SLAS2022 International Conference and Exhibition

The SLAS2022 course package contains 135 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
  • Omics
  • Precision Medicine and Diagnostics 
  • New Modalities
  • Ignite

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. 

Roman Simon

Research Scientist

Boehringer Ingelheim Pharma GmbH & Co. KG

Roman studied Pharmaceutical Sciences at the University of Freiburg, Germany, and graduated after a research stay at the University of East Anglia, UK, in 2015. During his doctoral studies in the group of Prof. Manfred Jung, University of Freiburg, Germany, he developed in vitro assay systems and chemical probes for the screening and characterization of novel small molecule inhibitors of epigenetic targets with special focus on lysine acetyltransferases. In 2019, he obtained his Ph.D. in Pharmaceutical and Medicinal Chemistry from the Albert-Ludwigs-University in Freiburg, Germany. Subsequently, he started his postdoctoral work in the High-Throughput Biology group at Boehringer Ingelheim Pharma GmbH & Co.KG in Biberach, Germany, where he was responsible for the establishment and technological advancement of MS-based technologies to enable label-free high-throughput screening and to provide insights into drug-protein interactions beyond the generic potency readout. Since November 2021, Roman continues his work with Boehringer Ingelheim as a Scientist within the department of Drug Discovery Sciences.

Jefferson Chin, B.Sc.

Senior Scientist


Jefferson Chin is a Senior Scientist in the Compound Management & Distribution at Pfizer located in Groton, Ct. Jeff has a bachelor’s degree in Chemistry from Carnegie Mellon University and an MBA from the University of New Haven.  Jeff has over 30 years of experience in analytical chemistry, organic synthesis and finally compound management. He uses his experience to be the “voice of reason” while interacting with the chemists or biologist and developing new analytical workflows to extend CMD’s capabilities.

Kevin Elias

Director, Gynecologic Oncology Laboratory,

Brigham and Women's Hospital

Dr. Elias is a board-certified gynecologic oncologist and the Director of the Gynecologic Oncology Laboratory at Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School. His lab focuses on early detection strategies for gynecologic cancers and novel therapeutic development using a combination of artificial intelligence and cancer nanotechnology applications.

Robert Plumb

Director Omics

Waters Corporation

Dr Robert Plumb is the Director of Omics and Small Molecule Pharma in the Waters Scientific Operations Division, based in Milford, Massachusetts. 

Dr Plumb has published over 100 papers on the subject of HPLC/MS and NMR for bioanalysis, metabolomics and metabolite identification.  He is a recognized expert in the use of liquid chromatography with mass spectrometry, capillary scale LC, purifications scale LC and metabonomics, giving many invited papers at international meetings around the world.

After obtaining an honors degree in Chemistry from the University of Hertfordshire in 1992, he started work in at Glaxo Research and Development Drug Metabolism Department. During his time at Glaxo and later GlaxoWellcome he continued his research in liquid chromatography combined with NMR and mass spectrometry for metabolite identification and bioanalysis obtaining his PhD in 1999.

John Janiszewski

Research Scientist


Jonathan Shrimp

Research Scientist


Jonathan Shrimp, PhD in chemistry from Cornell University, Research Scientist at the National Center for Advancing Translational Sciences/National Institutes of Health (NCATS/NIH). As a research scientist at NCATS, my research aligns with the vision of NCATS, which involves collaborations with disease-focused laboratories. Together, we perform small molecule screening projects for disease targets, which involves assay development, screening and validation to help characterize the underlying biology. Additionally, we pursue new technologies for target-based and phenotypic screening in additiona to downstream validation.

Bradford Casey

Senior Associate Director of Research Programs

The Michael J Fox Foundation

Bradford Casey, Ph.D. leads the Michael J. Fox Foundation’s Genomics, Computational Biology, and Data Science research portfolios, working with other Foundation scientists to develop the Foundation’s research strategy. He collaborates with researchers, clinical leaders, as well as industry partners to develop new resources, apply new technology, and ensure that MJFF research priorities reflect and best serve the ultimate needs of patients. Bradford completed his Ph.D. in Neuroscience at University of Texas Southwestern Medical Center, where he applied new approaches in next-generation sequencing to study the activity of DNA-binding transcription factors in gene expression networks. His postdoctoral research focused on the development and application of novel computational genomics strategies in neuroscience to apply “big data” approaches to biological data sets. Bradford also serves as a scientific liaison to the Accelerating Medicines Partnership (AMP-PD), a public-private consortium focused on leveraging strengths of federal, academic, and industry partners to develop shared research tools and resources for the community. In addition to academic research, Bradford has broad experience working with researchers, legislators, and government agencies on policy initiatives to advocate for patients and neuroscience research.

Don Nguyen

High Throughput MS Scientist


Don's graduate work, carried out at the University of California ,San Diego, combined microbial natural products chemistry with many facets of mass spectrometry.  He then took a postdoc at EMBL in Heidelberg, Germany focusing on combining optical microscopy with LC-MS and imaging MS in single cell and sub-cellular metabolomics.  After completing his postdoc, Don was not ready to leave Europe and joined the Bioassay Automation team in the department of Discovery Pharmacology at Merck Healthcare (Darmstadt, Germany).  Here he is working on developing and integrating new high throughput mass spectrometry technologies for screening approaches.

Matthias Trost

Professor of Proteomics

Newcastle University

Prof Matthias Trost is a Professor of Proteomics at Newcastle University, UK. He is a proteomics expert with over 20 years of experience in mass spectrometry. He studied chemistry in Freiburg, Germany, and Manchester, UK, completing his PhD in Cellular Microbiology and Proteomics at the Helmholtz-Centre for Infection Research in Braunschweig, Germany and his postdoctoral research at the Institute for Research in Immunology and Cancer in Montréal, Canada. In 2010, he became Group Leader and Head of Proteomics at the MRC Protein Phosphorylation and Ubiquitylation Unit (MRC PPU) at the University of Dundee. In 2016, he was appointed Professor of Proteomics at Newcastle University. Since 2019, he has been a Wellcome Trust Investigator. Matthias’ main biological interest is in phagosome and macrophage biology and particularly signalling events in innate immunity driven by phosphorylation and ubiquitylation. In recent years, his lab has additionally focused on clinical proteomics and using mass spectrometry for drug discovery. For this, the lab pioneered the usage of high-throughput MALDI TOF mass spectrometry for drug screening which has attracted significant industry interest. He was just awarded the Biochemical Society's Industry and Academic Collaboration Award. 

Josephine Bunch

Martin Giera, Ph.D.

Head of the Metabolomics Group at the Center for Proteomics and Metabolomics

Leiden University Medical Center

Martin studied pharmacy in Heidelberg and Munich. He is the head of the Metabolomics group at the Center for Proteomics and Metabolomics at the Leiden University Medical Center (LUMC). He holds a PhD in Pharmaceutical Chemistry obtained from the Ludwig-Maximilians-University in Munich (Germany) . With a postdoctoral fellowship (DAAD stipend), he joined the group of Prof. Hubertus Irth at the VU University Amsterdam. Following a research stay in the laboratory of Prof. Charles Serhan at Harvard Medical School, he moved to the LUMC where he today heads the Metabolomics group. He is editor of the book “Clinical Metabolomics”. Martin is a permanent committee member of the inter-disciplinary panel of the FWO and served in several EU committees. His main interests lie in clinical and fundamental disease-related research, using metabolomics-based approaches and notably lipidomics.

Associate Principal Scientist

Senior Scientist


Aarti  was trained as an organic chemist, obtaining her M.S. from the UGA at Athens in 2005 with Prof. Geert-Jan Boons. She started her industrial career as a medicinal chemist at Vertex, and  she moved to AstraZeneca as a lead chemist in both oncology and the fragment based lead generation group contributing to the discovery of several clinical candidates. In 2013 she joined AstraZeneca’s newly created Chemical Biology group, focusing on small molecule target deconvolution and target engagement, supporting multiple drug discovery projects at different stages.    
In the chemical biology group, Aarti has championed the application of the CETSA and in-cell Chemoproteomics to measure cellular target engagement and target validation for multipass transmembrane protein receptors. Aarti’s efforts in studying difficult targets was recognized in 2017 with AstraZeneca’s Breakthrough Scientist of the Year award. Again in 2020, she was awarded for finding the target of a small molecule modulator of inflammation.

Maria Emilia Duenas

Marie Sklodowska-Curie Fellow

Newcastle University

Dr. Maria Emilia Dueñas, Marie Skłodowska-Curie Fellow, Newcastle University, Biosciences Institute

I completed my B.S. in Chemistry at the Universidad San Francisco de Quito (Ecuador) in 2013. In 2018, I obtained my Ph.D. degree in Analytical Chemistry from Iowa State University (United States) after working in Dr. Young Jin Lee’s group. My research focused on advancing the field of metabolomics using high-spatial resolution MALDI mass spectrometry imaging. I am currently a Marie Skłodowska-Curie postdoctoral fellow at Newcastle University (United Kingdom) in Dr. Matthias Trost’s Laboratory of Biomedical Mass Spectrometry. I am developing high-throughput MALDI-TOF mass spectrometry metabolite screening cellular assays for drug discovery in human disease. Moreover, I have expertise in quantitative proteomics investigating inflammatory disease, and implement thermal proteome profiling mass spectrometry techniques to identify protein targets and off-targets of drugs. 

Virneliz Fernandez-Vega

Scientific Associate

Scripps Research, Florida

Virneliz Fernández Vega is an Assay Development Scientific Associate in the Lead Identification/High Throughput Screening Division in the Department of Molecular Medicine at the Scripps Research in the Florida Campus since 2008. Her main focus involves the implementation and validation of physiological relevant 3D cell culture models of pancreas, brain and lung cancer for drug target screening using HTS automation. Also, she develops and implements biochemical and cell-based assays compatible for uHTS campaigns to screen large compound libraries for drug discovery of a multidisciplinary range of therapeutic areas including cancer, autoimmune diseases, neurological disorders and infectious diseases.

Before joining Scripps Florida, Mrs. Fernández Vega worked at the University of Miami studying the gene expression of transcription factors involved in breast cancer and tumor growth development. Prior to joining University of Miami in 2002, she worked in the Laboratory of Infectious Diseases in the Epidemiology Section at the National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Health in Bethesda, MD. Her primary focus was the characterization of the Norwalk virus N-terminal protein. Mrs. Fernández Vega graduated from the University of Puerto Rico with a major in Microbiology in 2001.

Tetsuhiro Harimoto

Graduate Student

Columbia University

Tetsuhiro Harimoto is a doctorate candidate in the Department of Biomedical Engineering at Columbia University. His current research in Dr. Tal Danino’s laboratory focuses on developing synthetic biology and bioengineering technologies to utilize bacteria for the detection and treatment of cancer. His recent works include developing multicellular platform for rapid characterization of tumor-targeting bacteria and constructing engineered biosensors for precision bacterial targeting in the body. Tetsuhiro received his BS in pharmacology and toxicology from the University of Toronto and earned his MS in biomedical engineering from Columbia University. Prior to graduate school, Tetsuhiro worked at Morgan Stanley as an equity research associate, analyzing the financial markets of pharmaceutical and medical device industries. Tetsuhiro joined the Danino lab in 2016 and is currently a NIH F99K00 Fellow.

Scott Fraser

Elizabeth Garrett Chair of Convergent Biosciences

University of Southern California

Professor Scott E. Fraser has a long-standing commitment to quantitative biology, applying the tools of chemistry, engineering, and physics to problems in biology and medicine. His personal research centers on imaging and molecular analyses of intact biological systems, with an emphasis on early development, organogenesis, and medical diagnostics.  His innovations have spawned start-up companies, and have been integrated into instruments and FDA approved diagnostics. After training in physics (B.S., Harvey Mudd College, 1976) and biophysics (Ph.D., Johns Hopkins University, 1979), Fraser served on the faculty at UCIrvine.  In 1990 he moved to Caltech to serve as the Anna Rosen Professor of Biology, and founded several multidisciplinary centers.  In 2012, he moved to USC to take a Provost Professorship.  He remains active in interdisciplinary research and serves as the Director of Science Initiatives for the USC campuses as well as co-directing USC’s Bridge Institute.

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.

Christina Woo

Associate Professor

Harvard University

Christina M. Woo is an Associate Professor in the Department of Chemistry and Chemical Biology at Harvard University, and an affiliate member of the Broad Institute. Christina’s research focuses on the design of chemical approaches to alter post-translational modifications and the signaling outcomes they produce in cells. She obtained a BA in Chemistry from Wellesley College (2008). She obtained her PhD in 2013 from Yale University under the guidance of Professor Seth Herzon as an NSF predoctoral fellow in the synthetic and chemical biology studies of diazofluorene antitumor antibiotics. In 2013, Christina joined the laboratory of Professor Carolyn Bertozzi at the University of California Berkeley as a Jane Coffins Child postdoctoral fellow and continued at Stanford University (2015) as a Burroughs Wellcome Fund postdoctoral fellow, where she developed a mass-independent chemical glycoproteomics platform for the identification of non-templated post-translational modifications. Christina joined the faculty at Harvard University in 2016. Her research has been recognized by the David Gin Young Investigator Award, Camille-Dreyfus Teacher-Scholar Award, Sloan Research Foundation, NSF CAREER, Bayer Early Excellence in Science Award, the NIH DP1 Avenir Award, and the Ono Pharma Foundation Breakthrough Science Award. 

