs harness endogenous lysosome targeting receptors that traffic proteins to the lysosome. By bridging the target protein with a lysosome targeting receptor, LYTACs promote lysosomal degradation of extracellular and membrane proteins. Following the initial development of LYTACs, we have now identified key genetic regulators of LYTAC activity through a genome-wide CRISPR screen, and elucidated pathways that are essential for improved lysosomal trafficking. In addition, we have expanded the LYTAC technology by harnessing tissue-specific lysosome targeting receptors to enable targeting distinct cell types."
Proteolysis Targeting Antibodies For Cell Surface Receptor Degradation
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Open to view video.  |   Closed captions available The development of Proteolysis Targeting Chimeras (PROTACs) technology over the last two decades has demonstrated the advantages of targeted protein degradation over inhibition. However, generating heterobifunctional compounds with high affinity and specificity to achieve efficient protein degradation is challenging, especially with a limited number of available ligands. Here we describe the development of Proteolysis Targeting Antibodies (PROTABs), a large molecule degrader that induces proximity between cell surface E3 ligase and transmembrane proteins, resulting in target degradation in vitro and in vivo. We show that ligase Zinc and Ring Finger 3 (ZNRF3) based PROTAB can enable colorectal cancer (CRC) specific degradation. In addition, we offer insights on the ground rules governing PROTAB mediated degradation by antibody format engineering and demonstrate that “on-demand” tissue-selective receptor degradation is achievable by leveraging additional E3 ligases on the cell surface.
Exploiting the PROTAC system to TIP60ing the balance for cancer treatment
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Open to view video.  |   Closed captions available In human papillomavirus (HPV)-positive cervical cancer, E3 identified by the differential display (EDD1) is upregulated and ubiquitinates the tumor suppressor Tat Interactive Protein 60 kDa (TIP60). EDD1-mediated ubiquitylation of TIP60 targets it for proteasomal degradation and ablates its tumor-suppressive functions. We hypothesized that selective targeting of EDD1 could restore TIP60 levels in HPV-induced cancers. With the lack of small molecules that can target EDD1 directly, we utilized the dTAG PROteolysis Targeting Chimera (PROTAC) system as a novel approach to degrade EDD1 indirectly. Through pulldown assays, we identified TIP60327-372 as the specific region of TIP60 that binds to EDD1. As dTAG specifically binds to FKBP12F36Vonly, we generated four fusion proteins incorporating FKBP12F36V and the TIP60327-372 peptide fragment in different sizes and orientations to function as an intermediate between dTAG and EDD1. In vitro experiments showed that the TIP60327-372-FKBP12F36V fusion protein was best suited to be used in the dTAG system to degrade EDD1. MG132, a proteasome inhibitor, was used to confirm that the decrease in EDD1 protein level was due to proteasomal degradation. Colony formation assays demonstrated that EDD1 degradation reduced the colony size in dTAG-treated HeLa cells stably expressing TIP60327-372-FKBP12F36V. These data suggest that targeting EDD1 has an anti-proliferative potential and also provides a proof of concept that can be exploited to target EDD1 in cancers.
The combination of PROTACS and AlphaLISA SureFire technology for the high throughput screening of kinases in drug discovery programs
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Open to view video.  |   Closed captions available "Screening of compound libraries for modulators of cellular function can require high throughput technologies amenable to automation. Protein phosphorylation within different cellular pathways is a common event for measurement of drug effectiveness. The AlphaLISA SureFire Ultra panel of protein phosphorylation kits provide such rapid, homogeneous assays, allowing drug effectiveness to be analysed for large or small sample numbers. More recently there has been an increased focus on 'Total' SureFire Ultra assay development and its combination with PROTACS for targeted protein degradation analysis. For such work, ideally we require assays against the ’Total’ proteins for directly assessing target engagement as well as assays that measure the downstream phosphorylation effects resulting from target engagement. To maximize data generation per sample, we have also recently expanded the SureFire Ultra assay portfolio to include the analysis of two targets per sample in a fully mix-and-read multiplexing format, termed Alpha SureFire Ultra Multiplex. This technology can measure either two different phosphoproteins, the phospho and total levels of the same protein or two different total proteins. We are continually expanding the development of new phospho/total assay kits to allow a greater selection of pathways for analysis, where normalization of the phospho signal with the total protein is achieved. Data will be presented on numerous recently developed assays and PROTACS examples, highlighting the utility of Alpha SureFire technology as a platform of choice for both high and low throughput screening applications in drug discovery."
A Novel High-Throughput Imaging Assay to Automate Visualization and Measurement of RNA in Single Cells
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Open to view video.  |   Closed captions available High-Throughput Imaging is routinely used in combination with immunofluorescence to visualize proteins, with genetically encoded fluorescent proteins, or with fluorescent chemical labels that bind to lipids or to nucleic acids, including RNA, albeit with extremely low sequence specificity. Visualizing and measuring nucleic acids by in situ fluorescence hybridization (FISH) in a high-throughput manner and with high sequence specificity could enable the systematic study of cellular processes in which RNA plays a central role, including transcription, splicing and translation. To this end we developed HCR RNA FISH, an optimized and semi-automated version of Hybridization Chain Reaction in a 384-well format. HCR RNA FISH is capable of sensitively quantifying changes in the levels of multiple RNA species in thousands of single cells per well and in thousands of wells per experiment. We first tested HCR RNA FISH in a CRISPR-Knock Out (KO) screen in human cells to identify cellular pathways that modify the activation of interferon stimulated genes (ISG). The screen, and subsequent validation experiments, identified several protein complexes, including cohesin and NuA4, whose ablation leads to upregulation of the ISG response both at basal levels, and in the presence of interferon-γ. We then developed an HCR RNA FISH assay to quantify alternative pre-mRNA splicing (AS) in human cells. This assay was used in an RNAi screen aimed at the identification of protein kinases that regulate AS of the FGFR2 gene, which is involved in development and cancer. The screen identified 6 protein kinases whose knock-down led to alterations of AS patterns of FGFR2. Finally, HCR RNA FISH was also used to estimate cell-to-cell and individual-to-individual heterogeneity of TNF and IL1B gene expression in primary human immune cells exposed to different combinations of Lipopolysaccharide (LPS), a known immunostimulant, and methylprednisolone (MP), an anti-inflammatory compound. Altogether, these results show that HCR RNA FISH is a robust technique that can be useful for functional genomics screens and/or in primary human cells to address a variety of questions related to the regulation of gene expression on a large scale and at the single cell level.
A novel E3 ligase-dependent glue degrader targeting STING
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Open to view video.  |   Closed captions available Stimulator of interferon genes (STING) is a central component of the cytosolic DNA sensing pathway, having a key role in the type I interferon innate immune response. Localized at the endoplasmic reticulum (ER), STING becomes activated by cGAMP, which is generated by the intracellular DNA sensor, cyclic GMP-AMP synthase (cGAS). Due to its critical role in immune function and its’ involvement in a variety of diseases, STING has been the focus of drug discovery efforts. Recent advances in drug discovery allow the targeting of proteins previously considered “un-druggable” by novel mechanisms of actions. Glue degraders are defined as compounds leading to targeted protein degradation (TPD) by creating novel ligase-substrate interactions. Here, we identify Compound 1, a novel glue degrader for STING. A genome-wide, CRISPR/Cas9 knock-out screen showed that the compound-mediated degradation of STING is compromised by the loss an E3 ligase that has not been previously reported in the context of TPD. In addition, two ubiquitin-like modifier-activating enzymes (E1 enzymes) were found to modulate STING degradation via Compound 1. While these two E1 enzymes may be auxiliary factors for Compound 1 activity, our results indicate that the novel E3 ligase is the main factor for the observed degradation mechanism. Validation, by individual CRISPR knock-outs, co-immunoprecipitations, as well as proximity mediated reporter assays reveal that Compound 1 functions as a glue degrader by forming novel interactions between STING and this E3 ligase. Furthermore, this mechanism was shown to be effective on the most common pathological STING mutations that cause STING-associated vasculopathy with onset in infancy (SAVI), suggesting a potential clinical application of this mechanism. Thus, these findings reveal a novel E3 ligase-dependent mechanism for compound-induced degradation of STING.
Proteome-Wide Ligand and Target Discovery in Cells
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Open to view video.  |   Closed captions available Advances in DNA sequencing and editing technologies have revolutionized our understanding of the molecular basis of many human diseases. However, many disease-relevant genes encode proteins that are poorly characterized and/or are considered “undruggable”, hindering our understanding of disease mechanisms and translating this knowledge into new therapies. Chemical probes offer a valuable way to directly interrogate the function and disease-relevance of proteins and can also serve as valuable leads for drug development, yet most proteins in the human proteome lack small-molecule ligands that can serve as probes. More generally, the boundaries, if any, on the ligandability, and therefore potential druggability, across native proteomes remains poorly understood. In this seminar, I will describe our lab’s efforts to develop powerful photoaffinity-based chemical proteomic strategies to broadly map reversible small molecule-protein interactions directly in cells, and how this information can be advanced into useful chemical probes to investigate protein function.
CETSA HT : Accelerating drug discovery for complex targets
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Open to view video.  |   Closed captions available Using our optimised Cellular CETSA-HT, we have successfully enabled Hit-ID campaigns to screen 250,000 compounds for high-value Oncology targets. The technology has a simple workflow, enabling automated, microtitre plate-based screening at scale. Furthermore, we have applied antibody-based Cellular CETSA at scale, to understand the disconnect between biochemical and phenotypic assays in complex targets.Target engagement is a critical step in characterising small molecule modulators and CETSA has revolutionized our ability to measure target engagement at a cellular level. However, there have been major limitations of the technology such as complex workflow, qualitative readouts (westerns) and throughput limitations, making it challenging for high-throughput screening (HTS) applications.In combination with our screening expertise, we have employed Cellular CETSA to measure target engagement with the native protein in a cellular setting at-scale, enabling hit finding, accelerating the early stages of drug discovery as well as supporting early preclinical studies.Current efforts in drug discovery focus on delivering innovative medicines by modulating complex targets, that are part of large heterocomplexes and have limited enzymatic activity on their own. This presents major challenges in hit finding, protein purification and delivering native conformations for biochemical screening. Another challenge is bridging the gap between evolving chemistry and phenotypic readouts in complex disease relevant models with these intractable targets. We will be sharing key learnings using multiple case studies , demonstrating technology development as well as project progression to address these challenges using CETSA-HT at AstraZeneca. In summary, our novel CETSA-HT workflow is providing key insights to accelerate complex drug discovery projects in the Oncology space.
Leveraging HTS technology and lab automation to generate high quality datasets for machine learning driven mAb design
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Open to view video.  |   Closed captions available Therapeutic antibodies require optimal functional property and desirable developability profiles to be viable in clinic. Traditional mAb discovery is both time consuming and limited in sequence space as a solution. Generate Biomedicines is building cutting-edge ML models and integrated dry lab and wet lab capabilities to enable lead discovery and sequence optimization. We have built state-of-the-art automation systems to scale up antibody production and characterization capabilities and an integrated data platform to support the discovery engine. The large data sets generated provide a solid foundation for building ML models to co-optimize multiple parameters at the same time. I will describe some of the high-throughput screening technologies and lab automation systems and how they are integrated into the “learning loop” of the co-optimization process. I will give a couple of examples on how we use high-throughput assay data, especially cell-based functional assay to optimize the function of ML-driven antibody design.