Betty Chan

Director, Biochemistry and Biophysics

Auron Therapeutics

Betty joined Auron Therapeutics in January 2021. She is a data-driven and motivated scientific investigator with 15 years of experience building and leading biochemistry and lead discovery capabilities. Betty’s interest and expertise include advancing small molecules from various hit finding approaches (including DNA-encoded library screening) to IND filing, developing innovative assays to interrogate new modalities and their biochemical mechanisms of action, and working collaboratively to build infrastructure for supporting new R&D programs. Prior to joining Auron, she worked at Civetta Therapeutics, Kymera Therapeutics, X-Chem Pharmaceuticals, H3 Biomedicine, and Galenea Corporation. Betty has a Ph.D. in Biological Chemistry and Molecular Pharmacology from Harvard University, a M.S. in Molecular and Cell Biology from Brandeis University, where she also received bachelor’s degrees in Biochemistry, Biology, and French Language and Literature.

Shan Yu

Senior Scientist


Shan Yu works as a Senior Scientist in the Early Target Discovery group at Takeda Development Center Americas. She received her PhD in physiology from the Pennsylvania State University. She started her drug discovery career as a postdoc fellow at Calibr/Scripps Research, where she led and participated in a wide-range of drug discovery programs covering inflammatory and metabolic diseases. Since joining Takeda, she led a team to develop automation platform and incorporate machine learning and AI approaches into high throughput screens.

Markus Schirle, Ph.D.

Chemical Biology and Therapeutics,

Novartis Institutes for Biomedical Research

Markus Schirle received his master’s degree in biochemistry at University of Tuebingen, Germany and received his Ph.D. there in 2001 for his work with H.G. Rammensee on the identification of disease-associated MHC peptide by mass spectrometry-based approaches. After postdoctoral studies in proteomics with Alfred Nordheim, he joined Cellzome (now GSK, Heidelberg, Germany) from 2001 - 2007, where his work focused on protein and small molecule affinity proteomics for target identification (ID) and mechanism of action (MoA) studies. Joining Novartis in 2007, he established an independent platform for chemical and affinity proteomics for target ID and MoA studies in what is now the Chemical Biology and Therapeutics department. He is currently leading a group that is dedicated to identification and characterization of compound-protein interactions using proteomics, chemical biology, in vitro biophysics and biochemistry as well as structural biology and co-leads the Novartis-Berkeley Center for Proteomics and Chemistry Technologies (NB-CPACT). With his team he is responsible for affinity-based approaches to target ID/MoA as well as applications of covalent chemoproteomics and complementary approaches to the identification of ligandable pockets and chemical starting points for Novartis projects globally as well as the exploration of new modalities. 

Patrick McDonough

Chief Research Officer

Vala Sciences, Inc

Patrick McDonough, Ph.D., Chief Research Officer at Vala Sciences Inc.,  is a Cell and Molecular Biologist with > 30 years experience in developing and performing cell based assays.  Specialities include cardiac myocytes, neurons, and CNS glial cells.  A particular interest is the differentiation of human induced pluripotent stem cells (hiPSCs) to excitable cell types (e.g., cardiac myocytes, neurons, and skeletal muscle) to enable research on diseases of the heart, brain, and skeletal muscle systems.

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.

Brendon Kapinos

Principal Scientist


Brendon Kapinos is a Principal Scientist in Hit Discovery and Optimization (HDO) at Pfizer in Groton, Connecticut and oversees the group’s high-throughput bioanalytical operations. He joined Pfizer in 2007 after obtaining a BS in Biotechnology from the Rochester Institute of Technology, and accepted a position in the department of Pharmacokinetics, Dynamics and Metabolism. He later joined HDO, developing high-throughput in vitro ADME screens, LC-MS/MS platforms and workflows while completing his MA in Biology from Brown University. Brendon is a member of the American Society for Mass Spectrometry and has presented on various high-throughput LC-MS/MS technologies and workflows.

Doreen Miao

Business Director

Ananda Devices

Divya Malik

Senior Scientist

Horizon Discovery Ltd (PerkinElmer)

Xiaoyu Li


The University of Hong Kong

Dr. Xiaoyu Li received his B.S. degree from Peking University in 1997 and Ph.D. degree in 2002 from the University of Chicago. After a postdoctoral training at Harvard University, he conducted research in several biotech firms. In 2009, he joined Peking University as Associate Professor and in 2015, Dr. Li joined The University of Hong Kong and currently is a Professor at Department of Chemistry. Dr. Li’s research focuses on DNA-encoded chemical library, protein labelling and profiling, and target identification.

Noel De Miranda

Associate Professor

Leiden University Medical Center

Noel de Miranda is a PI of the Cancer Immunogenomics group at the Leiden University Medical Center. His group combines the use of high-end genomic, transcriptomic, and proteomic technologies for the study of cancer genetics and immunology. The main aim of the group is to support the development of novel therapies to enrich the immunotherapy toolbox for the treatment of advanced cancers. The group’s activities are subdivided into two major pillars: 1) the discovery of immunotherapeutic targets in cancer patients that are not amenable to state-of-the-art immunotherapies and 2) the characterization of cancer microenvironments and of immune cell subsets with anti-cancer activity by applying high-dimensional technologies on cancer tissues.

Zoe Hughes-Thomas

Medicine Design Automation Team Lead


I completed my first degree in Chemistry at Oxford University followed by a Ph.D. in Biochemistry from the University of Cambridge.  During my early career I held a number of molecular biology and protein biochemistry roles. I have worked within the Biopharm Discovery Departments within GSK for the past 15 years.  I have held roles of increasing responsibility leading both functional lines and matrix discovery project teams including Team Leader of the High Throughput Expression group, accountable for delivering all IgG material for hit screening supporting campaigns.  In 2019, I moved in to my current role where I am accountable for delivering the automation strategy and deploying, maintaining & maximising value of all automation across GSK’s small and large molecule Medicine Design organisation. In particular, the delivery of a key enabling project within our strategic Biopharm modernisation project.  Most recently, working in partnership with external collaborators to deliver fully automated DNA generation and protein expression & purification platforms to support all antibody material generation across the discovery process.

Daniel Sipes

SVP Operations and Strategy


Daniel joined Strateos in March 2019.  Prior to Strateos he was the Director of Advanced Automation Technologies at the Genomics Institute of the Novartis Research Foundation (GNF).  In this role Daniel ran an innovative technology development group at the intersection of science and engineering.  Responsibilities included development, implementation and operation, as well as commercialization, of new technologies.  His most recent work focused on automation to support more complex readouts such as single-cell gene expression and droplet microfluidics.  Prior to working at GNF Daniel held various positions at Kalypsys, Inc, Ligand Pharmaceuticals and Genentech, Inc.  Daniel graduated with a BS in Molecular Biology from California State University, Sacramento and an MS in Immunology from University of California, Davis.  Daniel has served many volunteer positions within the Society for Laboratory Automation and Screening including a term on the Board of Directors from 2013-2015 and as President in 2014-15.

Guy Oshiro

Senior Product Manager

Dassault Systemes

Guy Oshiro, Ph.D., is a Senior Product Manager at Dassault Systemes BIOVIA in San Diego, California. Guy is driving the efforts at BIOVIA to develop solutions that support and accelerate drug discovery research efforts. Guy is a multi-disciplinary scientist with broad experience in drug discovery and a strong background in research informatics. He has over 20 years of industry experience generating, analyzing and managing scientific data. As a bench scientist, he led multiple drug discovery projects from concept into clinical studies. As a informatics consultant, Guy developed custom solutions to address small molecule and biologics drug discovery needs. At Pfizer, he supported translational research projects that depended on large 'omics data sets. He obtained his Ph.D. in Molecular Biology from the University of Colorado Health Sciences Center in Denver, Colorado. He completed his postdoctoral training in functional genomics and high throughput automation at the Genomics Institute of the Novartis Research Foundation in San Diego, California.

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.

James Evans



Dario Caramelli

Research Fellow

University of Glasgow

Dario Caramelli is a Research Fellow in the Cronin group at the University of Glasgow, currently leading the cheminformatics section of the group. His research involves building and programming of autonomous robots for reaction discovery and reaction screening as well as the development of software for chemical space modelling, data processing and cheminformatics. He obtained a Master degree in Organic chemistry in Rome (2015) and a PhD in the Cronin group (2019).

Charles-Hugues Lardeau

Senior Scientist

Janssen R&D, Pharmaceutical Companies of Johnson & Johnson

Charles-Hugues Lardeau is a Senior Scientist in the High Dimensional & Computational Biology team at Janssen (Beerse, Belgium), having previously held roles at AstraZeneca (UK) and CeMM, the Research Center for Molecular Medicine (Vienna, Austria). He has an interest in high-throughput screening and high-content imaging assays. Charles-Hugues Lardeau holds a Ph.D. from the University of Leeds (UK).

Vishakha Goyal

Automation Engineer

NCATS, NIH/Axle Informatics

Vishakha Goyal is an Automation Engineer at NCATS, NIH. She has a Master of Engineering in robotics from University of Maryland, College Park. She works on developing systems for automating chemistry processes using Internet of Things and Robotics. Her primary focus is on building software to integrate various laboratory devices with sensors and developing in-house automated benchtop devices for product purification and isolation by incorporating techniques like computer vision.

Judith Wardwell-Swanson

Sr. Scientist

InSphero AG

Judi Wardwell-Swanson is a Senior Scientist at InSphero and the 2021 president of the Society of Biomolecular Imaging and Informatics (SBI2). At InSphero her work is focused on the development of high content imaging and microphysiological system applications utilizing 3D human microtissue models. Judi also has accumulated more than 25 years of experience in the pharma industry and has a long-standing interest in the utilization of genomics and imaging technologies to help drive drug discovery. As Principal Investigator in the Applied Genomics Department at Bristol-Myers Squibb, her team conducted phenotypic screens in physiologically-relevant cell models with an emphasis on the identification and validation new drug targets. Judi is also the author of several journal articles and a book chapter on imaging-related topics such as HCS data management, analysis of multidimensional imaging data, and 3D imaging/analysis of heterocellular spheroids.

Mark Ding

Automation Chemist


Formerly, as a senior research chemist, I worked at a worldwide research reagent supplier Combi-blocks for 10 years. I have synthesized more than 1000 different kinds of compounds with different reaction types, such as Suzuki Coupling, Amide Coupling, Buchwald-Hartwig Amidation, Grignard Reaction, Sulfonylation., etc. I am proficient in new compound synthesis, analysis, and purification. 

As the high throughput automated chemistry will be the future. I joined ASPIRE team of NCATS/NIH as an automation chemist in 2019. I am dedicated to the development of both hardware and workflow for automated chemistry synthesis with different vendors and pharmaceutical companies. In the NCATS automated cloud lab collaboration with Eli Lilly and Strateos, I lead the hardware development, concurrent workflow development, chemistry vilidation of Indigo reactor in L2S2 since 2019 , and fully intergrating of Indigo with Chemspeed SWING XL in Eli Lilly L2S2 for automated production chemistry.

Janne Wiedmann

PhD Candidate

Karlsruhe Institute of Technology

Janne Wiedmann is a second year PhD candidate at Institute of Biological and Chemical Systems - Functional Material Systems at Karlsruhe Institute of Technology. She achieved her Bachelor's and Master's degree in Chemical Biology at Karlsruhe Institute of Technology and is now working in the group of Prof. Pavel Levkin in the field of miniaturized, high-throughput organic synthesis. The PhD projects include collaborations with Mannheim Center for Mass Spectrometry and Optical Spectroscopy and Sanofi-Aventis Germany GmbH.

Robyn Laskowski

Senior Research Associate

Corteva Agriscience

Robyn Laskowski, a Senior Research Associate at Corteva Agriscience, has been aiding in the success of farmers in one way or another her entire life. Born in Wisconsin, she was raised on and contributed to her family’s farm, which spurred her to explore a career in Agricultural Biotechnology. With a decade of experience evaluating, developing, and deploying new technologies, Robyn helped successfully implement multiple platforms advancing genotyping capabilities to support the production of the highest quality seed. In 2020 she used her experience to help establish Corteva’s COVID-19 diagnostic testing laboratory and the creation of an ultra-high throughput COVID-19 testing platform with newly engineered automation. 

Robyn has an undergraduate degree in Chemistry at the University of Wisconsin-Eau Claire and completed her master’s degree in Organic Chemistry at Iowa State University. She lives in Des Moines, Iowa with her partner. 

Sakshi Garg

Associate Director

Merck Healthcare KGaA

Sakshi Garg joined Merck Healthcare KGaA in 2016. She has expertise in image based readouts both in 2D and 3D cell culture, allowing her to lead several technology based collaborations in the field of advanced cellular assays. Most recently she has been actively involved in the JUMP Cell Painting consortium.