Evolving high-throughput screening to identify small molecule RNA modulators
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Open to view video.  |   Closed captions available Evolving high-throughput screening to identify small molecule RNA modulatorsOver recent years there has been a change in the landscape of drug discovery, with an increase in the number of pursued modalities and a focus on targets which have traditionally been considered intractable. Novel targets identified through functional genomic techniques and artificial intelligence knowledge graphs represent exciting new ways to treat disease. However, these targets are often catalytically inert or lack distinct binding sites, making these targets extremely challenging for traditional hit finding strategies. Modalities such as PROTACs and molecular glue degraders to drive targeted protein degradation offers one avenue to progress these challenging targets. Alongside methods for protein modulation, RNA as a small molecule target has seen an increase in interest, allowing not only targeting of the coding genome, but also non-coding parts of the genome linked to disease. Several small molecules have been identified that modulate RNA using a range of mechanisms and regulate diverse biological processes. The clinical relevance of small molecules targeting RNA has also been demonstrated with Risdiplam, the first FDA approved small molecule RNA therapeutic. Risdiplam acts by modifying RNA splicing to selectively increase levels of functional protein and is used to treat spinal muscular atrophy1.To successfully enable this RNA focused strategy hit discovery must overcome several challenges. Alongside building expertise in RNA biology and understanding how to best exploit this in drug discovery, we need to re-align methods that have historically been applied to protein targets to allow successful, high-throughput hit identification and build new approaches that may offer a competitive advantage. Within the high-throughput screening centre at AstraZeneca we have started to implement a range of cell-based, biochemical and biophysical approaches to identify small molecules targeting RNA. Here, we will discuss these strategies and our current experience with targeting RNA by high-throughput screening. 1. Ratni, H.; Ebeling, M.; Baird, J.; et al. Discovery of Risdiplam, a Selective Survival of Motor Neuron-2 (SMN2) Gene Splicing Modifier for the Treatment of Spinal Muscular Atrophy (SMA). Journal of medicinal chemistry 2018, 61, 6501-6517.
A high-throughput microfluidic mechanoporation platform for intracellular target engagement characterization of macrocyclic peptides
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Open to view video.  |   Closed captions available Cyclic peptides are poised to target intracellular protein-protein interactions that have been historically difficult to drug using small molecule approaches. However, characterization of functional target engagement of peptides in the intracellular environment poses a challenge due to the steep trade-off in permeability that accompanies their increased molecular weight. Recent advances in microfluidics have enabled permeabilization of the cytoplasmic membrane via mechanoporation, resulting in intracellular delivery of impermeable macromolecules with minimal cell perturbation. However, the application of these technologies in cell based assays is limited due to the manually intensive process of mixing cells and payloads prior to processing. In this work, we show that cells are transiently permeable after microfluidic vortex shedding and that low molecular weight macromolecules can be delivered to the cytosol upon rapid exposure after cells are processed. To increase the ability to screen peptides, we built a system, DµVS (dispensing-microfluidic vortex shedding), that integrates a microfluidic vortex shedding chip with inline microplate-based dispensing. To do so, we synced an electronic pressure regulator, flow rate sensor, on/off dispense tip valve, and an x-y motion control platform in a software-driven feedback loop. Using this system, we enabled dispensing of low microliter-scale volumes of mechanoporated cells to hundreds of wells on microtiter plates in several minutes. We validated the intracellular delivery of an impermeable peptide directed at MDM2, a negative regulator of the tumor suppressor p53, using a click chemistry- and NanoBRET-based cell permeability assay in 96-well format. Additionally, we utilized DµVS to identify functional activity of otherwise cell-inactive MDM2-binding peptides using a p53 reporter cell assay in 96- and 384-well format. Overall, DµVS can be combined with downstream cell assays to investigate intracellular target engagement in a high-throughput manner, both for improving structure-activity relationship (SAR) efforts and for early proof-of-biology of non-optimized peptide (or potentially other macromolecular) tools.
Ignite Theater
Abterra Biosciences, Inc.
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Open to view video.  |   Closed captions available "The Innovation: Antibodies are one of the fastest growing classes of therapeutics, with approved uses across oncology, autoimmunity, and infectious diseases. However, only a fraction of antibodies that leave the discovery stage make it to market. A leading cause of failure is lack of efficacy, the drugs don’t work in patients. Current methods for antibody discovery rely on animal immunizations and in vitro antibody library screening, which generate a large panel of candidate antibodies that bind a target but do not translate to effective therapies. The best source of effective therapeutic antibodies is patients whose immune systems encountered the disease and optimized antibodies to overcome it. Antibodies generated in response to disease are optimized for therapeutic use not simply binding to a target. Single B cell screening approaches can be used to discover antibodies directly from human patients, however, B cells are an imperfect proxy for the antibodies selected by the immune system to combat a disease. Antigen-experienced B cells are rare in blood, and antibody proteins are 10 billion times more abundant. Relevant antibodies are present in many copies, while they may only be encoded in a handful of B cells. Furthermore, most B cells encode antibodies that are never selected for production at high levels in the blood, which can lead scientists to chase false leads. Alicanto® replaces the need for single B cell screening by performing serum antibody screening instead. In the first stage, relevant antibodies are enriched from patient serum using affinity purification against a target. The enriched antibody sample is subjected to bottom up mass spectrometry analysis in which the antibodies are digested with proteases, analyzed by LC-MS/MS, and sequenced by in-house computational tools. Concurrently, circulating B cells are sequenced by next-generation sequencing to create an antibody repertoire. The proteomic information is integrated with the antibody repertoire. The Alicanto discovery engine is fed the repertoire and proteomic information and uses a proprietary algorithm to identify candidate antibodies that are present in the patient serum and relevant to the target. See the attached slide overview of Alicanto. A second generation of Alicanto will expand the use cases and eligible samples on which we can perform antibody discovery. Alicanto 2nd generation will identify candidate antibodies directly from antibody protein, without the need for a B cell-derived repertoire. This will enable antibody discovery on samples where there are no viable cells retained, as is the case in many clinical trials, or where antibodies are obtained from non-blood fluids such as cerebral spinal fluid where few cells are present. Alicanto® is a drug discovery technology that uses multi-omics (genomics, transcriptomics, and proteomics) data sets to deliver better antibody therapeutics. The technology would be relevant to attendees in the Omics technology session.The Technical Objectives and Challenges: Alicanto® is a human drug discovery technology, however, it is extensible to any species with a jaw and a backbone. The first technical objective was to validate the Alicanto process in well controlled animal studies. We’ve successfully discovered antibodies from immunized rabbits, llamas, and alpacas. We currently are generating revenue by using Alicanto as part of a custom antibody discovery service. Our second technical objective is to complete a human antibody discovery pilot with Alicanto in infectious diseases. Unlike in hyperimmunized animals, a key challenge in adapting Alicanto for use in humans is the smaller volume of blood that can be obtained from patients as well as the lower concentration of relevant antibodies. We’ve grown our team to include scientists with protein purification expertise to optimize the Alicanto workflows for this case. In addition, we’ve expanded our in-house mass spectrometry capabilities with an ultrasensitive Orbitrap instrument that can analyze smaller quantities of antibody. In 2021 we collaborated with Vanderbilt University Medical Center to identify Ebolavirus neutralizing antibodies from a convalescent patient, and we have ongoing COVID-19 projects that will finish in Q4 2022. A third technical objective is to apply Alicanto to antibody discovery for a cancer indication. Aberrant expression or post-translational modification of cell surface proteins, mutated proteins, and oncofetal proteins all illicit antibody responses to tumors. The challenges associated with antibody discovery in this setting is the same as for infectious disease (limited sample and low antibody concentration) only more so. The function of antibodies to cancer targets is varied including antagonist and agonist functions, a need for precise binding to small differences present on cancer cells versus healthy cells, and, in some cases, the need to identify the target of a functional antibody detected from serum. We’re addressing these challenging scenarios through a combination of optimization of protein purification, developing new methods on the mass spectrometer, and creating new computational tools for analyzing the antibody repertoire. A final technical objective is the development of Alicanto second generation. To enable sequencing, antibodies must be digested into peptides and reassembled informatically into a full-length protein. The key challenge to the development of this technology is the accurate assembly of peptides in a complex mix of proteins that have significant homology to one another. We’ve filed a patent covering methods of performing assembly to recover antibody sequences and won an $1.2M SBIR award in 2021 to fund the development. We envision Alicanto as a technology that will be used as part of an antibody discovery service that we offer to pharmaceutical and biotechnology partners.The Market Opportunity: Our customers are developing the next blockbuster antibody therapeutics, the market for which exceeded $160B in 2019. Outsourcing has become ubiquitous for early antibody discovery, with >$2B spent by the pharmaceutical industry on antibody discovery outsourcing each year. We seek partnerships with pharmaceutical companies to discover new drug candidates using Alicanto® in oncology and infectious disease. Through our partnership business model we gain access to both the outsourcing market through upfront research fees and milestone payments, as well as the therapeutic sales market through royalties. Alicanto is a disease agnostic technology, but expertise in our customer’s domains is essential for winning their business and successfully executing projects. Our first segment of the market will be solid tumor cancers including small cell lung cancer and triple negative breast cancer.The Company and Team: Abterra Bio is a spin out from the University of California – San Diego Computer Science Department, and builds on the core technologies for data analysis pioneered in the labs of Drs. Pavel Pevzner and Vineet Bafna. The management team, Drs. Natalie Castellana, Stefano Bonissone, and Anand Patel together with the founders pioneered novel methods for antibody sequencing and analysis. The company began life as Digital Proteomics with the mission of developing software for proteomic analysis. In 2021 in response to customer demand, the company pivoted to antibody discovery and sequencing services, renamed to Abterra Biosciences and incorporated as a C corporation. The management team has grown the business to 10 employees, established a fully functional genomics and proteomics lab, and won >$6M in NIH SBIR grants to fund research & development. In 2021 we closed a seed financing for the expansion of our proteomics and mass spectrometry capabilities as well as complete pilot studies of Alicanto for human antibody discovery. We are joined by advisors Dr. Nathan Trinklein, who has deep expertise in therapeutic antibody development for cancer, and Dr. Sammy Datwani who brings broad expertise in biotechnology and business strategy. Abterra Bio is generating revenue through the commercialization of three technologies, Alicanto®, Reptor, and Valens. To date we’ve worked with >65 pharma and biotech companies, including 7 of the top 10 pharma companies, to support their antibody development projects.Technology Topical Focus (optional): Conference Selection: SLAS2023 International Conference and Exhibition, Omics track"
Saguaro Technologies