Roman Affentranger

Section Head Automation Technologies


Dr. Roman Affentranger obtained his Ph.D. in 2006 from the Institute of Biochemistry at ETH Zurich, Switzerland, then joined the Institute of Biotechnology and Biomedicine of the Autonomous University of Barcelona, Spain, as postdoctoral researcher. From 2010 to 2013 he engaged in software project management activities in the areas of predictive toxicology, drug discovery and formulation research. In 2013 he joined Roche Pharma Research and Early Development (pRED) as Head of Small Molecule Discovery Informatics. In 2019 he transitioned to the Roche pRED Lead Discovery department to lead the Automation Technologies section, which covers high-throughput screening, compound management, and automated cell culture and cell banking.

Katrina Wisdom



Dr. Katrina Wisdom is a Bioengineer, Bioscientist, and Investigator of Complex In Vitro Models at GlaxoSmithKline.  Prior to her postdoctoral fellowship at University of Pennsylvania in Bioengineering, she received her doctorate and master's degrees from Stanford University and her bachelor's degree from Duke University.    She was awarded the University of Pennsylvania Provost's Postdoctoral fellowship, a National Science Foundation Graduate Research Fellowship, and a Stanford Bio-X Interdisciplinary Biosciences Fellowship.  Her expertise includes mechanobiology, biomaterials, cell-matrix interactions, and 3D cell migration and vascularization in immuno-oncology and epithelial barrier models.

Sam Michael



I am an automation engineer interesting in the combination of science, engineering, and information technology.

Allysa Stern

Product Applications Scientist

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. 

Helen Plant

Associate Director HTS Automation Team

AstraZeneca Pharmaceuticals

Having obtained my BSc in Biochemistry at the University of Manchester UK,  I have worked in the pharmaceutical industry for 29 years. I am an experienced drug-discovery bioscientist, working in the fields of Biochemical & Cell Assay Development, High Throughput Screening and  Laboratory Automation. In 2009 I joined the AstraZeneca Global High Throughput Screening centre as a senior scientist, with a responsibility for delivering screening data to a global internal & external customer base. Over the years I have developed an interest and depth of experience in lab automation  and in 2020 I was promoted to Associate Director, leading an AZ automation team and matrix managing a multidisciplinary team of external automation engineers. The team ensures delivery of automated high throughput screens to AstraZeneca drug projects and academic collaborators, focusing on the architecture, design, and data management of robotics and high-throughput systems to drive efficiency, inform decisions and enable discovery.

Dennis Sheberla



Dr. Dennis Sheberla brings to his role of Kebotix’s chief technology officer (CTO) an impressive multi-disciplinary background and passion to not only automate and discover fast new materials, but to apply these uses of AI, machine learning and robotics for a better world. Prior to Kebotix, Dennis’ interdisciplinary expertise is in synthetic organic chemistry, device fabrication and characterization, in addition to computational chemistry, machine learning and computer science. Dennis was a postdoctoral associate in the Department of Chemistry at the Weizmann Institute of Science in Israel, as well as MIT and Harvard in Cambridge, Massachusetts. Dennis earned his Ph.D. in Physical Organic Chemistry from the Technion – Israel Institute of Technology. He also holds an associate electrical engineering degree and certificate in computer science.

Emma Chory

Post-doctoral Fellow

Massachusetts Institute of Technology

Emma Chory is a postdoctoral fellow in the Sculpting Evolution Group at MIT, advised by Kevin Esvelt and Jim Collins. Emma's research utilizes directed evolution, robotics, and chemical biology to evolve biosynthetic pathways for the synthesis of novel therapeutics. Emma obtained her PhD in Chemical Engineering in the laboratory of Gerald Crabtree at Stanford University where her work revealed the fundamental mechanisms governing chromatin regulation. She is the recipient of the NSF Graduate Research Fellowship and a pre- and postdoctoral NIH NRSA Fellowship.

Anna Popova

Project leader

Karlsruhe Institute of Technology

Dr. Anna Popova is a head of biological sub-group in the Multifunctional Materials Systems research laboratory at the Institute of Biological and Chemical Systems (IBCS-FMS) at Karlsruhe Institute of Technology (KIT), Germany led by Prof. Pavel Levkin. She graduated from the department of Cell Biology and Immunology of the Biological Faculty, Lomonosov Moscow State University in Russia and obtained her Ph.D. in Cell and Molecular Biology in at University of Heidelberg, Germany. Since January 2014 Dr. Popova started at KIT as a project leader and head of the biology sub-group. Dr. Popova is the co-founder of Aquarray GmbH.

Kyle Loh

Assistant Professor and DiGenova Endowed Faculty Scholar

Stanford University

Kyle Loh is an Assistant Professor and The DiGenova Endowed Faculty Scholar at Stanford University. His lab is interested in generating different types of human cells—ranging from bone to blood vessels to brain—in a Petri dish from embryonic stem cells. Recently, his lab has used these human cell-types to study deadly biosafety level 4 (BSL4) viruses, such as Ebola and Nipah viruses. Kyle has received the NIH Director's Early Independence Award and Forbes 30 Under 30, and has been named a Packard Fellow, Pew Scholar, Human Frontier Science Program Young Investigator, and Baxter Foundation Faculty Scholar.

Thomas Angelini

Associate Professor

University of Florida

Dr. Thomas E. Angelini is an associate professor in the department of Mechanical and Aerospace Engineering at the University of Florida.  His research background includes the study of protein, lipid, DNA and virus self-assembly; collective cell migration and force transmission in cell monolayers; bacterial biofilm growth and spreading associated with biosurfactants and extracellular polysaccharide. Currently, his work focuses on cell-assembly and collective motion in 2D and 3D cell populations, and 3D printing of soft and biological matter. Since 2017, Dr. Angelini has served as an Associate Editor for the journal Soft Matter, published by the Royal Society of Chemistry.

Woojung Shin

Postdoctoral Fellow

Wyss Institute At Harvard University

I am a biomedical engineer and scientist with expertise in developing microphysiological human organ-on-a-chip platforms. I received my BS and MS degrees in Chemical Engineering at Sungkyunkwan University in South Korea and PhD degree in Biomedical Engineering at The University of Texas at Austin. Now, as a postdoctoral fellow at the Wyss Institute at Harvard University, I am trying to answer pressing questions in biomedical research and clinical settings by taking the engineering principles.

Athanasia Apostolou

Research Scholar

Emulate Inc.

Athanasia (Nasia) Apostolou,Ph.D., former Research Scholar at Emulate, Inc., has led the effort for developing and implementing the biopsy derived Colon Intestine-Chip in studying mechanisms that drive leaky-gut syndrome in humans. Prior to joining Emulate, Athanasia studied the role of the adaptive response to stressors on maintaining intestinal homeostasis in animal models. 

Athanasia has received her Ph.D. in Experimental Physiology from the Medical School of the National and Kapodistrian University of Athens and has first or co-authored several research articles and patents.

Caroline Sartain

Sr. Scientist

Fulcrum Therapeutics

Caroline Sartain is a Senior Scientist in Fulcrum Therapeutics' Target Discovery group where she specializes in next-generation sequencing-based assays for drug discovery. Caroline holds a PhD in Genetics from Cornell University and completed her postdoctoral work at Washington State University. Caroline's academic work focused on genetic regulation of reproductive biology; in her industry work she pivoted toward NGS assay development. She has worked in Boston-area diagnostics and therapeutics companies since 2017, holding positions at Good Start Genetics and Torpedo Diagnostics before landing at Fulcrum Therapeutics, where she has led NGS lab efforts since 2019. Caroline was awarded Fulcrum Therapeutics' Innovation Award for her contributions toward the development of the FulcrumSeek™ screening platform.

Nicholas Geisse

Chief Science Officer

Curi Bio

Dr. Nicholas Geisse is the Chief Science Officer at Curi Bio, a leading developer of human stem cell-based platforms for drug discovery. Dr. Geisse graduated from Boston University in Biochemistry and Molecular Biology and completed his graduate studies (Ph.D.) in Pharmacology at Cambridge University in England under Dr. RM Henderson, followed by a postdoctoral fellowship in cardiac cell and tissue engineering at the Harvard University School of Engineering and Applied Sciences under Prof. Kevin Kit Parker. After his postdoc, he went into industry and worked for Asylum Research (a manufacturer of Atomic Force Microscopes) as a scientist and project manager. At Curi, Dr. Geisse is part of the executive management team and is responsible for guiding the overall scientific strategy of the company in addition to developing and bringing to market Curi’s next-generation of innovative products aimed at increasing the predictive power of in vitro cell based assays.

Shuibing Chen

Associate Professor

Weill Cornell Medical College

Dr. Shuibing Chen is the Kilts Family Associate Professor and the Director of Diabetes Program in the Department of Surgery at Weill Cornell Medicine, New York. The major research interest in the Chen Laboratory at Weill Cornell Medicine focuses on studying the role of genetic factors and environmental factors on pancreatic beta cell in type 1 and 2 diabetes. In response to the COVID-19 pandemic, Dr. Chen created a panel of hPSC-derived cells/organoids to study SARS-CoV-2 infection. Dr, Chen has published more than 40 papers on peer-reviewed high impact journals, such as Nature, Nature Medicine, Cell Metabolism, Cell Stem Cell, Nature Chemical Biology, etc. She has received many awards including New York Stem Cell Foundation Robertson Investigator, ADA Junior Faculty Award, ADA Innovative Award, NIH Director’s New Innovator Award, American Association for Cancer Research Career Development Award, and ISSCR Dr. Susan Lim Award for Outstanding Young Investigator, etc.

Seungil Kim

Staff Scientist and Microscopy Team Manager

Lawrence J. Ellison Institute for Transformative Medicine

Seungil Kim, Ph.D., is a Staff Scientist and Microscopy Team Manager at the Lawrence J. Ellison Institute for Transformative Medicine. Dr. Kim completed his B.S. and M.S. degrees in South Korea. He then moved to WashU and received a doctoral degree in Developmental Biology. He carried out his postdoctoral research in the department of Cell and Tissue Biology at UCSF. Seungil has over 10 years of experience working with various in vitro/in vivo models and advanced cellular imaging techniques. His current research focus is to understand the contributions of the tumor microenvironment to drug response, using patient-derived 3D organoids as a model system. Moreover, he is developing high-throughput automated imaging methods to screen novel drug compounds in colorectal cancer.

Saiph Savage

Assistant Professor

Northeastern University

Dr. Saiph Savage is an Assistant Professor at Northeastern University  in the Khoury College of Computer Sciences where she directs the Civic A.I. lab. She is one of the 35 Innovators under 35 by the MIT Technology Review, a Google Anita Borg Scholarship recipient, and a fellow at the Center for Democracy & Technology. Her work has been covered in the BBC, Deutsche Welle, the Economist, and the New York Times, as well as published in top venues such as ACM CHI, CSCW, and the Web Conference, where she has also won honorable mention awards.  Dr. Savage currently also collaborates with the Civic Innovation lab of the National Autonomous University of Mexico (UNAM), has been awarded grants from the National Science Foundation, the United Nations, industry, and has also formalized new collaborations with Federal and local Governments where she is driving them to adopt Human Centered Design and A.I. to deliver better experiences and government services to citizens. Dr. Savage students have obtained fellowships and internships in industry (Facebook Research, Twitch Research, Twitter, Snap, and Microsoft Research) as well as academia (Oxford Internet Institute).  Saiph holds a bachelor’s degree in Computer Engineering from the National Autonomous University of Mexico (UNAM), and a master's and Ph.D. in Computer Science from the University of California, Santa Barbara (UCSB). Dr. Savage has also worked at the University of Washington,  and Carnegie Mellon University (CMU). Additionally, Dr. Savage  has been a tech worker at Microsoft Bing, Intel Labs, and a crowd research worker at Stanford.

Rohit Arora

Application Scientist

Iktos Inc

Rohit Arora is an Application Scientist at Iktos where he works on collaborations with, and deployment of Iktos software to, pharmaceutical and biotech clients. Prior to Iktos, he was a Postdoctoral Research Scientist at Harvard Medical School where he developed and applied Machine Learning methods to develop diagnostic biomarkers. Rohit has a PhD in structural bioinformatics from École Normale Supérieure Paris-Saclay where he applied in-silico methods to understand inhibition mechanism of therapeutically relevant proteins. He has also conducted related research at Université d'Orléans, in collaboration with Janssen Pharmaceutica.

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."

Jeroen Overman

Senior Scientist Mechanistic Biology & Profiling


Jeroen Overman received his PhD from the University of Queensland, Australia, where he investigated the role of transcription factors in aberrant cardiovascular growth and developed drug discovery projects against novel targets. He then joined Charles River Laboratories to drive mechanistic pharmacology and in vitro safety screening with a strong focus on high content imaging strategies. In 2020, he joined the department of Mechanistic Biology and Profiling at AstraZeneca, where he delivers profiling data with a deep mechanistic understanding for a wide range of early drug discovery projects across TAs.

Neil Benn

Managing Director

Ziath Ltd

Neil is co-founder and Managing Director of Ziath.  Since 1994, Neil has experience with a range of companies; GlaxoSmithKline; Cambridge Antibody Technology, Cenix Bioscience GmbH and the Max Planck Institute of Cell Biology and Genomics. Within these companies Neil has been responsible for the development, maintenance and implementation of laboratory automation and associated software with a focus on process control and information management.

Neil has served on the board of the European Laboratory Robotics Interest Group (ELRIG) in both Germany and the UK. He was the informatics chair for Lab Automation 2009, has edited for the Journal for the Association for Laboratory Automation and also served on the board of The Journal for Laboratory Automation. Neil has a Bachelor’s degree in Biotechnology and a Master’s degree in Computer Science.

Katelyn Hardy

Director, Informatics and Technology

MOMA Therapeutics

Having spent seven years in life science software services and then biotechnology leadership roles, Kate understands the varied needs of biotech companies and has learned a thing or two about how high quality data and user-friendly technology enable research discoveries and business intelligence. User success has always been central to her methodology and she is passionate about driving engagement across all levels of an organization, from bench researchers to business leadership.

After consulting with Third Rock Ventures portfolio companies for a year and helping launch companies with integrated and highly adoptable informatics platforms, Kate accepted a full time role at the Boston-based biotech startup MOMA Therapeutics as their head of informatics and technology. Her goal is to be a trusted advisor to both the business and the research sides of the company while deploying and supporting innovative technology solutions that are just as cutting-edge as MOMA’s ambitious research goals. Kate holds a BS in chemistry from Northeastern University and has completed multiple graduate level courses in topics spanning organic and bioanalytical chemistry to executive leadership and management.

Amanda Paulson

Informatics Specialist

ATOM Consortium; Univ of California, San Francisco

Amanda Paulson, PhD is a Specialist in Informatics in the Arkin Lab at the University of California, San Francisco. She earned her PhD in Biomedical Sciences at UCSF modeling the population dynamics of heterogeneous tumor cells. She then worked as a data science fellow at Frederick National Labs for Cancer Research where she was affiliated with the ATOM Research Alliance. As a fellow she built machine learning QSAR models for drug-induced liver injury (DILI) using phenotypic data from high content imaging screens. Currently, Amanda is still affiliated with ATOM and continues her work on DILI. She also works closely with experimentalists in the Arkin lab to process, analyze and manage the data generated from high throughput screening at the Small Molecule Discovery Center at UCSF.

Garrett Peterson

Chief Strategy Officer

Yahara Software

Garrett Peterson is the Chief Strategy Officer for Yahara Software, and has a BA in Computer Science from Lakeland University and an MBA from the University of Wisconsin-Madison.  Mr. Peterson has more than 35 years of IT management experience focusing primarily on the verticals of laboratory operations and scientific instrument integration. During his career, he has worked for both private and public-sector organizations, including a stint as the CIO of the State Public Health Laboratory in Wisconsin, and has been directly involved with countless LIMS implementations and system integrations for a wide variety of laboratory operations. In his role at Yahara Software, Mr. Peterson leads teams that provide innovative software solutions to support life science clients including efforts such as implementing laboratory systems at the CDC and working with organizations worldwide to support and enhance laboratory automation initiatives.

When he is not spending time working on laboratory informatics, Garrett spends his free time operating pinball machines for various establishments in Madison and playing keyboards in a band.

Sridhar Iyengar, Ph.D.


Elemental Machines

Sridhar Iyengar, a serial entrepreneur, has revolutionized multiple industries. Sridhar’s first company, Agamatrix, developed the first medical device, the iBGStar (a glucometer), to connect to the iPhone, setting the stage for connected health. AgaMatrix established partnerships with Apple, Sanofi, Walgreens, Amazon, and Target. His second company, Misfit, maker of elegant wearable products, was sold to Fossil for $260M. Sridhar’s current company, Elemental Machines, leverages Industry 4.0 technologies such as AI, data science and IoT to accelerate scientific innovation. Sridhar holds over 50 patents and received his Ph.D. from Cambridge University as a Marshall Scholar. Beyond Elemental Machines, Sridhar has been known to run 13.1 miles on occasion and has been spotted on stage behind a wall of drums.

Omer Bayraktar

Group leader

Wellcome Sanger Institute

Dr Bayraktar is a neuroscientist interested in studying human brain development and disease. His technical interests are focused on high-throughput spatial genomics. Omer was a postdoctoral fellow in David Rowitch’s lab, where he developed new spatial genomic pipelines for mapping large tissues and discovered astroglial layers in the cerebral cortex. Omer started his research group in the Cellular Genetics Programme at the Wellcome Sanger Institute in 2018. His group has developed new computational tools to integrate single cell and spatial transcriptomics data for comprehensive mapping of cell types across complex tissues. Currently, Omer is leading the Sanger-EBI High-Throughput Spatial Genomics Team to develop experimental and computational platforms to map human tissue architecture at scale. 

Song Lin Chua

Assistant Professor

Hong Kong Polytechnic University

Dr. Song-Lin CHUA is an Assistant Professor in Microbiology from Hong Kong Polytechnic University and Associate Director of Shenzhen Key Laboratory of Food Biological Safety Control. He was awarded the Interstellar Initiative Early Career Investigator in 2021 and Lee Kong Chian Medicine Fellowship in Singapore in 2015. He had published in 30 publications and filed 3 US patents, with expertise in microbiology, diagnosis of infections, and antimicrobial discovery.

Wee-Joo Chng


National University of Singapore

Professor Wee Joo Chng is Director of the National University Cancer Institute, Singapore and Group Director of Research, at the National University Health System. He is the Provost’s Chair Professor and Vice-Dean of Research of the Yong Loo Lin School of Medicine, and Deputy Director and Senior Principal Investigator of the Cancer Science Institute of Singapore, at the National University of Singapore. 

He is a member of many international professional committees, such as the International Myeloma Working Group and the Asian Myeloma Network. He is also involved in a number of Grant Review Committees, Conference Organising Committee, Advisory Boards and Steering Committees of Global Clinical Trials. He has authored more than 300 publications in many reputed journals, and actively participates in clinical trials and has delivered talks in many national and international conferences. He has won multiple awards for his outstanding achievements in translational research both locally and internationally including the International Myeloma Foundation’s Brian GM Durie Outstanding Achievement Award, the National Medical Excellence Outstanding Clinician Scientist Award, the National Medical Research Council Senior Translational Research (STaR) Award, the National University of Singapore Young Researcher Award, and the Celgene Future Leaders in Haematology Award.

Liping Yu

VP Application

Applied Cells Inc.

Dr. Yu received her PhD in Physical Chemistry and Biophysics from Carnegie Mellon University. Right after that she started her career at BD Biosciences, a division of Becton Dickinson, located in San Jose, California. In her 12-years career at BD, Dr. Yu focused on innovation and technology development. She has been an active inventor herself with six issued patents and more than 10 pending. Dr. Yu joined Applied Cells in 2018 leading the activities in application development.

Funien Tsai


10x Genomics

Scientist in the Molecular Biology R&D team at 10x Genomics, who helps develop NGS technologies to enable high-throughput, low-throughput and multi-omic single-cell sequencing.

Rong Fan


Yale University

Dr. Rong Fan is Professor of Biomedical Engineering at Yale University. He received a Ph.D. in Chemistry from the University of California at Berkeley and conducted the postdoctoral research at California Institute of Technology prior to launching his own research laboratory at Yale University in 2010. His current interest is focused on developing microtechnologies for single-cell and spatial omics profiling to interrogate functional cellular heterogeneity and inter-cellular signaling network in human health and disease (e.g., cancer and autoimmunity). He co-founded IsoPlexis, Singleron Biotechnologies, and AtlasXomics. He is the recipient of a number of awards including the NCI Howard Temin Career Transition Award, the NSF CAREER Award, and the Packard Fellowship for Science and Engineering. He is a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), elected a senior member of the National Academy of Inventors (NAI), and elected to the Connecticut Academy of Science and Engineering (CASE).

Allen Wang

Associate Director

Center for Epigenomics, UC San Diego

Dr. Wang is currently the Associate Director of Research at the Center for Epigenomics at UC San Diego. Dr. Wang specializes in the application of epigenomic technology platforms and interpretation of large-scale datasets to investigate human development and disease. He was previously a JDRF postdoctoral fellow at UC San Diego where his research focused on understanding pancreatic beta-cell development and diabetes by combining human genetics, stem cell differentiation, and epigenomics in the laboratory of Dr. Maike Sander. At the Center for Epigenomics, he currently oversees – including experimental design and data interpretation - multiple collaborative projects with investigators both in and out of San Diego, including projects focused on understanding human brain function using functional organoids, the molecular basis of human diseases such as diabetes and macular degeneration, and investigating lung cell-type diversity in the context of pedatric diseases such as BPD as part of LungMAP.

Yuchen Fan

Senior Scientist

Genentech, Inc

Yuchen Fan, senior scientist, gRED, Genentech. My academic and industrial expertise is focusd on drug delivery, nanomedicine, immunoengineering, and high-throughput analytical techniques for pharmaceutical and biotech applications. Currently I lead the high-throughput screening (HTS) and lab automation efforts to support the development of emerging drug delivery platforms and pharmaceutical formulations.

Antonin Tutter

Principal Scientist II

Novartis Institute for Biomedical Research

I received my PhD from UCSD in the lab of Katherine Jones (Salk), working on identifying factors required to initiate transcription on reconstituted chromatin. For my postdoc in the lab of Johannes Walter at HMS, I studied replication initiation in vitro using Xenopus egg extracts. Since then I've been at Novartis, where my recent work has been focused around targeted protein degradation / targeted protein stabilization.

Benedict Cross

Chief Technology Officer

PhoreMost Ltd

Ben is Chief Technology Officer (CTO) at PhoreMost, a target identification and drug discovery company based at the Babraham campus, Cambridge. He joined in 2019 to lead the evolution and development of the SITESEEKER® screening platform which uses PROTEINi® to discover new drugs to unprecedented targets. Prior to joining PhoreMost, Ben founded and led a CRISPR-based functional genomic screening department at Horizon Discovery, the leading UK gene editing biotech company based in Cambridge. As an academic, Ben’s training was in chemical genetics and mechanisms of proteostasis, working where Ben uncovered new modes of inhibition in the unfolded protein response.

Aram Chung, Ph.D.

Associate Professor / CEO

Korea University / MxT Biotech

Aram Chung is an associate professor in the School of Biomedical Engineering at Korea University. He received his undergraduate degree in mechanical engineering from Seoul National University, completed a Ph.D. in mechanical engineering from Cornell University, and carried out postdoctoral studies in bioengineering at UCLA. He then joined the Department of Mechanical Engineering at RPI as an assistant professor until he moved to Korea University. His lab investigates microscale flows to develop a new class of microfluidic systems for biomedicine. He is a founder/CEO of MxT Biotech, which is focused on developing transformative microfluidics-based cell therapies for cancer patients.

Tuyen Nguyen

Senior Scientist

Alnylam Pharmaceuticals

Tuyen Nguyen is a Senior Scientist at Alnylam Pharmaceuticals Inc., a biopharmaceutical company focused on the discovery, development, and commercialization of RNA interference (RNAi) therapeutics for genetically defined diseases.   She manages the target discovery and validation, and overseas the in vitro high throughput screening pipeline.   She also leads the CNS and Ocular assay development efforts in the development of human translational models using 2D/3D platforms.  In addition, she has extensive knowledge in building, optimizing, and validating high throughput in vitro screening automation system.  She received a B.S. in Biology from Emmanuel College and a master’s degree in Biotechnology from Harvard University.

Benedikt Von Der Heyde

Senior Scientist

Pelago Bioscience AB

Benedikt von der Heyde is a senior scientist at Pelago Bioscience. He is primarily developing high-throughput CETSA assays, as well as acting as a project accountable lead and performing internal R&D work. Before that, he absolved his PhD at Uppsala University (Sweden), investigating how findings from genome-wide association studies can be translated using a high-throughput imaging & CRISPR-Cas9 based approach in zebrafish.

Anastasia Velentza

Senior Director


Anastasia Velentza, Ph.D., Senior Director, Plexium Anastasia Velentza is the Head of Discovery Technology at Plexium, a TPD company. Anastasia has 23 years in Drug Discovery, with expertise in Screening and Discovery Biology across multiple therapeutic areas, modalities and targets. Before Plexium, she held positions of increasing responsibility at Novartis, Dart Neuroscience and Ferring Pharmaceuticals. Anastasia was NIH Research Award scholar in a drug discovery training program at Northwestern University in Chicago, IL. She earned her Bachelor of Science in Chemistry at the University of Patras in Greece, and a Ph.D. from the same institution in Bioorganic Chemistry, funded by a competitive scholarship and EU programs.

Jesse Chen


RA Capital Management

Jesse Chen, Ph.D is an Entrepreneur-in-Residence at RA Capital Management.  In this role he works closely with RA’s Venture Team to evaluate various drug discovery platforms and initiate novel therapeutics programs. Jesse has more than a decade of discovery research and management experience, from early discovery through preclinical development. Most recently, Jesse co-founded Avilar Therapeutics and led discovery research until its $60M seed financing. Prior to joining RA, Jesse was Senior Director of Discovery at Kymera Therapeutics. As the first and founding member of Kymera’s scientific team, Jesse was responsible for building the company’s industry-leading targeted protein degradation platform and pipeline, and he helped secure the company’s Series A and B financings as well as a partnership with Vertex. Jesse also held research leadership roles at Moderna Therapeutics and Millennium Pharmaceuticals, where he was responsible for developing novel platforms and leading discovery programs. Jesse earned his Ph.D. in Biological Chemistry from MIT and was a Harvard Origins Research Fellow.