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Open to view video.  |   Closed captions available  |  60 minutes "The Innovation: The first innovation that Saguaro started commercializing this year is ChromaLive, a completely new generation of cell dyes. ChromaLive enables scientists to leverage laboratory automation practices like never before. It allows indefinite live-cell assays, the detection of many cell phenotypes - such as autophagy, stress, apoptosis and more - all at once, and does not require washing steps or fixing. Since the ChromaLive dyes are non-toxic to cells, the need for an additional plate for each assay time point of interest is removed. In addition, ChromaLive dyes’ spectral profile and staining patterns change depending on cell state, so it can be used to detect many phenotypes at once, allowing scientists to use one plate in total, instead of one extra plate for each phenotype of interest. Lastly, ChromaLive only becomes fluorescent once inside a cell, therefore removing the need for a washing step, which can affect reproducibility and limit throughput. These three unprecedented aspects of ChromaLive allow scientists to scale up the size and relevance of their cell-based screening experiments. The proprietary technology was developed by Dr. David Andrews from Sunnybrook Research Institute and licensed exclusively to Saguaro for further development and to bring the new technology to market. For his own research purposes, Dr. Andrews needed dyes that would be non-toxic to cells and that only became fluorescent once inside the cells to avoid the need for washing steps. Given that no commercially available dyes were fit for his purpose, he took on the initiative to develop new dyes himself. To his own surprise not only did he develop dyes with these exact features, he also discovered that their spectral and staining properties changed depending on cell phenotype. Those changes can be captured by multi-parametric image analysis to be able to quantify and classify cells according to their respective phenotype. The dyes have the potential to drastically improve drug discovery by enabling scientists to capture new biological data that wasn’t possible otherwise. Their unique set of features are particularly suited to perform high content screening on live cells for extended periods of time. Many currently available HCS systems now offer these capabilities, but the application itself is extremely limited due to the lack of suitable fluorescents dyes. Furthermore, the use of physiologically relevant cell culture models such as 3D cell cultures and organoids is in part limited by currently available dyes, which cannot get uniform staining throughout 3D models without altering them. Since the ChromaLive dyes are non-toxic and they only become fluorescent inside the cells, scientists can grow their 3D models along with the dyes mixed in the culture medium. This allows uniform staining throughout and therefore enables scientists to capture new information on cell behavior in three dimensions and over time.The Technical Objectives and Challenges: Since this next-generation technology comes with a completely new set of features, it paves the way for drastic improvements in a very wide range of applications. At the same time, even if most of the technology’s risks have been mitigated, there is still work to be done to find and reach the limit of its capabilities. This will help confirm the extent to which it can be used, out of all the potential applications. The dyes are already being commercialized and in the hands of many companies and institutions worldwide, but in order to accelerate its adoption, the main challenge is to generate as much data as possible on their use with cell cultures in a short amount of time. In terms of non-toxicity, previous work has proven that the dyes appear completely non-toxic compared to alternatives. They had no effect on cell proliferation for a wide range of cells, from immortalized cell lines, to primary-derived cells and stem cells. It has never displayed any effect on cell viability or proliferation, even in cell cultures grown for more than 25 days. It was used on various highly sensitive stem cells (pluripotent and brain tumor stem cells) and had no effect on their viability, nor their differentiation, which had proven impossible with other dyes. Most of its mechanism of action is understood, but more work could always be done to understand further how it could affect the cells in any way, if at all. In terms of how many phenotypes can be identified using the dyes, the potential is still as high as the number of phenotypes one is interested in measuring, but the extent is yet to be validated given how broad the applications can be. So far, using multi-parametric image analysis, previous work has proven that the dyes are suitable for monitoring most common phenotypes of interest such as cell viability, apoptosis, ER stress, autophagy, quiescence and necrosis. The dyes have also been used successfully to distinguish un-differentiated from differentiated cells in stem cell cultures and distinguish different types of cells in co-culture models. Finally, ChromaLive is a new family of dye molecules and Saguaro is working on developing a panel of dyes with various spectral and staining properties to extend further in the total number of applications it can be used for. New molecules are continuously being tested for this purpose. The challenge is to change the spectral properties while also keeping the dyes non-toxic and keeping them only fluorescent once inside the cells. Nonetheless, in terms of spectral properties, the first dye product that Saguaro started commercializing is already fit for most applications.The Market Opportunity: The most appropriate customer profile in the near term who will benefit from ChromaLive and adopt it quickly is the drug discovery scientist that already has experience with high-content screening and multi-parametric image analysis. The main pain point is that the throughput is very limited by current dyes, which yield limited data in terms of cell biology and how it evolves over time. For stem cell and cell painting experiments, each plate can only be used for one time point, because the dyes are toxic to cells, require washing and fixing. 3D cell cultures cannot be stained evenly without altering the cells, resulting in very limited data on cell biology. In addition, most dyes or assay reagents are specific to one sub-cellular structure or one mechanism of action at a time, which can lead to false positive and false negative results. For example, caspase assays are commonly used to measure apoptosis, but there are caspase-independent pathways that also lead to apoptosis. In contrast with such specific assays that measure the level of a biomarker associated with a cellular state, ChromaLive provides an unbiased look into cellular biology, akin to a cell painting assay but in live cells. That is because ChromaLive dyes indiscriminately stain all membranes in a cell, highlighting how differently it appears with changing cell states. For those reasons, their use in HCS combined with multi-parametric image analysis provides an unbiased way to measure many cellular phenotypes simultaneously, for as many time points as needed.The Company and Team: Saguaro is a Quebec-based startup that develops and distributes next-generation cell culture products to improve drug discovery on two fronts. The first one is to enable scientists to capture new biological data to help them better evaluate the real performance of their drug compounds. The second is to enable them to work with more physiologically relevant in vitro models and be able to use them at large scale. Both co-founders, Louis Turcotte and Felix Lavoie-Perusse, have combined technical backgrounds in biochemistry and engineering, while also having held leadership positions in high-tech companies, working in business development and management. Louis is CEO, while Felix is CCO and focuses on the company’s commercialization efforts. They have raised a pre-seed round in January 2022 from two angel investors: a CEO and a CFO of a biopharma company traded on NASDAQ. Saguaro now consists of five employees, including two PhDs working exclusively on developing and expanding its portfolio of technologies. The startup can also count on external support from its advisory board, consisting of both angel investors along with Dr. David Andrews from Sunnybrook Research Institute and Ella Korets-Smith from Virica Biotech. ChromaLive is the first technology that Saguaro launched early in 2022 and has attracted many early customers worldwide, including 6 of the largest pharmaceutical companies in the world. Saguaro is now looking to raise its seed round to accelerate commercialization efforts for ChromaLive while also expanding the company’s innovative product portfolio.Technology Topical Focus (optional): Conference Selection: SLAS 2023 International Conference and Exhibition"
Picoliter Thin Layer Chromatography (PicoTLC) to Assay Lipid Signaling in Single Cells
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Open to view video.  |   Closed captions available  |  60 minutes "Introduction. Thin layer chromatography (TLC) is a widely used analytical technique for many applications, but its use for extremely miniature samples, such as a single cell with a volume of ~1 picoliter, has not been realized to date. A major challenge is that the dimensions of the adsorbent layer in conventional TLC significantly exceed that of single cells. To address this challenge, we have developed a new microfabricated TLC platform by creating an array of microchannels filled with monolithic porous silica. The channels reduce the lateral diffusion and confine the movement of compounds along the microchannels, enabling sample separation and detection of samples of the picoliter volumes.The platform is termed picoliter TLC (PicoTLC). Materials and Methods. The PicoTLC microchip was fabricated by combining sol-gel chemistry with microfabrication. PicoTLC incorporates an array of microscale channels made from a highly porous monolithic silica. The channels were designed to accept picoliter-scale volume samples and possessed a width and depth for each channel of 80 μm and 13μm, respectively. Droplets of fluorescent compounds with a volume of ~9 picoliter were spotted on the microchannels and separated upon exposure of the channel inlet to organic solvents. To demonstrate single-cell analysis, single K562cells loaded with sphingosine-CY5 were spotted on the microchannels. The cellular metabolites of sphingosine-CY5were extracted from the individual cells and separated using PicoTLC. Results and Discussion. To demonstrate the utility of PicoTLC, model lipid compounds such as fluorescein-conjugated sphingosine & sphingosine-1-phosphate were spotted at the inlet of the microchannels, followed by separation. The results demonstrated that PicoTLC is capable of separating picoliter samples of organic molecules. To further demonstrate the power of PicoTLC, single cells loaded with sphingosine-CY5 were spotted on the microchannels. Separation was initiated by the application of separation solvent and the fluorescence of CY5 was measured within the channel. Two fluorescent analytes (sphingosine-CY5 and sphingosine-1-phosphate-CY5) were extracted from the cell and separated along the microband in 4 min (resolution = 1.8). Sphingosine kinase (SK) activity as evidenced by formation of sphingosine-1-phosphate-CY5 was heterogeneous across the single cells. To confirm that the conversion of sphingosine-CY5 to sphingosine-1-phosphate-CY5 was due to SK, cells were incubated with the SK inhibitor PF543 and then assayed. As expected, the formation of sphingosine-1-phosphate-CY5 peak was prevented in the cells treated with the inhibitor. Analysis of single cells either treated with PF543 or DMSO demonstrated the inhibition of sphingosine kinase in the drug-treated cells (p-value ≤0.0001). Conclusion. We have developed a TLC technology for separating the components of picoliter-scale specimens including single cells. Further, PicoTLC was demonstrated for the assay of sphingolipid signaling activity in single cells. We envision PicoTLC will have potential applications in many areas where miniature specimens and high-throughput parallel analyses are needed."
The Neuro’s Early Drug Discovery Unit: Open to partnerships for innovative neuroscience drug development
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Open to view video.  |   Closed captions available  |  60 minutes Working with patient-derived induced pluripotent stem cells (iPSCs), The Neuro’s Early Drug Discovery Unit (EDDU) ( is focused on accelerating the discovery of new treatments for neurological disorders and promoting sharing of knowledge, scientific research data, and materials, benefitting patients worldwide. Our team of more than 45 members is focused on the applications of iPSCs across both fundamental and translational discovery projects in partnership with academic and industry users. Combining expertise with iPSCs, CRISPR editing, 2D and 3D neuronal models, assay development, and automated high-content screening we aim to better understand why a disease is arising and to work with partners on innovative approaches towards developing new technologies or therapeutics. To date, we have generated > 130 iPSC lines from controls and individuals diagnosed with a range of neurodegenerative or developmental disorders, in addition to taking advantage of our established CRISPR editing pipeline to generate a number of knockout and knockin lines, all available to be accessed by external users. Our state-of-the-art facility is located at McGill University in Montreal, Canada and major equipment is available to handle the demands of collaborative projects requiring proficiency in molecular biology, protein purification, histology, microscopy and data storage, tissue dissociation and flow cytometry, and automated cell handling. With the latest in high-content imaging platforms that include the Opera Phenix Plus Automated High-Content System and ImageXpress from Molecular Devices, coupled with a suite of liquid handling equipment, we are well established to develop a broad range of image-based assays with both 2D and 3D neuronal models. In summary, the Neuro’s EDDU combines our capabilities with those of our collaborators to 1) apply iPSCs and iPSC-derived brain cells and organoids to study the molecular basis of neurological diseases; 2) develop new tools and technology in disease modelling and target engagement that will help to identify potential therapies; and 3) translate newly developed assays onto an automated high-throughput platform that can be integrated with preclinical drug screens.