Gary Kleiger

Associate Professor

University of Nevada, Las Vegas

Dr. Kleiger began his career as a structural biologist in the laboratory of Dr. David Eisenberg (UCLA). Dr. Kleiger then joined the laboratory of Dr. Ray Deshaies (formerly Caltech and now Vice President of global research, Amgen) focusing on the ubiquitin system and the application of biochemical and enzymological techniques to uncover enzyme mechanism. Dr. Kleiger is an expert in targeted protein degradation and a leader in the application of enzyme kinetics to the ubiquitylation reaction. Dr. Kleiger's research is at the nexus of understanding how ubiquitylating enzymes function at the molecular level and how to harness the power of these enzymes to treat various human diseases such as cancer. He is  involved in both academic and industry collaborations seeking insights into the targeted degradation of disease-causing proteins.

Kalli Catcott

Sr. Scientist

Mersana Therapeutics

Kalli is a Principal Scientist at Mersana Therapeutics working on bioconjugation and antibody drug conjugates. She received her bachelors from UC San Diego and has a PhD from Northeastern University. Kalli has spent the past 15 years making antibody conjugates of all kinds at companies such as ImmunoGen, Amgen, and Mersana. There is a very good chance that she arrived here on a bicycle.

Philip Mitchell

Science Director

Charles River

Science Director at Charles River Labs where I oversee small molecule Early Discovery drug discovery projects particularly in the area of Huntington's Disease.  Prior to joining CRL in 2016 I was a senior group leader at Takeda Cambridge with responsibility for assay development, in vitro pharmacology and hit ID activities.  I'm a biologist by training with degree in Biochemistry from the University of Liverpool and PhD in Molecular Biology from the Institute of Cancer Research (ICR) London. My career in drug discovery started in a Wellcome Foundation funded lab at the ICR cloning novel kinase as potential breast cancer targets.   Since then I've  gained  over 20 years drug discovery experience in  academia, biotech, pharma and CRO environments and been a member of project teams that have been fortunate enough to transition small molecules to pre-clinical & clinical development.

Greg Thurber

Associate Chair and Associate Professor of Chemical Engineering

University of Michigan

Greg M. Thurber is Associate Professor of Chemical Engineering and Biomedical Engineering at the University of Michigan and Associate Chair of Graduate Education in ChE. His work focuses on applying fundamental biotransport principles to design novel therapeutics and molecular imaging agents including antibody drug conjugates. Prof. Thurber received his training in protein therapeutics at MIT and in vivo molecular imaging at Mass General Hospital and Harvard Medical School. He has authored over 50 papers and delivered 60 invited talks at major pharmaceutical companies, national and international conferences, and university departmental seminars. He also has consulting/research contract affiliations with more than 15 different companies. Prof. Thurber’s work has been featured in popular news outlets including NPR’s “All Things Considered” and Smithsonian Magazine, and he has received several awards including an NIH K01 award, the National Science Foundation CAREER award, and the World ADC George R. Pettit Award for contributions to the field of antibody drug conjugates.

Arjun Raj


University of Pennsylvania

Arjun went to UC Berkeley, where he majored in math and physics, earned his PhD in math from the Courant Institute at NYU, and did his postdoctoral training at MIT before joining the faculty at Penn Bioengineering in 2010. He is currently a professor of Bioengineering.  His research focus is on the developed experimental techniques for making highly quantitative measurements in single cells and models for linking those measurements to cellular function.  His ultimate goal is to achieve a quantitative understanding of the molecular underpinnings of cellular behavior.

Will Greenleaf

Associate Professor

Stanford University

Nathan Price


Thorne HealthTech

Dr. Nathan Price is Chief Scientific Officer of Thorne HealthTech (NASDAQ: THRN). Previously he was CEO of Onegevity, an AI health intelligence company that merged with Thorne prior to the IPO in 2021. In 2019, he was named as one of the 10 Emerging Leaders in Health and Medicine by the National Academy of Medicine, and in 2021 he was appointed to the Board on Life Sciences of the National Academies of Sciences, Engineering, and Medicine. He spent much of his earlier career as Professor and Associate Director of the Institute for Systems Biology (now on leave), co-director with biotechnology pioneer Lee Hood of the Hood-Price Lab for Systems Biomedicine, and is Affiliate Faculty at the University of Washington in Bioengineering and Computer Science & Engineering. He is a Camille Dreyfus Teacher-Scholar, received the 2016 Grace A. Goldsmith award for his work pioneering ‘scientific wellness’, was a co-founder of Arivale, and received a Healthy Longevity Catalyst Award from the National Academy of Medicine in 2020. He has co-authored more than 180 peer-reviewed scientific publications and given over 200 talks and keynotes. He also served as Chair of the NIH Study Section on Modeling and Analysis of Biological Systems (MABS).  

Caroline Uhler

Associate Professor


Caroline Uhler is an associate professor in the Department of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society at MIT. In addition, she co-directs the newly-launched Eric and Wendy Schmidt Center at the Broad Institute. She holds an MSc in mathematics, a BSc in biology, and an MEd all from the University of Zurich. She obtained her PhD in statistics from UC Berkeley in 2011 and then spent three years as an assistant professor at IST Austria before joining MIT in 2015. She is a Simons Investigator, a Sloan Research Fellow and an elected member of the International Statistical Institute. In addition, she received an NSF Career Award, a Sofja Kovalevskaja Award, and a START Award from the Austrian Science Foundation. Her research lies at the intersection of machine learning, statistics, and genomics, with a particular focus on computational models of genome packing and regulation.

Jessilyn Dunn

Assistant Professor

Duke University

Dr. Jessilyn Dunn is an Assistant Professor of Biomedical Engineering and Biostatistics & Bioinformatics at Duke University. Her primary areas of research focus on biomedical data science and mobile health; her work includes wearable sensor, electronic health records, and multi-omics integration and digital biomarker discovery. Dr. Dunn is the Director of the BIG IDEAs Laboratory, whose goal is to detect, treat, and prevent chronic and acute diseases through digital health innovation. She is also currently PI of the CovIdentify study to detect and monitor COVID-19 using mobile health technologies. Dr. Dunn was a NIH Big Data to Knowledge (BD2K) Postdoctoral Fellow at Stanford and an NSF Graduate Research Fellow at Georgia Tech and Emory, as well as a visiting scholar at the US Centers for Disease Control and Prevention and the National Cardiovascular Research Institute in Madrid, Spain.

Derek Janssens

Postdoctoral Researcher

Fred Hutchinson Cancer Research Center

Dr. Derek Janssens PhD is a postdoctoral researcher in the lab of Dr. Steven Henikoff in the Basic Sciences Division of the Fred Hutchinson Cancer Research Center. After completing his graduate thesis at the University of Michigan, Derek joined the Henikoff lab in 2017 and has been developing novel chromatin profiling tools to understand the epigenetic heterogeneity of cancer. Both the automated CUT&RUN and CUT&Tag platforms Derek developed are currently available as core services through the Fred Hutchinson Cancer Institute. More recently, Derek has been optimizing CUT&Tag for single cell applications and is working to increase the number of single cells profiled in each experiment, while minimizing the cost.

Diana Azzam

Assistant Professor

Florida International University

Diana Azzam, PhD, is an Assistant Professor at Florida International University. She has a PhD in Biochemistry & Molecular Biology from the University of Miami, Florida. Her lab focuses on implementing functional precision medicine approaches in clinical trials to improve treatment outcomes of cancer patients. Her research also investigates cancer stem cells and their role in therapy resistance and metastasis.

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.

Thomas Conrads

Director of Women's Health Research

Inova Health System

Thomas P. Conrads, PhD is the Director of Women’s Health Research in the Inova Health System and the affiliated Women’s Health Integrated Research Center in Northern Virginia. He is also the Chief Scientific Officer of the Department of Defense Gynecologic Cancer Center of Excellence. His efforts are focused on developing and applying cutting-edge applications and workflows in proteomics for cohort-scale analysis of clinically derived specimens. The overarching goals of these efforts are toward identifying and validating protein biomarkers and surrogates for enhanced cancer patient management through improved early detection, patient stratification, and monitoring for therapeutic efficacy, outcome and recurrence.

Rene Overmeer

Head Assay Development and Automation

Hubrecht Organoid Technology (HUB)

René received his PhD in Biology from the Leiden University Medical Center on a molecular study of DNA damage repair. He subsequently moved to University Medical Center Utrecht to do his Post Doc studying Ras/Rap cancer signaling. During this period, he started working with adult stem cell derived Organoid Technology and developed the first drug screens together with the group of Hans Clevers. He continued this work in the newly formed ‘Hubrecht Organoid Technology’ (HUB) where he became responsible for development of new assays and high throughput screening.

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."

Heather Colvan, Ph.D.

Director of Operations


Heather Colvan is the cofounder and Director of Operations for Simplicis. Simplicis provides expert sample management solutions focused on data and hardware integration for automated pharmaceutical laboratories.

For the past 12 years Heather has been focused on delivering problem specific solutions to Simplicis's clients with a dedication to data management.  Prior to Simplicis Heather worked in healthcare revenue cycle management implementing and integrating claims inventory management solutions.

Heather is an advocate for women in computer science and gladly volunteers her time to facilitate a Girls Who Code club at her son's school.

Shawnnah Monterrey


BeanStock Ventures

Shawnnah Monterrey, MBA, CEO of BeanStock Ventures, is a domain expert with over 20 years of experience in the medical industry with specific emphasis on guiding innovative products to market.  Shawnnah has a passion for innovation in medical devices, life sciences and biotechnology. As the CEO, she continues to provide thought leadership in guiding the innovation of products and services that benefit the market and healthcare.

Maya Krolik


The Bishop's High School, La Jolla, California

Maya is a rising Junior with a never ceasing curiosity for the world around her. She was the team captain and programming lead on her FTC robotics team, and is currently their youth mentor. She also helped lead the team’s outreach efforts in hopes of inspiring the next generation of coders and engineers. Maya has experience with android app development, computer vision, and machine learning. As Maya graduates High School and goes to college, she is always exploring every possible opportunity to learn and grow as both an engineer and a person.

Debbie Bowers, M.BA., B.S.

Sr. VP, Commercial Development

BioDot, Inc.

Debbie Bowers, VP of Commercial Development and Board Member at BioSoft Integrators; WomXn of SLAS Co-Chair. 26 years supporting global Life Science customers through automation consultation, applications development and first in class customer care. An industrial engineer; an MBA with an emphasis in Global Marketing; and certification in Contract Law. Holistic diversity with all scientific application areas with knowledge of global best practices used in laboratories around the world. Joined BioDot in November 2020. From 2017 to 2020, as President and CCO, Debbie led the commercial strategy for BioSoft Integrators.  BioSoft offers Laboratory Information Management Systems (LIMS) to life science, clinical and manufacturing operation laboratories & is the preferred provider of High Performance Computing (HPC) solutions for PacBio customers.  Through Debbie's leadership from 2014 to 2017 as VP of Robotic Operations at Hamilton Robotics, her team of 250+ outperformed Industry Growth Targets YoY in selling automated liquid handling systems, while vaulting industry partnerships with the top 20 Life Science innovators, and launched 20+ new products to clinical and RUO customers. 2013/2014, Bowers was VP of Business Development at Invetech, a Danaher company, who specialized in product development for clinical diagnostics, life science and consumer product companies like Haemonetics, Coca Cola and Bio-Rad.  2000 thru 2012, Debbie acquired in-depth knowledge in all areas of liquid handling automation, detection, automated sample storage and retrieval systems and the consumables and modules required to automate complete workflows for life science applications in her many roles at Tecan US.  While at Tecan, she was responsible for sales, marketing, applications, custom solutions, product development and worked with every facet of customer type and scientific application. Early engineering, project management and technical sales roles provided Debbie with expertise in micro and macro filtration when working for Pall Gelman Sciences and Baker Hughes Process Equipment Company.

Samuel Oliveira

Postdoctoral Researcher

Boston University

Dr. Samuel Oliveira is a Post-doc at the CIDAR lab ( and the Research Lead of the DAMP Lab (, led by Prof. Doug Densmore at Boston University. Samuel has a background in Bioengineering, Microfluidics, Microscopy, and Lab Automation. At the CIDAR lab, his research is focused on automating the design and fabrication of micro-environments to study the dynamics of intercellular communication and multicellular circuits in synthetic bacterial communities. At the DAMP Lab, he is responsible for supervising novel hardware, software, and wetware projects and managing off-the-shelf services and customer projects involving the design and assembly of synthetic genetic constructs using automated platforms.

Deepak Balaji Govindaraj



Dr. Deepak Balaji Thimiri Govindaraj is a Centre Manager of CSIR Synthetic Biology and Precision Medicine Centre. Deepak Balaji is a chemical engineer by training and has worked on nanobiotechnology, industrial synthetic biology and drug screening for precision medicine. 

During his PhD in KU Leuven Belgium, Deepak worked on Nanobiotechnology methods for cell surface proteomics. The work resulted in a Patent and sold as a product in a spin-out company. Deepak then went to EMBL for a Marie Curie EIPOD Fellow where he designed synthetic baculovirus genome for recombinant protein expression. As a Senior Scientist at Oslo University hospital Norway,  Deepak established the drug sensitivity screening platform for blood cancer precision medicine.  Deepak has published 32 research papers, 3 granted patents, 25 conference proceedings and book chapters. Deepak has published in high impact journal such as Molecular Systems Biology, Blood, Nanoconvergence and Leukemia.

Neil Benn

Managing Director

Ziath Ltd

Neil is co-founder and Managing Director of Ziath.  Since 1994, Neil has experience with a range of companies; GlaxoSmithKline; Cambridge Antibody Technology, Cenix Bioscience GmbH and the Max Planck Institute of Cell Biology and Genomics. Within these companies Neil has been responsible for the development, maintenance and implementation of laboratory automation and associated software with a focus on process control and information management.

Neil has served on the board of the European Laboratory Robotics Interest Group (ELRIG) in both Germany and the UK. He was the informatics chair for Lab Automation 2009, has edited for the Journal for the Association for Laboratory Automation and also served on the board of The Journal for Laboratory Automation. Neil has a Bachelor’s degree in Biotechnology and a Master’s degree in Computer Science.

Maciej Grajewski


SG Papertronics B.V. and University of Groningen

Maciej Grajewski studied Biotechnology at Poznań University of Life Sciences. After graduation, he moved to Groningen for his PhD studies on microfluidic cell cultures and optical real-time cell monitoring. This work was performed with professor Verpoorte, in the Pharmaceutical Analysis group. It was also part of a larger EU collaborative network (LiPhos), which aimed to design, develop and test an optical tool for endothelial cell behaviour. Currently, Maciej’s interests revolve around real-time monitoring systems for diagnostic and environmental purposes.

Adam Stoten

SVP Academic Partnerships

Evotec (UK) Ltd

Dr Adam Stoten is SVP Academic Partnerships at Evotec SE, a global multi-modality drug discovery and development company, where he is responsible for creating new international BRIDGE partnerships to accelerate the translation of academic science into new therapeutics. Prior to Evotec, Dr Stoten was Chief Operating Officer and board director at Oxford University Innovation Ltd (OUI). While at OUI he was a member of the team that negotiated the Oxford COVID vaccine partnership with AstraZeneca, was a founding director of Vaccitech Ltd and EvOx Therapeutics Ltd and was a co-architect of Evotec's first BRIDGE; LAB282. Between 2010 and 2013 Dr Stoten worked as Deputy General Manager for a joint venture between the University of Oxford and Emergent BioSolutions Inc, developing a next generation TB vaccine. Prior to this Dr Stoten worked in healthcare consulting and then in increasingly senior commercialisation roles at Isis Innovation. Dr Stoten also serves as a board member of both PraxisAuril, the UK professional association for knowledge exchange practitioners, and of ATTP, the body that maintains internationally recognised standards for the knowledge and technology transfer profession.

Ytsen van der Meer

Investment Manager


Life Sciences investor from the Netherlands.

I work at a regional investment fund based out of the Netherlands that invests across several domains, amongst others life sciences & health, in the pre-seed and series A stages. My personal expertise lies within the early stage, life sciences and high- and deeptech domain. 

Corina Prent

Managing Director

RUG Ventures

Maurizio Aiello



Maurizo Aiello, CEO of React4life with international experience in company growth, execution, innovation. Specialties are: strategic vision and ability to create innovation, starting from basic and applied research and reaching the market. At present, he launched 3 startups born from basic research.

He holds a physics degree in nuclear physics in 1994. He has been Technologist at National Research Council of Italy since 2001 and Professor at the University of Genoa.
From 2014 to 2020 Aiello was Italian delegate for European Commission Horizon 2020 ""Secure Societies"" program; board member in different companies and institution, and scientific councils: among them former president of the SIIT Technology District, CEO of Cleis Security, board member at Italian Institute of Communications and others.
Author of more than 60 articles in international journals, international conferences, white papers; research activity in bioengineering, cybersecurity and infrastructure management. Hacker, with competences in development of cyberattacks and cyberweapons to IoT devices and networking infrastructure. Author of “slowdroid” denial of service attack.
Since 2017 Maurizio Aiello is founder and CEO of React4life s.r.l., an Italian biotech company that develops organ on chip technologies for accelerating the human disease understanding and novel personalized therapies development; React4life has won several international awards and projects, and recently the Innovation Radar award from European Commission as best Health technology 2021. 

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.

Amel Bendali

COO & Co-Founder


Amel Bendali, PhD, is the Chief Operating Officer and co-founder of Inorevia, a Paris-based startup providing new tools for life science research and diagnostics.

After graduating as an engineer in Physics and Biotechnologies, she joined the Vision Institute in Paris to participate in an ambitious research project to develop retinal prosthetic implantable devices, helping to restore functional vision to blind patients. Once graduated with a PhD in Neurosciences, she decided to move to microfluidics and microsystems, and joined Dr JL Viovy's lab at Curie Institute in Paris. After developing technologies based on microfluidics and magnetic particles, she co-founded Inorevia with Julien Autebert, CEO and CTO, and 3 researchers from CNRS who invented the technologies.
Since the creation of Inorevia in 2016, Amel has gained extensive experience in entrepreneurship, market approach for innovation, and taking patents and invention to meet market needs and solving actual users challenges.

Inorevia's vision is to unlock next-generation life science solutions, by combining highly efficient miniaturization and full automation to support reasearchers and clinicians dealing with complex workflows and challenging samples.

Mitchell Mutz, Ph.D.

Entrepreneur Partner

Vivo Capital

Mitchell Mutz, PhD, is an accomplished biotech serial entrepreneur, venture investor, and inventor.  He is currently an entrepreneur partner at Vivo Capital, a fund focused on investment opportunities in therapeutics, medical devices, and tools. Prior to joining Vivo, Mitchell was Senior Investment Director at the Roche Venture Fund, a $500M Swiss corporate venture fund which invests for financial return.  His portfolio included Enliven Therapeutics, Fabric Genomics, Good Therapeutics, Jasper Therapeutics (NASDAQ: JSPR), Kumquat Biosciences, lino Biotechnology, Pandion Therapeutics (acquired by Merck), Purigen Biosystems, and Stratos Genomics (acquired by Roche).   Previously, Mitchell was a co-founder, president, chief scientific officer, and board member of Amplyx Pharmaceuticals, Inc., a biotherapeutics company and Stanford University spinout. Mitchell led the company's R&D efforts, team building, as well as financing and in-licensing strategy and helped grow the company from early preclinical discovery to the clinical stage.  Amplyx has attracted over $140M in venture financing as well as over $11M in non-dilutive funding from the NIH.  Amplyx had a successful Phase 2 clinical trial readout in 2020 and was acquired by Pfizer in 2021.  Mitchell was also on the founding team and the Principal Scientist of Labcyte, a tools company that he helped grow from a garage-based start-up to profitability. Mitchell was responsible for discovering and and developing biotechnology applications for Labcyte's novel acoustic drop ejection technology.  Labcyte employs over 250 people worldwide, attracted over $80M in venture financing, and was acquired by Beckman Coulter Life Sciences in 2019.  Mitchell earned a Ph.D. in chemistry from the University of Rochester, a diploma in orchestral studies from the University of London, and a B.A. in chemistry with high honors from Oberlin College.  Mitchell is also an inventor on 37 issued patents.

Elizabeth Sharlow

Professor of Research

University of Virginia

Elizabeth Sharlow is a Professor of Research in the Department of Pharmacology at the University of Virginia. She is currently developing high content imaging assays using iPSC-derived neurons and iNeurons  from healthy and Alzheimer's disease patients. She has worked in the drug discovery field for over 20 years in academia and in industry.

Ishita Mili

Artistic Director


Ishita Mili is a Bengali American Choreographer, Director of IMGE Dance LLC, and US Sales Associate for acCELLerate. After extensively training in Indian classical, folk, and hip hop dance in NJ, Ishita founded to use her cultural roots to share global stories with artists of diverse backgrounds. IMGE has since been highlighted at Kala Ghoda Arts Festival, New Victory Theater, Seattle International Dance Festival. Ishita was also featured in Dance Informa and Pulse Magazine UK as a rising South Asian artist, and was most recently Co-Choreographer of "HAIR" The American Rock Musical at Asolo Repertory Theater. Ishita also holds a BS in Chemistry and a Masters of Business and Science in Drug Discovery and Development, and has been working with acCELLerate since 2018 to expand and support the use of Assay Ready Cells transatlantically.

Colin Cox

Director of Automation

Seer, Inc.

Lab automation engineer and molecular biologist specialized in scaling, development, and teams. Extensive experience with liquid handlers and integrated workcells in R&D and factory settings.

I teach 3D printing, am a certified rescue SCUBA diver, and am passionate about D&I programs.

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.

Ashley Wallace, Ph.D.

Assistant Director of Education and Outreach

University of Pennsylvania

Ashley J. Wallace, Ph.D. is the Assistant Director of Education and Outreach for the Laboratory for Research on the Structure of Matter (LRSM), an NSF-funded center for materials science research, at the University of Pennsylvania. She is the immediate past Diversity and Education Coordinator for the Center for Engineering MechanoBiology (CEMB), an NSF-funded science and technology center.

Dr. Wallace obtained a BS in Chemistry from Southern University and A&M College (SUBR) and her doctoral degree from the Department of Chemistry at THE Ohio State University (OSU), where she designed self-assembling amphiphilic materials for early detection of cancer tumors via MRI under the supervision of Dr. Joshua Goldberger. Upon completing her doctoral program, she realized her desire to combine her love for science with general education. In her current position, Dr. Wallace’s scientific repertoire and commitment to developing a new generation of scientific leaders for an ever-evolving workforce is shown through managing a well-versed portfolio of programs. She is also heavily involved in the development and implementation of policies that support diversity initiatives and fosters a culturally inclusive scientific community.

Aiming to promote and increase public awareness of STEM relevance in society to communities that are disproportionally underserved, Dr. Wallace has held a number of leadership roles as an active member of the National Society of Black Engineers Greater Philadelphia Professionals (NSBE GPP) Chapter and the National Organization for the Professional Advancement of Black Chemists and Chemical Engineers (NOBCChE). In 2020, she successfully organized NOBCChE’s first all-virtual national conference, and was awarded the 2020 NOBCChE Presidential Award, recognizing her for her leadership as an advocate for underrepresented communities in science, technology, engineering, and mathematics (STEM). In 2021, Dr. Wallace was elected to be serve NOBCChE as an Executive Board Member.

Hakim Yadi


Closed Loop Medicine

Peter E. Wais, PhD

Assistant Professor of Neurology


Peter E. Wais, Ph.D., Assistant Professor in Residence, Department of Neurology, UCSF

After a career in industry, which culminated as chief executive for companies producing basic sheet steel and pure chocolate, I redirected my energy and curiosity toward basic research in the cognitive neuroscience of long-term memory. I made the transition from leadership of an industrial organization to graduate school at UCSD, where I developed my thesis in cognitive neuroscience about the roles of the hippocampus in recognition memory.

My current research focus involves a translational neuroscience approach in a cognitive training intervention that targets sustained improvement in capabilities for long-term memory (LTM) and cognitive control. My goal in this research is to develop an effective, practically useful cognitive intervention that remediates high-fidelity LTM capabilities in older adults diminished by mild cognitive impairment (MCI).

Timothy Ruckh, PhD

Associate Director, Digital Health


Tim Ruckh is an Associate Director in AstraZeneca's R&D Digital Health group. In his role he supports clinical stage drug programs with aspects of their digital strategy that focus on remote clinical data collection using devices and wearable sensors. Tim's academic training was in Mechanical (B.S, M.S) and Biomedical (Ph.D) Engineering, and he was a postdoc at Massachusetts General Hospital and Northeastern University before joining the private sector at Google [X], later becoming Verily Life Sciences, and AstraZeneca. His current focus is on developing and implementing digital health technologies to collect key clinical trial endpoint data in order to increase efficiency in clinical development.

Silvia Scaglione, Ph.D.

Chief Scientist


She received in 2005 the Ph.D. in Bioengineering at the University of Genoa, Italy.

Since 2010 Silvia Scaglione is permanent Researcher at National council of Research (CNR).

She is founder and chief scientist of React4life s.r.l., an innovative biotech company that develops organ on chip technologies for accelerating the human disease understanding and novel personalized therapies development; React4life has won several international awards and projects, such as H2020 SME Instrument Phase 1, seal of Excellence SME phase 2, Innovation Radar (2021) as best Health technology.
Scaglione is author of more than 80 international peer-reviewed papers, book chapters, author of 7 patents.

Rachel Chasse

Group Lead - Digital Operations & Qualifications


Rachel Chasse is a Group Lead, Digital Operations & Qualifications at AbbVie. Previously, she was the founding Director of Innovation at the Digital Medicine Society (DiMe). At DiMe, she curated scientific content, led patient engagement and equity initiatives, and developed content for the Playbook, the essential industry guide for developing successful digital clinical measures. Prior, she supported the digital clinical team at MindMedicine, developing successful digital, remote data capture paradigms supporting psychadelic drug development. Before that, she was in the Digital Medicine group at Pfizer exploring innovative technological approaches to drug development, including developing the industry-first on-site lab using digital medicine tools (wearables, ambient sensors, etc). Rachel is based in Chicago, USA.

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).