Tessara Therapeutics: RealBrain® Platform for Neural Drug Discovery
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Open to view video.  |   Closed captions available  |  20 minutes The Innovation: Tessara Therapeutics has engineered the optimal micro-environment to activate neural stem cells to develop into fully functional mini-brains in vitro. The RealBrain® 3-dimensional (3D) human neural micro-tissues significantly advance our ability to accurately model the human brain, and will improve the efficiency of the drug discovery process, and provide a new therapeutic approach to a range of neuro-degenerative diseases. By converging streams of innovation in neuroscience, biomaterials, industrial automation, artificial intelligence, and data analytics, Tessara now has the first 3D neural in vitro model that is fully human, mature and functional in only 3 weeks, optically clear, highly reproducible, requires only a single culture medium, is easily scaled up using automated liquid handlers, and can accurately model both normal and disease states including Alzheimer’s. The technology behind the RealBrain platform combines a range of neuroscience and biomaterial insights generated at Universities in the US, Europe, and Australia. Tessara is now completing scale up and beginning commercialisation of the RealBrain® Platform to generate a new “gold standard” platform for neurological drug screening, with a vision to break therapeutic barriers in neurology and realise a world in which we can protect, restore and rebuild the brain.The Technical Objectives and Challenges: Tessara combines human neural stem cells with proprietary biomaterials in the optimal 3D micro-environment that instructs the cells to activate their endogenous neurodevelopment programs, self-organise and mature into RealBrain® human neural tissue. In the past 12 months, Tessara has taken the technology that had been validated in the laboratory, and scaled it up ready for commercial applications. The scale-up has involved two distinct processes: 1) a 1000 fold scale up in the chemical synthetic methods required for the production of Tessara's proprietary biomaterial components that are mixed to encapsulate the cells in a 3D support Matrix; and 2) miniaturization and scale up of the casting and culturing technology required for commercial-scale manufacturing of the RealBrain® micro-tissues for 96- and 384-well plate formats. These efforts have resulted in new IP, including biomaterials compositions and proprietary manufacturing trade secrets. This scale-up work now provides us with a 3D in vitro platform that combines ease of handling at high-volume and optimal reproducibility with the well established high physiological relevance of full functional human neural networks growing in 3D dimensional culture. This combination is now being used by drug development companies via our early access program to evaluate mechanistic and toxicological endpoints associated with new drug candidates in both normal and Alzheimer’s disease variants of the RealBrain model. In parallel, Tessara is also performing proof-of-concept studies for use of the RealBrain micro-tissues as a cell-based therapy. Micro-tissues have been introduced into neural injury sites in an in vivo animal model, and engraftment and persistence of the introduced cells has been confirmed. These results open the door for a new regenerative medicine approach to treat traumatic and degenerative brain injury.The Market Opportunity: Our target customers for the RealBrain platform are drug discovery companies undertaking target validation and lead optimisation. The fully function, human 3D models provide high physiological relevance, and can follow-on from early-stage compound hit screens, whilst then also reducing the need for in vivo animal tests. Tessara’s business model is not to offer CRO services. Instead, we are partnering with large established CROs, and will act as a technology partner to provide an ongoing supply of validated applications and assays of the RealBrain 3D micro-tissue platform. Pharma market reports confirm that evaluation of in excess of 70,000 neurologically-relevant lead compounds is outsourced to CROs each year. With average spend of $30,000 per lead, this generates a market of $2Bn. Additional market potential is also available via the cell therapy applications. Early license deals in the Parkinson’s Disease indication have raised between $16-200m in the period from 2016-2021.The Company and Team: CEO: Dr Christos Papadimitriou. Background in biomaterials and regenerative medicine. CSO: Professor Paul Adlard. 25 years experience in drug development and brain injury, including Alzheimers, and TBI CBO: Christopher Boyer. Originally trained in neural drug development, now 15 years experience in business development and licensing. COO: Peter Girling. Background in stem cells and 3D model development, and the establishment of cell production facilities. Advisors: Professor Jenniffer Ellissieff (JHU), Professor David Finlekstein (The Florey Institute). Dr Carmel O'Brien (CSIRO)Technology Topical Focus (optional): Conference Selection: SLAS 2023
Innovative separation platform via spongy monoliths for proteins, antibodies, EVs, viruses, and cells
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Open to view video.  |   Closed captions available  |  60 minutes "Previously, we developed a spongy-like porous polymer consisting of poly(ethylene-co-glycidyl methacrylate) with continuous macropores that allowed efficient in situ reaction between the epoxy groups and proteins of interest. Immobilization of Protein A on spongy monolith enabled high-yield collection of immunoglobulin G (IgG) from cell culture supernatant even at high flow rate. We believe that this new platform will be useful for variety of protein-based reactions with rapid flow rates and low costs. In present study, we focused on the specific separation of glycoproteins by the recognition of sugar chains using a spongy monolith (SPM) as a separation medium. As a fundamental study, we prepared SPMs modified with a few lectins for lectin affinity chromatography (LAC). We employed Sambucus sieboldiana agglutinin (SSA), which interacts effectively with sialic acid, and concanavalin A (ConA), which interacts effectively with mannose/glucose, were immobilized onto the surface of the SPM. After packing the modified SPM into the column, the adsorption selectivity due to the lectin affinity was evaluated. Additionally, the collecting procedures were also optimized by changing the elution conditions. Additionally, new SPMs were developed for the separation of an extracellular vesicle, exosome and a corona virus, SARS-CoV-2. In former case, the specific lectins were immobilized onto a SPM and the selective separation of exosomes were successfully achieved. In case of the virus separation, an antibody was modified onto a SPM for the selective adsorption of a spike protein on SARS-CoV-2. Then, we finally achieved to selective concentration of SARS-CoV-2 from a pseudo salivary sample. According to these applications, newly developed SPMs can be used for the rapid and effective separation of the bio-related targets, such as proteins, glycoproteins, extracellular vesicles, viruses, and cells. (1) Kubota, K.; Kubo, T.; Tanigawa, T.; Naito, T.; Otsuka, K. Sci. Rep. 7: 178, 2017"
An Automation Powered Clinical Testing and Research Core Facility Platform
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Open to view video.  |   Closed captions available  |  30 minutes Laboratory automation advances life-science innovation by igniting scientific discovery and experimentation. The decision to automate your research can be motivated by a demand for increased throughput, enhanced reproducibility, improved turn-around time, expanded walkaway time, or a combination of all of these. The COVID-19 pandemic prompted Boston University (BU) to develop, build, and deploy a high throughput sample RNA extraction and PCR processing CLIA-approved facility. Between 2020 and 2022, the BU DAMP (Design, Automation, Manufacturing, Processes) Lab harnessed the power of automation to process over 2.3 million samples for SARS-CoV-2. The lab installed seven Hamilton Microlab STAR liquid handling robots with three unique deck layouts and execution methods to accomplish this level of throughput. Automating portions of this assay provided a ten-fold increase in daily sample throughput, maintained a rapid turn-around time, reduced human error, and saved an estimated 20,000 labor hours. This enabled the lab to test at a scale that dramatically increased campus safety and allowed the BU community to confidently return to in-person learning. The testing capacity as represented by these metrics would not have been possible in a traditional lab setting. As a core facility at BU, the DAMP Lab is building on the infrastructure and experience of the BU Clinical Testing Lab to implement automated methods for over 45 different molecular biology protocols. This expansion of the DAMP Lab’s automation capabilities as well as the incorporation of a cloud-based interface will streamline collaboration within and beyond BU, empowering researchers to focus on results rather than laborious and repetitive benchwork. In addition to the benefits of improved throughput, walk-away time, and turn-around time, researchers will gain the useful data that comes with scaling up a manual process. Analytical data will be collected from each DAMP Lab service project to ascertain metrics on labor savings, and how the throughput was affected. This will allow researchers to move forward with an educated understanding of their capabilities with automation and give them insight into future project planning, staffing, equipment scheduling, and purchasing. The combination of biological services, data analysis, automation, and dissemination of standardized protocols are core functions of the DAMP lab. The DAMP Lab believes that automation standardization and cloud based collaboration will be a major driving force for research and innovation in life sciences research.