Charles Fracchia, CEO



Charles Fracchia is the founder of BioBright, a Boston-based company that automates the secure data collection and analysis from laboratory and biomanufacturing environments. BioBright was initially funded by DARPA to create DarwinSync: the first -and continues to be the only- scalable and end-to-end encrypted data collection and analytics system for the life sciences market.

Mr. Fracchia is also the Co-Founder of BIO-ISAC, an international organization that addresses threats unique to the bioeconomy and enables coordination among stakeholders to facilitate a robust and secure industry.

Charles received his graduate education between the MIT Media Lab and Harvard Medical School and obtained his bachelor’s degree from Imperial College London. Charles gained critical experience from his work at IBM Research and Ginkgo Bioworks where he was respectively the first synthetic biologist and first full-time person outside of the founding team. He has received a number of awards including MIT Technology Review’s 35 under 35, IBM PhD fellowships and the Extraordinary Minds fellowship.
In 2021, the US Defense Advanced Research Projects Agency (DARPA) named Charles Fracchia to its Information Science and Technology (ISAT) Study Group.

Joshua Kangas, Ph.D.

Assistant Teaching Professor

Carnegie Mellon University

A successful Computational Biology researcher will have a strong understanding of computational techniques and the biological processes and techniques underlying the development of the data they are analyzing. In the courses Joshua teaches at Carnegie Mellon University, students generate experimental data in wet-lab experiments and learn to apply computational techniques for the analysis of those data. Joshua constantly looks for ways to make our course offerings as modern as possible in both the wet-lab and computational techniques learned by students. At times, this has included modernizing classic labs or generating new modules based on novel research. He teaches courses for high school students, undergraduates, and graduate students (M.S. and Ph.D.).

He was also integral in the design and setup of the Automation Lab used by the M.S. Automated Science program at Carnegie Mellon University.

Brian O'Sullivan

Senior VP Commercial

HighRes Biosolutions

Brian joined HighRes in March 2014 as the head of sales and marketing. In his eight years with the company, he and his team built a dynamic global sales, marketing, applications and service/support organization spanning the globe. Brian has more than 20 years experience selling, marketing, demonstrating, breaking, servicing lab automation solution. The solutions range from basic liquid handling workstations to enterprise level modular, mobile robotic automation data factories.

Toby Blackburn, MBA

Head of Business Development and Strategy

Emerald Cloud Lab

Toby Blackburn serves as the Head of BD and Strategy at Emerald Cloud Lab (ECL), a physical laboratory which scientists can access remotely via the internet that allows them to run, analyze, and interpret experiments without setting foot in the lab. He holds an MBA from Duke University’s Fuqua School of Business, and a B.S. in Chemical Engineering from North Carolina State University.

David R. Walt, Ph.D.

Hansjörg Wyss Professor of Bioinspired Engineering

Harvard Medical School, Brigham and Women’s Hospital, Wyss Institute at Harvard

David R. Walt is the Hansjörg Wyss Professor of Bioinspired Engineering at Harvard Medical School and Professor of Pathology at Harvard Medical School and Brigham and Women’s Hospital, is a Core Faculty Member of the Wyss Institute at Harvard University, Associate Member at the Broad Institute, and is a Howard Hughes Medical Institute Professor. Dr. Walt is co-Director of the Mass General Brigham Center for COVID Innovation. Dr. Walt is the Scientific Founder of Illumina Inc., Quanterix Corp., and has co-founded multiple other life sciences startups including Ultivue, Inc., Arbor Biotechnologies, Sherlock Biosciences, Vizgen, Inc., and Torus Biosciences . He has received numerous national and international awards and honors for his fundamental and applied work in the field of optical microwell arrays and single molecules. He is a member of the U.S. National Academy of Engineering, the U.S. National Academy of Medicine, a Fellow of the American Academy of Arts and Sciences, a Fellow of the American Institute for Medical and Biological Engineering, a Fellow of the American Association for the Advancement of Science, a Fellow of the National Academy of Inventors, and is inducted in the US National Inventors Hall of Fame.

Raven Solomon

Diversity, Equity, and Inclusion thought leader

RAVEN SOLOMON is a global Diversity, Equity, and Inclusion thought leader and nationally recognized keynote speaker who helps organizations get future-ready by understanding generations, racial equity, and their intersection.

Raven's mission is simple-- to solve for racial inequity by breaking down generational and racial barriers in the workplace, replacing them with empathy and synergy that fosters productive working relationships, drives business results, and prepares organizations to compete in the not-so-distant future.

She is the author of the 2019 release Leading Your Parents: 25 Rules to Effective Multigenerational Leadership for Millennials and Gen Z, where she shares leadership principles and practical advice for young professionals seeking to transition into leadership positions in today’s diverse workplace, and the founder of the Charlotte-based Center for Next Generation Leadership and Professional Development, a startup focused on providing softskill development to the leaders of tomorrow. In her spare time, Raven consults with Franklin Covey, the world leader in leadership development, in the area of unconscious bias and is the host of The Generational View Podcast.

Raven has helped tens of thousands, from podiums around the world, close the gaps inside of dozens of industry-leading companies, and create sustainable cultural change. She’s also consulted with household brands in the areas of generational diversity & inclusion and early talent development and retention. As the valedictorian of her college graduating class and one of the youngest-ever executives in the Fortune 50 company with which she spent nearly a decade, she has always shown that her approach to leading and influencing people yields results.

Carolyn Bertozzi, PhD

Anne T. and Robert M. Bass Professor of Chemistry, Professor of Chemical & Systems Biology and Radiology (by courtesy), Baker Family Director

Stanford ChEM-H

Carolyn Bertozzi is the Baker Family Director of Stanford ChEM-H and the Anne T. and Robert M. Bass Professor of Humanities and Sciences in the Department of Chemistry at Stanford University. She is also an Investigator of the Howard Hughes Medical Institute. Her research focuses on profiling changes in cell surface glycosylation associated with cancer, inflammation and infection, and exploiting this information for development of diagnostic and therapeutic approaches, most recently in the area of immuno-oncology. She is an elected member of the National Academy of Medicine, the National Academy of Sciences, and the American Academy of Arts and Sciences. She also has been awarded the Lemelson-MIT Prize, a MacArthur Foundation Fellowship, the Chemistry for the Future Solvay Prize, among many others.