Igniting Drug Discovery: Pharma Scale Organ-on-Chip Powered by Image-Based AI
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Open to view video.  |   Closed captions available The Innovation: Drug Discovery is a costly and lengthy process. It is estimated that it takes on average 1$ billion and 10 years for a drug from pre-clinical testing to approval. Lack of sufficiently predictive methods for target validation and for identifying and optimizing therapeutic candidates is currently considered to be the main technical roadblock in drug discovery. Human microphysiological systems (MPS), such as human organ chips, are emerging tools aimed to address this challenge. Xellar Inc., used a three-pronged approach to drug discovery by combining Organ-on-a-Chip technology, multicellular 3D disease modeling, and Artificial Intelligence (AI)/machine learning to enable spatiotemporal profiling of disease states and drug responses. By increasing the predictive validity during preclinical development, our ultimate objective is to reduce the drug discovery attrition rate and expedite the transition of drugs from the laboratory to the clinic. What sets us apart from other companies in the organ chip field is our unique expertise in microfluidic organ chip design, fabrication, disease modeling, and phenotypic drug discovery. We are the first company in the world that combines dynamic 3D culture, lab automation, and computer-vision-based machine learning for new drug discovery. Our strategy involved multiple topics that members of the SLAS will be interested in, such as microfabrication, imaging, and lab automation.The Technical Objectives and Challenges: In addition to providing biologically relevant complexity, our microfluidic device and platform are designed and developed for scalability, allowing high-throughput screening and lab automation compatibility, to meet the efficiency needs of drug discovery and development. At Xellar Biosystems, we excel at complexity and scalability to accelerate the world of drug discovery and development. Our microfluidic-based Organ-on-a-Chip technology recapitulates the multicellular microenvironment of the organ, incorporating vascularization, biomechanical structure and forces, and paracrine signaling experienced in vivo, providing an excellent in vitro model suitable for drug discovery. Downstream morphological, secretory, and multi-omics profiling of these complex organ models using AI and machine learning analysis, allows the development of multiplexed profiles of different cellular populations, permitting the detection of subtle biologically relevant responses and phenotypes. Our chip design utilizes a combination of surface modification and physical microstructure design to allow membrane-free 3D tissue culture. Associated patent applications are pending. We have also designed a micropumping systems which allows a controlled microphysiological environment like uni-directional perfusion and physiologically relevant oxygen and shear stress level for different organ types. During the developmental phase, we have tested many different materials and fabrication techniques in order to achieve optimized quality in terms of biocompatibility, drug absorption, and optic performance.The Market Opportunity: Our long-term objective is to build a portfolio of drug pipelines. However, our near-term commercial focus is to create various disease models for testing drug toxicity and drug efficacy using our proprietary organ chip devices. We do not plan to commercialize our organ chip devices as a product, but instead use them to provide integrated discovery and development services to academic labs, biotech, and large pharmaceutical companies. In parallel, we are investigating opportunities to codevelop therapeutics with major pharmaceutical companies.The Company and Team: Our company was founded in early 2022 in Boston, Massachusetts. In August of 2022, we completed a $10 million seed round co-invested by Legend Capital, ZhenFund, and Yayi Capital. Dr. Xie Xin, our CEO and co-founder, completed his postdoctoral research at Harvard University on organ-on-a-chip and engineered living systems and worked for TransMedics, Inc. (Nasdaq: TMDX), a global leader in organ transplantation device research and development. Most of the founding team come from prominent multinational biopharmaceutical corporations and prestigious scientific research institutions, such as Harvard University, MIT, and Stanford University. They have extensive experience in industrial pharmaceutical product development and cutting-edge research and development in biological and AI technologies. Dr. Haiqing Bai, the leader of our preclinical platform, led one of the first human organ chip studies that resulted in an investigation new drug (IND) application. Our Scientific Advisory Board (SAB) includes Professor Y. Shrike Zhang from Harvard University who is an expert in bioengineering and 3D organ printing and professor Polina Golland of the Artificial Intelligence Laboratory at MIT who is the founder of Cell Profiler, the most widely used software for computer vision and cell morphology analysis. We have collaboration with Professor Donald Ingber at the Wyss Institute at Harvard University who is the Founding Director of the Wyss Institute and a pioneer in the organ-on-chip field. We also collaboration with Dr. Ann Carpenter at MIT who is an expert in the field of image analysis for cell biology and artificial intelligence for drug discovery.Technology Topical Focus (optional): Conference Selection: SLAS2023 International Conference and Exhibition
QES, a novel approach for the analysis of complex biological systems
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Open to view video.  |   Closed captions available The increasing availability of biological and biomedical data, such as DNA sequences, has set the stage for the development of AI solutions that capture the complexity of health and disease. However, genetics provides only the blueprint, and proteins, metabolites, and other molecules are the effectors of health and disease. There are more than 1,000,000 proteoforms and 200,000 metabolites, fluctuating in form and abundance in response to internal and external queues in the human body. Measuring this complexity at scale requires tradeoffs like limiting the breadth of the analysis (e.g., ELISA) or restricting the number of samples and statistical power in exchange for a broader view (e.g., LC-MS). To truly allow AI to impact bioscience research and, eventually healthcare, we need an approach that breaks incrementalism and produces reliable data at scale. To address this challenge we have taken inspiration from how the sense of smell copes with the complexity of odors where a finite number of receptors can detect a vast chemical world by combinatorial activation. We have coupled this approach with the concepts from a legacy spectroscopic technique, Inelastic Electron Tunneling Spectroscopy (IETS), where molecular vibration frequency data is encoded in the current arising from the transfer of electrons between electrodes when cooling the sample at ultra-low temperatures. Our Quantum Electrochemical Spectroscopy (QES) utilizes broad electrochemical sensors to create a high dimensional vibrational signature of the molecular species of a biological specimen. Then, the spectrum is uploaded as a digital twin of the sample, deconvoluted, and parsed for inferencing using previously trained models. - The QES platform is amenable to over-the-air updates of new analytes and signatures since it does not require target-specific reagents to perform the assays. - In addition, the simpler assay without reagents makes the measurement more reproducible and comparable between runs, sites, etc. Coupled with the fast operation (1 step, 30m), small sample requirement (2-4 ul), and small footprint, we believe this data acquisition approach will change how much and how frequently we can acquire data closer to the biological systems. in this presentation we will walk the audience through the key concepts of QES, its analytical power and its market potential.
Accessibility in the Lab - The Accessibility Pipeline Panel Discussion
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Open to view video.  |   Closed captions available From the early stages of education all the way to entering the workforce, how do we ensure that the lab is a welcoming environment to all individuals who have the passion and the aptitude for scientific research? In what ways are we unwittingly excluding individuals with disabilities, and in what ways are we hindering the progress of life sciences research by preventing full participation of individuals with unique life experiences and perspectives? Join the discussion with this panel of accessibility experts as we seek to answer these questions and many more surrounding the importance of ensuring accessibility in the lab.
Poster Theater
Development of innovative LightSpot® fluorescent ligands for the specific detection, localization and quantification of the Permeability-glycoprotein (P-gp), on Triple Negative Breast Cancer preclinical models
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Open to view video.  |   Closed captions available The Permeability-glycoprotein (P-gp, also known as ABCB1) is the major MDR (Multi Drug Resistance) protein playing a role in cancer drug resistance. This membrane-transporter confers natural or acquired cellular resistance to many anticancer agents by limiting their intracellular accumulation and thus reducing treatment outcomes. In this way, P-gp has long been considered as a potential resistance biomarker to help in treatment efficacy prediction. However, up to date, successful translation of clinically validated methods aiming to explore P-gp expression level in tumors has remained very limited. This was principally attributed to methodological limitations associated to antibody-based assays. Among these limitations, interindividual P-gp epitope polymorphisms, and lack of antibodies penetration inside cells and cell masses were principally described. In this context, the development of small-size-molecule-based imaging approach appears to be for us, an innovative and alternative strategy to overcome these limitations.
Supported Gel Slabs: A Promising Method for Generating Tumor-likeStructures and Screening Toxicants in a 3D Environment
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Ultra-high content analyses of circulating and solid tumor cells
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Open to view video.  |   Closed captions available Metastatic spread of cancer is responsible for >90% of all cancer-related deaths highlighting the need to better understand the cellular and molecular mechanisms underlying this phase of cancer, and to monitor disease as it progresses. Our team combines the discovery of a novel circulating tumor cell, that co-expresses cancer cell and immune cell proteins (called a hybrid cell), cutting-edge multiplex cyclic immunofluorescence (cyCIF) for interrogation of multiple proteins on the same tissue section or blood smear, and powerful software (QITissue) that allows for the visualization and analysis of many biomarkers at once. Additionally, with the help of deep learning segmentation algorithm (Mesmer) this combination creates a platform that can allow for non-invasive, real time monitoring of disease evolution. We set out to determine if disseminated or peripheral blood hybrid cells (called circulating hybrid cells, CHCs) harbored identical phenotypes as tissue-bound hybrid cells. To do this we generated and validated an array of cancer, immune, structural, and phenotypic-specific cyCIF ab-oligos then probed patient matched tumors and peripheral blood specimens for discrete and aligned phenotypes. We identified a high degree of heterogenous expression among tumor and circulating hybrid cells. Further, we demonstrate a subset of tumor-hybrid phenotypes are detected in patient matched CHCs. These findings lay the foundation for further developing detection and phenotypic analyses of CHCs as a potential non-invasive (i.e., liquid biopsy, blood-based biopsy) readout for tumor burden.
Enabling Late-Stage Drug Diversification by High-Throughput Experimentation with Geometric Deep Learning
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Open to view video.  |   Closed captions available Abstract: Late-stage functionalization (LSF) represents an economical approach for optimizing the properties of drug candidates. However, the chemical complexity of drug molecules often renders late-stage diversification challenging. Aiming to address this problem, an LSF platform based on high-throughput experimentation (HTE) and geometric deep learning is introduced. Our study focuses on late-stage borylation reactions, which provide opportunities for extending structure-activity relationships (SAR) as well as modulation of absorption, distribution, metabolism and extraction (ADME) properties through structural diversification.A comprehensive literature analysis delivered 1301 reaction conditions extracted from 38 (borylation) publications. This high-quality data set provided the foundation to identify 24 suitable reaction conditions for automated HTE. To assess the relevant chemical space for LSF, 1174 approved small molecule drugs were clustered by chemical diversity. In total, 23 drugs from these different clusters, twelve common fragments and five simple substrates were selected and subjected to HTE borylations to deliver an experimental data set containing 956 reactions. A geometric deep learning platform was developed consisting of a set of different graph transformer neural networks (GTNNs) tailored to learn three targets, namely, (1) binary reaction outcome for novel substrates, (2) reaction yield, and (3) regioselectivity. To quantify the influence of steric and electronic effects on model performance, the input molecular graphs were featured using two-dimensional (2D), three-dimensional (3D) and quantum mechanics (QM) augmented information. The GTNNs were trained and optimized on 1301 and 956 reactions originating from literature and in-house experiments, respectively.The resulting computational models correctly predicted novel reactions with known and unknown substrates with a balanced accuracy of 92% and 67%. Reaction yields for diverse reaction conditions were predicted with a mean absolute error margin of 4–5%. The regioselectivity of the major products was accurately captured for up to 90% of the cases studied. Applied to 23 diverse commercial drug molecules, the platform successfully identified numerous opportunities for structural diversification. Six of the borylation opportunities identified by machine learning were validated via scale-up reactions and characterized. The incorporation of steric information via 3D molecular graphs led to improved neural network performance for all investigated tasks, ranging from small enhancements of reaction yield prediction (MAE, 4.23% vs. 4.41%) and binary reaction outcomes (accuracy, 81% vs. 76%) to substantial improvements of regioselectivity predictions (F-score, 60% vs. 39%). FAIR (findability, accessibility, interoperability, and reusability) documentation of reaction data and a newly introduced comprehensive reaction data format proved to be key enablers for the seamless integration of deep learning and HTE for LSF.
Vascular inflammation on a chip: A scalable platform for trans-endothelial electrical resistance and immune cell migration
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Open to view video.  |   Closed captions available The vasculature system plays a critical role in the body inflammation processes. Vascular inflammatory mechanisms are characterized by disruption of blood vessel wall permeability together with increased immune cell recruitment and migration. There is a critical need to develop models that fully recapitulate changes in vascular barrier permeability in response to inflammatory conditions. To this extent, we demonstrate a platform for inducing inflammatory reaction in HUVEC based microfluidic barrier models combined with continuous Trans Epithelial Electrical Measurements and coculture with Human peripheral Blood mononuclear cells. Over 250 tubules where exposed to Tumor necrosis factor alpha (TNFα) and interferon gamma (INF-γ) or human peripheral blood mononuclear cells. We found that the endothelial barrier changes differently depending on the inflammatory cytokine or immune cells added leading to changes in ICAM expression and endothelial morphology. We propose our platform as an essential tool for modeling endothelial inflammation in combination with immune cell interaction that can be used to screen for different targets and drugs to treat chronic vascular inflammation.
Automation of Complex Organoid Culture and Assay Workflows
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Open to view video.  |   Closed captions available "Tissue organoids, and other 3D biological models, are advancing biomedical research, including drug and target discovery, by capturing more of the relevant tissue biology. Additionally, patient-derived organoids (PDOs), such as from tumors, are being used as predictive models of patient responses to drugs and therapies. To enable and facilitate the use of these complex 3D tissue models, we leveraged the state-of-the-art, flexible automation BioAssembly™ Platform that is comprised of 5 modules: 1) the BioAssemblyBot® (BAB) 6-axis robotic system, 2) BioStorageBot™ incubator, 3) an intuitive BioApps™ workflow control software, 4) integrated confocal imaging scanners, and 5) advanced image and data analytics tools, to implement an automated workflow for culture and assaying of organoids. In this application, we demonstrate an automated workflow for culturing and assaying HCT116 cell-derived spheroids or patient-derived colorectal cancer organoids (CRC-PDOs) in domes of Matrigel® within standard 96 well plates. Using the Platform, we generated uniform, 5 μl matrix domes of HCT116-derived spheroids in half the time it took a human to perform the same task. Automated daily media exchanges were performed, followed by automated imaging of organoids using the Molecular Devices ImageXpress® confocal imaging system. Organoid plates were 1) transferred from the incubator to the media exchange station for feeding, 2) transferred from the station to the imager, 3) imaged, and 4) transferred back to the incubator. Acquired images were subsequently analyzed for comparison between manual and BAB-assisted seeding of the organoids. Compared to the manual approach, the automated platform gave less variation in organoid number and shape. We further extended our application by exposing assay-ready CRC-PDOs (manufactured and supplied by Cellesce Ltd) with serial dilutions of several anti-cancer compounds that include trametinib. Organoid phenotypic responses were then captured using a similar workflow described earlier, with an additional amendment that includes a nuclei stain. Additionally, organoid cultures were assayed with Cell Titer-Glo® for cell viability. Acquired images were then segmented and analyzed with IN Carta to extract multiparametric measurements about organoid size, number, and other cellular features. This data set was subsequently mined, normalized, and analyzed by StratoMineR™, a cloud-based data analytics solution provided by Core Life Analytics. Collectively, the results generated from the automated assay were consistent with the expected effects of these drugs on CRC-PDOs. In ready coordination with other instruments and analyses, the flexible BioAssembly™ Platform can automatically build and deploy organoids derived from a wide range of cell types using standardized or customized differentiation and assay protocols.  This Platform is amenable to microplates as well as specialized, microfluidic device-based microphysiological systems (in progress). Using a defined and robust workflow from automatic seeding to data analytics allows for reproducibility and quick acquisition of actionable knowledge for quality control and feedback.
A microwell platform to standardize human rectal organoid cultures for high-content imaging and phenotypic analyses
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Open to view video.  |   Closed captions available "In recent years, organoids have emerged as a game-changer for disease modelling and drug screening. These organoids are three-dimensional, miniaturized, and simplified versions of an organ that mimic some of the key features of the native tissue in vitro. Traditional organoid culture methods consist of embedding these structures in solidified extracellular matrix (ECM) thus introducing an intrinsic lack of reproducibility and creating highly heterogeneous organoid populations. Moreover, organoids are randomly distributed within the ECM which complicates subsequent readouts and images analyses. To overcome these challenges, we used Gri3D®, a ready-to-use platform for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a dense microwell array patterned in a cell repellent hydrogel. The platform enables homogenous cell seeding, efficient cell aggregation and subsequent formation of a single organoid per microwell in suspension-like conditions. A uniquely designed pipetting port, adjacent to each well, allows safe media exchange for long-term cultures. The resulting organoids are positioned in predefined locations in the same focal plane, allowing simultaneous tracking at high resolution. Combined with the ImageXpress® Micro Confocal system, we follow the development and self-organization of healthy human rectal organoids over time with brightfield imaging. Using an AI-based approach, we efficiently detect each single organoid and characterize their size, diameter, as well as complex morphological features such as lumen. Finally, we investigate the concentration-dependent toxicity of a small panel of compounds on human rectal organoids using AI-based brightfield image analyses and fluorescence-based readouts. The combination of a high-density microcavity array culture approach and a high content imaging system together with artificial intelligence algorithms allows the assessment of phenotypic features at a single-organoid level in an automatable high-throughput fashion. The presented approach has high potential in solving key challenges related to disease modeling and compound assessment at larger scale using organoids."
Automated workflow for 3D cell model generation and immunofluorescence phenotypic profiling using Pu·MA System EC (Environmental Control)
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Open to view video.  |   Closed captions available Three-dimensional cell models have gained popularity, compared with traditional 2D models, because they better reproduce key aspects of human tissues and are amenable to a wide range of applications from basic research to pharmaceutical drug safety and efficacy testing. Immunofluorescence (IF) staining and high-content imaging of 3D cell models are important tools that allow evaluation of the expression and localization of specific proteins within cells, as well as the distribution and interaction of different cell types, in response to treatments. Image-based phenotypic profiling is a validated strategy by which data-rich biological images are analyzed for patterns, revealing disease-associated screenable phenotypes. This process helps to understand disease mechanisms and to assess novel therapies more effectively. However, the transition from 2D to 3D cell models has resulted in challenges related to sample handling and assay development and requires more sophisticated protocols and instrumentation. Here we present our novel automated workflow for phenotypic profiling of 3D models using microfluidic low attachment flowchips and the new Pu·MA system EC (Environmental Control). The Pu·MA System EC can precisely control temperature, carbon dioxide levels and relative humidity in the flowchip chamber. The system enables generation of 3D cell models combined with automated 3D cell-based assays. The Pu·MA System EC workflow consists of 1) 3D cell model formation from a cell suspension with automated media exchanges, 2) incubation with compounds, 3) sample fixation and automated washes at room temperature, and 4) automated IF staining at room temperature. The samples can then be imaged and analyzed on confocal microscopes or high-content imaging systems. We used this workflow to analyze the cell marker expressions for proliferation and epithelial-mesenchymal transition (EMT) phenotype in two triple-negative breast cancer models: MCF7 spheroids and patient-derived tumoroids from aggressive tumor explant primary cells, TU-BcX-4IC (4IC). 3D cell models were formed from 5000 cells per well over 2-3 days within the flowchip with high cell viability. Automated media exchanges were performed every 12 hours. Formed spheroids and tumoroids were fixed, washed, and stained for Ki67 (proliferation), pan-cytokeratin, E-cadherin (epithelial markers), N-cadherin, Vimentin (mesenchymal markers) and F-actin in the flowchip. Confocal images were acquired using CellVoyager CQ1 High-Content Analysis System. A 150-200 μm Z-stack of images with 5 μm Z-step was acquired in the flowchip. MCF7 spheroids showed strong signals for epithelial markers (E-Cadherin, cyto-keratins). In comparison, 4IC patient-derived tumoroids showed marked downregulation of epithelial markers but had strong Vimentin and N-cadherin expression. This suggests that these highly aggressive 4IC cells have acquired a mesenchymal phenotype. This completely automated Pu·MA System EC workflow for 3D cell model formation, assay and phenotypic profiling eliminates sample disturbance, manual handling errors and provides consistent reproducible high-quality data. This platform is a valuable tool in a wide range of research areas including disease modeling, drug discovery and personalized medicine.
An automated platform for engineering primary human T-cells with digital microfluidics
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Open to view video.  |   Closed captions available Commercially available electroporation (EP) devices suffer from low viability when working with fewer than 105 cells and often require 106 cells per reaction for success with sensitive cells lines. This high cell number requirement makes transfecting primary cells prohibitively expensive and limits the ability to work with rare patient derived cells. Additionally, the lower transfection efficiency for current EP platform also creates challenges in integrating current EP platforms into an automated gene editing workflow that would allow for high throughput testing of different conditions (e.g., testing different guides or donor templates). We have developed a new EP platform for efficient transfection of primary cells using digital microfluidics (DMF). DMF allows for precise control of low quantities of cells in microliter droplets and has recently emerged as a promising technology for automating genetic engineering workflows. To meet the demand for an automated EP system capable of working with small cell populations (i.e. < 105 cells), we have designed a novel electroporator that can be integrated into a two-plate DMF device allowing for automated, high viability transfection of mammalian cells requiring only ~104 cells per reaction. To enable efficient transfection, DMF actuation is used to merge three droplets into a sequential chain, the outer droplets are comprised of high conductivity media (e.g., DMEM) and are in contact with gold electrodes and an inner droplet that contains cells and biomolecules suspended in low conductivity media (e.g., EP Buffer). First, we show here results related to delivering a large, 2000kDa FITC-tagged dextran payload into immortalized mammalian cell lines such as HeLa, Hek293, and Jurkat with viability ratios (VR) >90% and transfection efficiencies (TE) of >90% and up to 99%. We further validated the system using a 5kb plasmid in the same 3 cell lines. Measured 48 hours post-electroporation, we were able to achieve a TE as high as 70% and VR of >90% for all 3 cell lines. For an application, we will show the ability to transfect primary human CD4+ T cells with high efficiency and excellent cell viability. In experiments delivering the 2000kDa dextran payload, 24-hours post transfection the primary cells had a VR of 92% and a TE of 71%. Next, we experimented delivering an eGFP plasmid into the primary T cells. GFP expression was measured 48 hours post transfection where the cells were found to have a TE of >30% and VR of 88%. The VR of transfected cells was monitored for the remainder of the week and found to be equal to that of non-electroporated cells by day 5 post electroporation. We additionally will show how we integrate our tri-droplet platform into an automated gene-editing workflow to engineer primary T-cell lines for use developing new cellular therapies.
RealBrain® 3D neuronal micro-tissues – a high throughput platform for drug discovery in Alzheimer’s disease and other neurodegenerative disorders
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Open to view video.  |   Closed captions available "Recent advances in 3D cell culture systems provide a more physiologically relevant alternative to current approaches for high throughput compound screening. RealBrain® 3D neuronal micro-tissues (Tessara Therapeutics) demonstrate several advantages over other 3D models - they are optically clear, reach maturity within three weeks and the human neuronal cells that are initially encapsulated in a synthetic biomaterial then replace this with a cell-secreted extracellular matrix during the maturation phase. Robotic manufacturing has also been optimized to ensure reproducible and scalable production of RealBrain® micro-tissues. Academic and industry collaborations demonstrate the utility of our drug screening platform for commonly used screening outputs, such as neurite outgrowth, and highlight the capacity to develop bespoke assays to investigate pathways involved in the pathogenesis of multiple neurodegenerative conditions. We engaged with Molecular Devices, who leveraged their ImageXpress® Micro confocal high content imaging system and MetaXpress® image acquisition and analysis software, to develop an algorithm to analyze the neurites, nodes and cell bodies present in the microtissues. By reconstructing samples taken at different z layers and wavelength channels we reconstructed a digital replica of the 3D brain model revealing, previously undetected, mechanistic insights for drug discovery. We have subsequently applied this approach to quantify the impact of known compounds on neurite outgrowth and connectivity in our platform. Then, we leveraged recent discoveries around the role of ferroptosis, a distinct form of iron-dependent programmed cell death that has been implicated as a novel mechanism of neurodegeneration in conditions such as Alzheimer’s and Parkinson’s diseases and brain injury, to demonstrate the physiological relevance of our platform. Currently, the main tools for ferroptosis drug discovery are tumor or immortalized cell lines, which fail to capture the complex micro-environment of human neuronal tissue, which is a major contributing factor to the high failure rate of drug discovery. In the first demonstration of its kind, we utilized our 3D RealBrain® microtissues to create a human neuronal model of ferroptosis using validated compounds for the induction of this pathway (erastin and RSL3) and its rescue (liproxstatin and ferrostatin). We plan to expand on this study and to combine it with our ADBrain® micro-tissues to screen putative anti-ferroptosis drugs. Multiple studies demonstrate that 3D RealBrain® micro-tissues are a breakthrough in organotypic neural cultures that will help drive innovation and knowledge translation. It will also significantly de-risk drug discovery pipelines by reducing cost and providing earlier insights into drug neurotoxicity and therapeutic efficacy. With current changes in the regulatory landscape, this work will also foster the adoption of non-animal-based screening approaches across the sector."
Liquid overlay technology and magnetized cells enable access and easier handling of cancer cell spheroids.
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Open to view video.  |   Closed captions available Drug screening is a laborious and costly process that still needs streamlining and improved predictiveness. Today, 3D cell culture can improve the overall screening workflow, but most models are still unsuitable for high-throughput screening. Several 3D cell culture techniques have been developed in the last decades to fulfil many unmet challenges. In the presented work, we showcase the integration of liquid overlay (Opti3D®, BIORCELL3D) and magnetic 3D cell cultures (M3D, Greiner Bio-One) to address many unmet needs in this field, including reproducibility and easier manipulation. In this context, we attempted to combine liquid overlay models with magnetization on breast cancer spheroids made with MDA-MB-231 cell line. For this, different magnetization options by adding Nanoshuttle-PL reagent at different steps of liquid overlay protocol were tested (1) at cell seeding step, (2) after compact spheroid obtention according to different non-matrix-spheroid developed protocols, or (3) at the same time as the addition of matrix. The addition of magnetic reagent as the same time as the matrix permits to have most promising results. Indeed, it permits to center spheroids in the well with the magnetic tool “96 spheroid drive” and to transfer them for one plate to another with “Solo or Multi MagPen” (100% and 25% of transfer success, respectively). Then, the impact of magnetization with or without transfer of these spheroids by size, morphology and viability analysis were evaluated. The results show 90 % of size similarity between magnetized and non-magnetized spheroids and 97% between transferred and non-transferred magnetized spheroids. The three conditions have the same viability profiles, suggesting the innocuity of magnetization and transfer. As a result, this combination can improve the handling of the spheroids meaningfully and could help conceive user-friendly 96-well plate kits with one unique and reproducible spheroid per well, particularly adapted for high-throughput drug screening.
Painting in 3D: High throughput phenotypic screening in printed 3D cell culture
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Open to view video.  |   Closed captions available Advanced three dimensional cell culture techniques have been adopted in many laboratories to better model in vivo tissue by recapitulating multi-cellular architecture and the presence of extracellular matrix features. We describe here a workflow for cell painting-based phenotypic screening in 3D cell cultures by using high throughput bioprinting with high content confocal imaging and machine learning. By combining the high throughput bioprinter RASTRUM with the Operetta CLS high-content analysis platform and customised machine learning algorithms, we demonstrate the utility of the protocol in 3D synthetic hydrogel cultures with brain cancer (U87MG) cells. To establish and validate the workflow, we treated the bioprinted 3D brain cancer cultures with either the histone deacetylase inhibitor panobinostat or the tubulin-targeting chemotherapy drug paclitaxel. Both drugs readily entered the encapsulated U87MG networks and markedly altered cell proliferation and morphology. Following staining with the PhenoVue cell painting dyes, three-channel 1 mm3 stacks (1.8 x 1.8 x 0.3 mm) were captured at 20x magnification, followed by post hoc feature extraction using the inbuilt Harmony software, and python-based analysis of the high dimensional data set. The dimensionality reduction algorithms reliably identified and separated each compound in a concentration-dependent manner from each other and vehicle controls. Through our validation experiment we demonstrate the full compatibility of the bioprinted 3D cell cultures with high content image-based in vitro assays. The efficiency of the workflow, minimal protocol modifications, and applicability of an established phenotypic screening process, demonstrates that advanced encapsulated 3D cell cultures can be used in 2D cell culture screening workflows, while providing a more holistic view on cell biology to increase the predictability to in vivo drug response.
AutoHCS: Automated AI-based scoring of dose-response high-content screens.
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Open to view video.  |   Closed captions available Modern drug development increasingly depends on high-content compound screens where automation is the key to rapid, impactful discoveries. AutoHCSTM is an AI-based system developed by ViQi Inc. that automatically detects and scores dose-dependent phenotypic responses to drugs in high-content screens. The only inputs to the analysis are images from any automated plate imager and a plate map specifying concentrations, replicates, and controls. Because the system does not depend on segmentation, it works non-parametrically with multichannel fluorescence, a combination of fluorescence and brightfield, or brightfield alone. With these inputs, AIs are trained by AutoHCS to score cellular responses to compound concentration within hours. For individual compounds, the system scores the cellular response to each concentration against each of the positive controls. It also scores compounds across concentrations independently of the controls, permitting the discovery of novel phenotypes. Finally, the report contains a series of dendrograms depicting phenotypic similarity of cellular responses to 1) each compound concentration compared with the set of positive and negative controls and 2) all compounds in the screen. AutoHCS entirely determines its training parameters using the experimental controls rather than user input, which eliminates subjective criteria selection that may bias phenotype scoring. This also makes it extremely user-friendly and flexible to researcher needs. It is cloud-based, meaning there is no software or specialized computing hardware to install locally. Accordingly, AutoHCS is scalable to millions of images of many varieties. With these features, AutoHCS harnesses the pattern recognition abilities of modern AIs to precisely score high-content screens in an entirely automated, objective manner.
Open Source High Content Screening Data Visualization, Validation, and Processing at Scale
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Open to view video.  |   Closed captions available Abstract: Open source software tools for image processing have taken off over the last decade. Additionally, modern machine learning and deep learning models to process biomedical image data have exploded in recent years. However, in the biomedical field much of the attention and tooling has been focused on whole slide pathology imaging, volumetric electron microscopy, or relatively low throughput 2D and 3D fluorescent/transmitted light microscopy. While many of the tools and techniques needed in these fields translate well to high content screening (HCS); HCS presents its own unique pipelines, tools, and challenges in visualization, metadata annotation, and processing at scale. Here we present several data visualization and analysis pipelines, constructed from open source tools, specifically designed for the challenges of high content screening. We show the outputs of these pipelines on a high content screen for infectivity of SARS-CoV-2 across 200+ plates, 75,000+ wells, 1.5 million images (5+ terabytes of data), and >500 million cells in an open-source interactive web application, HCS-Explorer. Challenges at this scale include speed, scalability, memory stability of tooling, utilization of advanced hardware accelerators, and tracking and formatting of appropriate metadata. Additionally, tailoring of visualization software is needed to handle tiled loading of image data and relevant metadata, segmentations/annotations, and chemical structures. We present solutions that have been utilized in on-premise HPC resources as well as in the cloud, using the same tooling, and show the abstraction of our tools for ingesting metadata and formatting it in such a way that it is performant and adheres to open microscopy standards. We also compare our results to those obtained by industry standard tools in terms of both speed/scalability and accuracy/robustness to highlight the utility of our solutions in a real world context. Each pipeline is available as a Common Workflow Language (CWL) workflow and can be found on the open repository site, and each tool (step of the workflow) can be found as an Interoperable Computational Tool (ICT) in Github and Dockerhub. Each tool can be utilized as a container, as a command line tool, in a Jupyter Notebook, or via GUI in the Polus-Web Image Processing Pipeline (Polus-WIPP) application.Using these processing pipelines and custom data visualization tools the HCS community is now able to more quickly, easily, and cheaply discover quantitative insights from their imaging data. Additionally, for the first time, open-source HCS specific applications, tooling, and pipelines for large data visualization and processing have been developed and tested at scale for use by the community.
Deep learning models capture multi-dimensional features for cell morphology analysis from brightfield images
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Open to view video.  |   Closed captions available Many methods for imaging and sorting tumor cells require biomarker labels that perturb cells and may create a selection bias. The Deepcell platform can characterize and sort cells using only brightfield images of unlabeled single cells, thereby enabling more comprehensive and unbiased assessment of cell morphology and heterogeneity. Cells are imaged with a high-speed camera while flowing through a microfluidic channel and captured brightfield images are analyzed in real-time by deep learning models to generate quantitative AI embeddings, which are reproducible and multi-dimensional descriptions of cell morphology. However, one of the key technical challenges in building this platform was the development of an AI model to extract features from cell images from diverse human cells without prior knowledge of specific cell types, cell preparation, or other application-specific knowledge for an exploratory approach. Therefore, we developed Deepcell’s ‘Human Foundation Model’ (HFM), a feature encoder that transforms cell images into 128 dimensional embedding vectors. The model backbone, responsible for extracting image features, is based on the ResNet18 convolutional deep neural network architecture. Training utilizes a multi-task semi-supervised training framework that combines the VicReg self-supervised learning model, which learns images features without labels, along with supervised auxiliary models using labeled data. These sub-models enable the backbone model to recognize specific cell attributes such as granulation, pigmentation, characteristics of malignancy, attributes related to cellular states like apoptosis and necrosis. We augment the deep learning embeddings with computer vision derived cellular features, such as area, perimeter, intensity, and texture features to improve model interpretability and accuracy. Here, we describe how the HFM self-supervised backbone model was trained, the discriminatory power added by the supervised tasks, and validation of the reproducibility and generalization capabilities of the resulting model. We also demonstrate how the resulting embeddings can be visualized using the Deepcell software and how clusters of cells in the embedding space can be related to cell images, interpretable morphological features, and actionable biological characteristics. Potential applications of the Deepcell platform are diverse and promising, such as heterogeneous sample evaluation, disease detection and enrichment, drug and CRISPR perturbation screening, cell state characterization, and multi-omic integration.
Advantages of Integrating Acoustic Tube Technology for Automating Sample Provisioning
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Open to view video.  |   Closed captions available For sample management operations, provisioning copies of samples for hit follow-up and hit-to-lead can be laborious and resource intensive. This workflow usually involves a two-step process requiring cherry-picking from long-term storage stocks and subsequently reformatting liquid samples to match the requirements of downstream processes, such as hit confirmation or IC50 determination. Historically, the production of assay-ready-plates (ARPs) utilizing a fully integrated acoustic plating system required picking the samples from a large quantity of 1536- and 384-well storage plates, requiring time consuming robotic plate movements and large quantities of plate storage positions. The repetitive sealing and unsealing of source plates to pick samples can significantly increase run times and lead to unnecessarily exposing samples for long durations. Within the Compound Management and Distribution (CMD) group at Pfizer, a next-generation sample provisioning system decouples the cherry-picking and reformatting processes by integrating next-generation products from multiple vendors including Azenta, HighRes Biosolutions, Beckman, and others. The new design leverages the upstream cherry-picking process made possible through the use of acoustic storage tubes, which allow the realization of numerous advantages over the legacy system, including increased throughput, true redundancy, and sample preservation.
Solution Spotlight
High throughput robotics, genomics and microbiology: Integrating laboratory automation into microbiology, genomics and drug discovery workflows for improving animal and human health
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Open to view video.  |   Closed captions available "Surveillance of antimicrobial resistance (AMR) is critical to reducing its wide-reaching impact. Its reliance on sample size invites solutions to longstanding constraints regarding scalability. Together with Tecan and Scirobotics, automated robotic systems and high throughput next generation sequencing platforms have recently been developed, making it feasible to develop cost-effective tools to monitor AMR on large numbers of representative samples obtained from livestock for testing and food safety applications. In addition, a drug discovery platform for infectious diseases (bacteria, fungi and viruses) was developed using integrated assays involving microbiology, mass spectrophotometry, real-time cytometry and high throughput drug discovery assays, allowing for widely interpretable data outputs and reporting. This presentation will focus on advancing AMR surveillance through robotic multiplatform integration and identifying a balanced role of phenotype and genotype from a One Health perspective."
ARRALYZE: Functional assays at the single cell level.
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Open to view video.  |   Closed captions available "ARRALYZE is a proprietary digital cell biology platform that uses deep glass nano-wells for screening of large cell populations at the single cell level. ARRALYZE can selectively introduce cells into the wells, and after culturing and screening, you can isolate individual cells alive for subsequent steps such as expansion, single-cell genomics, or the like. The extreme degree of miniaturization not only increases the chances of finding better cells, saving expensive reagents, and shortening your workflow, but also provides a high degree of certainty of monoclonality, giving you an edge over the competition. Applications where ARRALYZE can play to its strengths are cell therapy, synthetic biology, cell line development or monoclonal antibody development. "
A standardized, automated and rapid platform for biomarker discovery applying a plasma proteomic workflow
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Open to view video.  |   Closed captions available "Plasma is a rich resource for protein biomarkers providing minimal invasiveness for collection of clinical specimens. The high complexity of plasma and wide dynamic range of plasma proteins complicates its analysis; therefore, workflow standardization is key for large patient cohorts, and a scalable and rapid platform for plasma proteomics is required. Tecan presents an automated platform that includes automated sample preparation with Tecan’s Fluent 480 and Resolvex A200 followed by standardized data acquisition and processing. This platform brings simplicity to the challenging analysis of plasma for high-throughput sample preparation with short-gradient MS-based analysis that allows scaling for large cohorts. The manual and automation workflows show equal performance in terms of protein recovery, precursors/protein identification, quantification, reproducibility and digestion efficiency with minimal hands-on time and precise quantification empowering researchers to spend quality time on data integration."
Challenges in Precision Molding and Emerging Micro Advancements
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Open to view video.  |   Closed captions available Today, the need for micro molding capabilities used to manufacture thinner walled vessels, micron-sized microfluidic channels, and tighter tolerances all while overcoming scalability issues for high volume applications. With the miniaturization of medical devices and laboratory processes, the need for small and highly precise components and parts has continued to increase rapidly. This presentation will review these challenges and offer insight to the solutions for successful and repeatable outcomes. In addition, we will discuss emerging applications where these micro manufacturing advancements are allowing far greater functionality through molded-in functional surfaces.
An integrated live-cell imaging system for automated high-throughput analysis of 2D cell migration and chemotaxis
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Open to view video.  |   Closed captions available An integrated live-cell imaging system for automated high-throughput analysis of 2D cell migration and chemotaxis
Automata LINQ unlocked: Meet the first fully-automated lab bench
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Open to view video.  |   Closed captions available "At this year's SLAS, come see the world’s first fully-automated lab bench: The Automata LINQ. LINQ is a lab automation platform that enables Life Sciences labs to finally fully automate any workflow. Made up of an automated lab bench, which fits into the same footprint as a regular lab bench, and lab orchestration software, which enables true walkaway time, LINQ is set to revolutionize the way we think about lab automation today and in the future. Join Automata’s Director of Product Growth, Russ Green, and Michael Asham, Head of Applications Engineering, as they reveal LINQ for the first time ever. At this talk, you’ll learn: What the new era of open, integrated automation will look like A deep dive into the LINQ platform The features and benefits of LINQ Examples of LINQ in action in cell culture and genomics workflows Join us at the Spotlight Theatre, Monday, February 27, 2023, 4:30 PM – 4:50 PM"
High-throughput Trans Endothelial Electrical Resistance (TEER) Measurements on a Tubular Organoid-derived Gut-on-a-chip model suitable for drug development research
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Open to view video.  |   Closed captions available High-throughput Trans Endothelial Electrical Resistance (TEER) Measurements on a Tubular Organoid-derived Gut-on-a-chip model suitable for drug development research
Microscale TFF with µPULSE: A Novel Solution for Lab-Scale Concentration, Buffer Exchange, and Desalting.
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Open to view video.  |   Closed captions available Microscale TFF with µPULSE: A Novel Solution for Lab-Scale Concentration, Buffer Exchange, and Desalting.
Trust all your moves to accelerate your cell line selection with an integrated automated shaking solution
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Open to view video.  |   Closed captions available Trust all your moves to accelerate your cell line selection with an integrated automated shaking solution
High-throughput cell engineering in microfluidic picodroplets
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Open to view video.  |   Closed captions available High-throughput cell engineering in microfluidic picodroplets
The masterpiece for 3D cell culture scale up
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Open to view video.  |   Closed captions available The masterpiece for 3D cell culture scale up
Prep for the Future with Automated sample preparation solutions for DNA, RNA, proteins, and cells
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Open to view video.  |   Closed captions available Prep for the future with automated sample preparation solutions for DNA, RNA, proteins, and cells. Manual sample preparation is tedious and inefficient. Check out an automated sample purification system and optimized reagents that serve applications, such as FFPE and cell-free DNA (cfDNA) tissue and liquid biopsy, immunoprecipitation, peptide mapping, and cells and exosomes and more.
Development of an Automated Interface for LC Instruments
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Open to view video.  |   Closed captions available Development of an Automated Interface for LC Instruments
Rethinking Your Sample Prep Approach with Laminar Wash™
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Open to view video.  |   Closed captions available Rethinking Your Sample Prep Approach with Laminar Wash™
Streamlining Your Lab with a New Liquid Handling Management Software for Liquid Handling Devices and Operators
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Open to view video.  |   Closed captions available Streamlining Your Lab with a New Liquid Handling Management Software for Liquid Handling Devices and Operators
Development of a high-throughput image cytometric screening method as a research tool for immunophenotypic characterization of patient samples from clinical studies
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Open to view video.  |   Closed captions available Immunophenotyping has been the primary assay for characterization of immune cells from patients undergoing therapeutic treatments in clinical research, which is critical for understanding disease progression and treatment efficacy. Flow cytometry has been the major methodology for characterizing surface marker expression for immunological research. In general, flow cytometry requires highly trained users and can be time-consuming, thus necessitating the need for a higher throughput method for routine measurements. Recently, a novel image cytometry system (Cellaca™ PLX Image Cytometer, Nexcelom from PerkinElmer, Lawrence, MA) was developed as a complementary method to flow cytometry for performing high-throughput immunophenotyping. In this work, we demonstrate a high-throughput image cytometric screening method to characterize immune cell populations, streamlining the analysis of routine surface marker panels. We validated the proposed method by comparing the Cellaca™ PLX and the Aurora (Cytek®) cytometer, which showed comparable CD3, CD14, CD19, and CD56 cell populations from subjects enrolled in autoimmunity and oncology disease study cohorts.
Creating a digital lab for all - from digital twins to interactive SOPs
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Open to view video.  |   Closed captions available Creating a digital lab for all - from digital twins to interactive SOPs
A Phenopushing Platform Identifies Compounds that Accelerate Cellular Adaptation to Acute Hypoxia
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Open to view video.  |   Closed captions available A Phenopushing Platform Identifies Compounds that Accelerate Cellular Adaptation to Acute Hypoxia
3D Cell Culture Solutions to Maximize Biological Complexity and Throughput
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Open to view video.  |   Closed captions available 3D Cell Culture Solutions to Maximize Biological Complexity and Throughput
Automated biomolecular analysis with mass photometry
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Open to view video.  |   Closed captions available Automated biomolecular analysis with mass photometry
From Cutting Edge to Practical: The Power of Compounded Innovation
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Open to view video.  |   Closed captions available Cutting-edge technologies like AI and quantum computing have yet to demonstrate a clear return on investment and pass regulatory barriers. Instead, discrete innovations such as machine learning, voice recognition, and OCR can already be leveraged today, making significant impacts. By combining these technologies in creative ways, pharmaceutical organisations are able to gain in efficiency, reduce the risk of errors, improve user experience and better retain talent. In this talk, we’ll explore the power of discrete innovations and how they can transform businesses.
High-throughput SPR assay for FcγR binding to drug candidates on the new Carterra LSAXT
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Open to view video.  |   Closed captions available High-throughput SPR assay for FcγR binding to drug candidates on the new Carterra LSAXT
From purified targets to cells: Combining surface chemistry and MALDI mass spec to analyze biochemical reactions and binding interactions
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Open to view video.  |   Closed captions available From purified targets to cells: Combining surface chemistry and MALDI mass spec to analyze biochemical reactions and binding interactions
Bring your workflows to the cloud - a programmers digital toolbox
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Open to view video.  |   Closed captions available Bring your workflows to the cloud - a programmers digital toolbox
Making Liquid Handling and Lab Automation Accessible for All: The FLO i8, F.A.S.T., and ROVER
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Open to view video.  |   Closed captions available "At FORMULATRIX, every product we deliver to the laboratory automation space seeks to simplify the translation of a lab's workflow into a digital domain as well as bring the latest sensing technologies and algorithms to deliver unparalleled simplicity for the end-user. Both our FLO i8 and F.A.S.T. systems seek to eliminate the need to consider liquid classes for executing workflows on these systems. Both units have embedded cameras for tip detection, tip re-arrangement, and to protect themselves from crashes and downtime. The FLO i8 eliminates the need for specific labware programming with our transparent conductive tips and touch probes design into each pipetting channel. Our thesis is to create breakthrough hardware complete with all sensors necessary to address the needs of lab automation of both today and the future through simple software updates. Our ROVER system seeks to automate labs that are already ""automated."" The ROVER can connect different automated cells and even different labs together, enabling new ways of thinking about scientific workflows. This can allow for 24/7 science to occur, with a push towards more continuous flow research rather than large batch-sized experimentation. This is both more efficient for labs and enables scientific insights to occur more rapidly. Our guiding thesis is: Life science and pharmaceutical research should only be governed by the pace of scientific insights and learning, and not by the tools and automation needed to arrive at this knowledge. This thought process has guided the products FORMULATRIX offers and continues to shape our innovations to meet the needs of the labs of the future. "
Innovation in Lab Automation with Digital PCR
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Open to view video.  |   Closed captions available In this presentation, learn about the latest innovations to enable absolute molecular quantification. The automation compatible QuantStudioTM Absolute QTM Digital PCR system will be highlighted, showcasing high throughput consistent data without the need for standard curves.
Morpholomics enabled through high content morphology analysis with AI powered, label-free single cell imaging and capture
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Open to view video.  |   Closed captions available Deepcell is advancing researchers’ understanding of cell biology by blending AI powered technology, microfluidics, and high resolution optics to deliver novel insights distinctively through the lens of cell morphology. We are pushing the boundaries of cell science with a morpholomics platform that uses machine learning and computer vision to characterize cells based on detailed morphological features without labeling while maintaining cell viability for multi-well sorting and downstream analyses. Come hear about the latest developments on the Deepcell platform and learn what the morpholome can reveal!