Opening Keynote Presentation: Therapeutic opportunities in glycoscience
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Open to view video. Cell surface glycans constitute a rich biomolecular dataset that drives both normal and pathological processes. Their “readers” are glycan-binding receptors that can engage in cell-cell interactions and cell signaling. Our research focuses on mechanistic studies of glycan/receptor biology and applications of this knowledge to new therapeutic strategies. Our recent efforts center on pathogenic glycans in the tumor microenvironment and new therapeutic modalities based on the concept of targeted degradation.
Featured Keynote Presentation: The Clear Case for Diversity, Equity and Inclusion in Life Sciences
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Open to view video. In this informative and inspiring keynote, Raven breaks down the connection between equity and generations that every organization needs to know and lean into to thrive in a marketplace that is growing more racially and ethnically diverse by the decade. She helps attendees of all backgrounds understand how and why a generation can impact how they view, understand, and even combat racism. Attendees will leave with greater clarity on the role their generation can play in fighting for racial equity, and how to effectively collaborate with other generations in that pursuit.
Closing Keynote Presentation: Bringing Biomarkers from Discovery to Clinical Impact
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Open to view video. New technologies can facilitate biomarker discovery by increasing throughput, detecting biomarkers at lower concentrations, and enabling detection of molecules that haven’t been discovered previously. Biomarker discovery, however, is only the beginning of the process. Biomarkers must be validated and methods must be developed for measuring them reproducibly with sufficient throughput to be used in both research and the clinic. The development of new biomarker technology platforms for both discovery and wider implementation involves automation and scaleup to enable biomarker use in research, drug development, and clinical diagnosis.
Advances in Bioanalytics and Biomarkers
Acoustic Ejection Mass Spectrometry: A Versatile Technology for Fast Bioanalysis and Fully Automated High-Throughput Screening
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Open to view video. The incorporation of electrospray ionization (ESI)-based mass spectrometry (MS) into the portfolio of high-throughput capable readout technologies has historically been hampered by the lack of suitable interfaces delivering the sample to the ESI ion source. Here, classical approaches face different bottlenecks such as limited sampling speed, analyte carry over, sample consumption, as well as the need for laborious sample preparation. The introduction of acoustic ejection mass spectrometry (AEMS) has provided an elegant solution by combining fast and contactless acoustic sampling with sensitive and accurate MS-based analyte detection. Our investigations on this novel technology resulted in two cutting-edge setups. First, a breadboard system combining a generic acoustic droplet ejection (ADE) system with an open port interface (OPI) was used to capture nanoliter droplets directly ejected from microtiter plate wells and to transport these to the ESI-source for MS analysis. This system was used to assess and optimize critical performance parameters related to analytical throughput and system stability. Maximum achievable sampling rates of up to 6 Hz are demonstrated for various ADME assays together with stress tests regarding ion suppression and system robustness. Complementary, the first commercial AEMS system (ECHO MS, Sciex) was integrated into Boehringer Ingelheim screening automation and modified to meet high-throughput screening (HTS) robustness requirements. This was achieved by combining custom software interfaces, in-house hardware modifications, and learnings from a validation project aiming at the identification of inhibitors of the cyclic GMP-AMP synthase (cGAS). We describe the method optimization to enable sensitive and accurate determination of enzyme activity and inhibition in a miniaturized 1536-well microtiter plate format. Furthermore, we present results from both a validation single-concentration screen using a test set of 5,500 compounds, and the subsequent concentration-response testing of selected hits in direct comparison with a previously established MALDI-TOF readout. In agreement with our observations on the breadboard system, passive and active cleaning options are demonstrated to effectively remain optimum system performance during HTS campaigns or to recover the ready state of the system after a blocked OPI from samples with high matrix loads. Finally, the results from the first HTS campaign using the fully automated AEMS readout at Boehringer Ingelheim are presented as the final validation of the method, demonstrating the system’s efficient and robust performance in a 1.2 million compound library screen.
Compound Confirmation using Acoustic Ejection-Open Port Interface Mass Spectrometry (AE-OPI-MS) Analysis in Support of High-Throughput Screening Activities
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Open to view video. Compound Management (CMD) has the responsibility to oversee the Pfizer compound collection and ensure that the integrity of the collection is of high quality. The sample QC (sQC) process, within CMD, is the current benchmark for assessing compound quality as it employs UPLC-MS to assess the basic requirements of compound quality, purity and mass confirmation. The throughput of sQC is driven by two factors, the number of compounds in the queue and the instrumentation available. The current sQC operations were designed to support lead optimization activities, where the number of active compounds range in the hundreds. High-Throughput screening activities, however, can have compound queues in the thousands which can overburden the sQC process. Acoustic Ejection Open Port Interface Mass Spectrometry (AE-OPI-MS) employs acoustic dispensing technology to introduce samples to the mass spec alleviating the chromatography requirement while increasing the rate of analysis over 3fold. AE-OPI-MS methodology has been developed to complement the traditional sQC analysis and expand the analytical capabilities to support high throughput screening. Software improvements were also developed to enable the analysis to include purity assessment.
Coordinated automation to support biomarker discovery using machine learning
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Open to view video. "Background Machine learning has opened new opportunities for biomarker discovery, but this analytic approach requires very large datasets for proper model construction.  Additionally, unbiased discovery necessitates consideration of a large number of input variables from each sample, while minimizing required sample volumes. All of these issues must be considered to avoid constraining model development due to insufficient power. We present our experience designing a high throughput analytic pipeline for evaluation of circulating microRNAs as novel biomarkers for diagnosis of women’s cancers. Methods The Mass General Brigham BioBank was interrogated using the Research Patient Data Registry, a centralized clinical data registry/warehouse, for participants with known gynecologic histories, at least three years of clinical follow-up data, available data from the electronic health record for query, and known genotype profiles. Barcoded, deidentified samples were transferred to the Gynecologic Oncology Laboratory at Brigham and Women’s Hospital. Working with Hamilton Storage, we designed a high-capacity automated sample storage, retrieval, and processing pipeline for aliquoting and analysis of the study samples. To measure the miRNAs, we worked with Abcam, Inc to design a custom panel of 180 microRNA probes using the Fireplex particle technology, a porous bio-inert hydrogel that allows target capture throughout the 3D volume with spatial resolution to cover 68 distinct microRNAs per 50 ul sample well.  The Fireplex® platform was adapted to a Hamilton Starlet® liquid handling robot by adding a positive pressure vacuum manifold to the deck to automate plate processing. Results A cohort of 10,000 study subjects was assembled from the Mass General Brigham BioBank. Samples were subaliquoted into low profile 0.6 ul 2D barcoded Hamilton tubes and placed into barcoded racks for storage in a Hamilton SamHD® automated storage system. After retrieval of samples, tubes were scanned, inventoried, and decapped using a Hamilton LabElite ID® capper/decapper, then placed onto the Starlet® liquid handling robot. The Fireplex® panel was designed to be distributed over 3 sets of plates. With full implementation of the system, we are now completing circulating miRNA profiles of 200 study subjects per week, which comprises 36,000 separate data points, and we will complete the 10,000-patient cohort in just over a year. Conclusions A coordinated approach to sample identification, inventory management, and high dimensionality analysis is required to use machine learning approaches to biomarker discovery. Automating each step of the process increases efficiency while allowing accurate sample tracking and maximization of each sample."
Defining The Pharmacometabodynamics of Gefitinib after Intravenous Administration to the Mouse by UHPLC/MS and UPLC-IM-MS Study
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Open to view video. Gefitinb, an anilinoquinazoline inhibitor of thymidylate kinase (selective for the epidermal growth factor receptor (EGFR)), was originally developed as a treatment for non-small cell lung cancer.  In this study Male C57 BL6 mice were dosed IV with gefitinb (10 mg/kg) and then microsampling combined with a rapid (sub 5 min) UHPLC/qqqMS used to determine the pharmacokinetics of the drug and its major circulating metabolites. In addition, 10 circulating metabolites  of the drug and 15 present in  the urine were characterized using UHPLC/IM/HRMS. The addition of an IM separation gave rise to much improved MS data thereby aiding the identification of several novel glucuronide metabolites. As well as the drug and its metabolites untargeted metabolic phenotyping (metabonomics/metabolomics)  enabled a range of time-related effects of the  drug on endogenous metabolism to be detected. Changes in endogenous metabolite profiles,  both increases and decreases in amounts,  appeared shortly after dosing and had largely returned to their predose values by 24hrs. The changes in the amounts of endogenous metabolites excreted in the urine mirrored to some extent the plasma pharmacokinetics of the drug demonstrating a possible pharmacometabodynamic effect. This type of combined drug and endogenous metabolite profiling may this represent a method for better understanding the pharmacology of drugs in terms of the way that their effects modulate the metabolic pathways of the organisms exposed to them, including patients.
Development of Fluorescence and Mass Spectrometry Based Detection Assays for assessment of TMPRSS2 inhibition as Potential Treatment of COVID-19
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Open to view video. The enzyme TMPRSS2 plays a critical role in entry of SARS-CoV-2 virus into a host cell. A fluorogenic tripeptide substrate was used to develop and validate biochemical screening assays for identification of TMPRSS2 inhibitors. In addition, HT-LC/MS/MS and Acoustic-Ejection MS (AEMS) assays were developed using a physiologically relevant, non-labeled peptide substrate. Validation of the LC/MS/MS assay was demonstrated by obtaining similar IC50 values to those obtained from the fluorogenic assay. Coherence of the AEMS assay was demonstrated by obtaining similar substrate Km values to those obtained from the LC/MS/MS assay. Herein we compare label and label-free detection methods with respect to analytical performance, cost, and routine usage in context of a screening campaign using two TMPRSS2 peptides as marker substrates.
Enabling the Field: A Strategic Perspective on Molecular Insight
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High throughput covalent fragment screening with MALDI mass spectrometry
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Label Free Bioanalytical Technologies: Emerging Fields of Application
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MALDI Imaging in drug discovery
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Metabolomics and Lipidomics Technologies for Target Discovery and Mechanism Deconvolution.
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Open to view video. In this lecture we will give an overview of recent developments in targeted and untargeted metabolomics and lipidomics analysis. Pitfalls and challenges for implementing metabolomics and lipidomics in drug discovery will be discussed. Showcasing specific examples, the use of lipidomics and metabolomics for target discovery, mode of action and physiological response marker elucidation will be explained. Next to a general introduction to the topic we will specifically focus on non-alcoholic steatohepatitis (NASH) and the use of lipidomics technologies. Showing data from one of our chemical probes in a humanized preclinical mouse model we will discuss the application of lipidomics and metabolomics starting with screening in a whole cell assay, followed by the definition of physiological response and target engagement markers and finally deciphering the mode of action.
Target deconvolution using compressed cellular thermal shift assay (cCETSA) influences key project decisions
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Open to view video. "Target deconvolution of small molecules is critical to understanding a potential therapeutics mechanism of action and safety liabilities. Although affinity pull down approaches have greatly expanded our knowledge of drug targets,  derivatization of the drug requires domain expertise in medicinal chemistry. Furthermore, affinity pull downs are not feasible when a drug molecule has a steep SAR that precluded linker attachment or lack of chemistry resources. Cellular thermal shift assay coupled with high-resolution mass-spectrometry (CETSA®-MS) has shown to be indispensable method for unbiased, proteome-wide, chemistry free target deconvolution by measuring changes in protein thermal stability upon compound binding within physiologically relevant system. The method is increasingly being employed both in mechanism of action (MoA) studies and to identify primary and off-targets of candidate drug molecules. In collaboration with Pelago, AstraZeneca have applied cCETSA (compressed CETSA), a more time and cost effective format of next generation CETSA MS on drug discovery projects. Here we would like to present the application of cCETSA in AstraZeneca for compounds at various project stages like phenotypic HTS hit, candidate identification drug, lead optimisation identification drug, literature compounds there by influencing key project decisions."
Unbiased high-throughput MALDI-TOF MS lipid and metabolite screening assays in primary human cells for drug discovery
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Open to view video. "Matrix-assisted laser/desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become a powerful tool for high-throughput screening (HTS) approaches in drug discovery, overcoming the shortcomings of conventional fluorescence label-based technologies. So far, most of the MALDI-TOF based HTS approaches have focused on in vitro assays with rather simple readouts, and have been limited mainly, but not exclusively, to peptide/protein-centric activity assays. Currently, comprehensive and unbiased HTS approaches to track metabolites with MALDI-TOF have not been explored for drug discovery applications. Metabolites are involved in every aspect of biology, and since the metabolome is highly dynamic in nature and a sensitive indicator of phenotype, we can take advantage of this to identify metabolic markers to be applied for treatment response in drug discovery. Although, phenotypic cellular assays using MALDI-TOF MS are possible using higher molecular masses, the capability of MALDI-TOF to detect compounds in the low mass range is generally considered limited due to interference peaks brought by the matrix. Metabolomics-based drug discovery presents therefore an exciting challenge for MS analysis as the system becomes inherently more complex. Herein, we apply this technology for cellular assays, specifically to detect metabolites and lipids in a comprehensive, untargeted, and unbiased HTS approach for drug discovery in idiopathic pulmonary fibrosis (IPF). Primary human nasal epithelial cells were used to develop a cellular assay pipeline for untargeted metabolite phenotypic identification using MALDI-TOF MS.  Multiple IPF-relevant stimuli and inhibitors were tested to see if stimulation and inhibition could be distinguished in the assay. Next, different sample preparation conditions, such as testing different matrices, additives, derivatization reagents, and extraction protocols, were investigated to ensure the most effective analysis for metabolites and lipids. All the parameters were optimized using Mosquito-TTP Labtech liquid handling robot to allow a systematic screening of a large number of combinations to find the best conditions. Moreover, all the protocols were simplified and adapted to HTS compatible platforms to ensure a smooth translation from an academic laboratory to industry. Preliminary testing revealed spectra that could be distinguished between the unstimulated, stimulated cells, and stimulated cells with inhibitor, in both the low and high mass region (m/z 200-1000 and 2-20 kDa). Using principal component analysis (PCA), hierarchical clustering, and machine learning strategies, a subset of peaks was identified to be unique to each condition. This data supports that it is possible to elucidate important metabolic features of cells in modelled pathophysiology. This approach has the potential to be further optimized as an automated HTS drug discovery assay in the industrial setting."
Assay Development and Screening@@@Innovation Award
Sorting Single T-cells Based on Cytokine Secretion Using 3D Structured Microparticles
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Open to view video. "The use of engineered immune cell-based therapies in treating hematologic malignancies has shown exciting results with improved patient outcomes including complete remissions, however, there are still significant variations in outcomes between patients and clinical trials. The biological basis behind these variations is still not well understood, but a growing body of literature has alluded to certain T-cell functional properties such as high proliferative potential and propensity to secrete multiple cytokines simultaneously as key drivers of response. However, tools to analyze and select populations of cells based on functional properties, such as secreted products, are critically lacking. Current immune cell phenotyping approaches are limited by heavy reliance on screening differentially expressed surface receptors which fails to describe their functional potency. Therefore, there is a critical need to develop new platforms to sort based on cell function, such as level and types of secreted cytokines to identify gene expression signatures associated with functional responses, uncover cell surface markers that are more descriptive of optimal functional phenotypes, or directly sort starting cell populations with higher therapeutic potential during manufacturing of cell therapy. Here, we report a workflow for the rapid screening and sorting of individual T-cells based on secreted factors that are accumulated on 3D-structured microparticles using a standard fluorescence activated cell sorter (FACS). Our cavity-containing hydrogel microparticles (nanovials) can be loaded with single T-cells and encapsulated into uniform droplets by simple pipetting steps to confine secreted cytokines for capture on the particle. Captured cytokines (TNF-α and IFN-γ) are each labelled with a fluorescent reporter antibody, and the corresponding cells are sorted based on the secretion level using a commercial FACS. Improving on our previous work to adhere Chinese Hamster Ovary cells and capture secreted antibodies on nanovials, we have further modified the nanovials to be optimized for T-cell cytokine secretion assay by incorporating anti-CD45 antibody as a new binding moiety on their surface and reducing their size down to 35 μm in diameter for improved cell loading efficiency and high-throughput sorting. We have demonstrated our ability to capture and label TNF-α, IFN-γ secretions produced from single T-cells and sorted nanovials containing cells using fluorescence height and area signals above a threshold value. By gating on a combination of fluorescence area and height parameters, we can differentiate secreted cytokine signal on nanovials from signal solely from presumably permeabilized or dead cells. Cells also maintained their viability after sorting, in which they can be further analyzed for their growth and functionality post-sort. Our technology can quantitatively screen and sort potentially millions of viable cells based on their cytokine secretion levels, which will aid in discovery of T-cell receptors and surface markers responsible for robust functional responses, improving upon the current paradigm of cell therapy."
3D Screening of Lung Cancer Spheroids using Natural Products
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Open to view video. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and is about 84% of all lung cancer cases that are diagnosed. NSCLC remains one of the leading causes of cancer-associated death, with a 5-year survival rate less of 25%. This type of cancer begins with healthy cells that change and start growing out of control forming lesions or tumors. Understanding the dynamics of how the tumor microenvironment promotes the cancer initiation and progression that will lead to the cancer metastasis is crucial to help in the process of identifying new molecular therapies. Primary cell 3D cell culture models have received renewed recognition not only due to their ability to better mimic the complexity of in vivo tumors as a potential bridge between traditional 2D culture and in vivo studies. 3D cell cultures are now cost effective and efficient and have been developed by combining the use of a cell-repellent surface and a novel angle plate adaptor technology. We also have access to one of the world’s largest repositories of Natural Products (NPs) at Scripps. NPs are typically not very well represented in the current drug discovery libraries and can provide a new insight to discover leads that could potentially emerge as novel molecular therapies. We combined these technologies for 3D cell culture primary screening in 1536 well format using ten NSCLC cells lines (5 wild type and 5 mutant) against ~1280 natural products. After further evaluation, the selected active NPs identified were prioritized to be screened against all 10 NSCLC cell lines as concentration response curves to determine the efficacy and selectivity of the compounds between wild type and mutant 3D cell models. Here, we demonstrate fully automated 3D screening using natural products that may identify NPs from microorganisms that can provide a future use toward human cancer.
A coculture platform to screen therapeutic bacteria within tumor spheroids
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Open to view video. The prevalence of tumor-colonizing bacteria has spurred new research directions including the engineering of bacteria to locally deliver therapeutics to tumor environments. However, a central challenge for translating this next-generation therapy to clinics is the lack of tools to identify potent therapeutic strains in tumor environment. Thus, the vast majority of the past studies have relied on animal models that only test a handful of therapeutic candidates. To address this challenge, we developed a novel 3D multicellular coculture platform that enables parallel and continuous culture of diverse bacteria in tumor spheroids, recapitulating selective bacterial growth in solid tumor. Leveraging the high throughput nature of the platform, we screened a library of therapeutic bacteria expressing cytotoxic molecules. We identified novel therapeutic bacteria that significantly reduced tumor size and validated similarities in efficacies using a syngeneic mouse model. Utilizing the stability of the multicellular culturing system, we also tested the performance of engineered bacterial biosensors in a physiological environment. We constructed oxygen, pH and lactate sensors that controls bacterial growth, and confirmed their activities in tumor spheroids. This approach identified a strain that reduced off-target colonization in an animal model. These approaches can be utilized towards accelerating the development of therapeutic bacteria for clinical applications.
Adding Dimensions to Multiplex Molecular Imaging
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Open to view video. "Imaging of living specimens (intravital imaging) offers a means to draw upon the growing body of high-throughput molecular data to better understand the underlying cellular and molecular mechanisms of complex events ranging from embryonic development to disease processes. However, imaging approaches are challenged by major tradeoffs between spatial resolution, temporal resolution, field of view and the limited photon budget. We are attempting to advance this tradeoff by constructing faster and more efficient light sheet microscopes that maintain subcellular resolution. Our two-photon light-sheet microscope combines the deep penetration of two-photon microscopy and the speed of light sheet microscopy to generate images with more than ten-fold improved imaging speed and sensitivity. As with other light sheet technologies, the collection of an entire 2-D optical section in parallel dramatically speeds acquisition rates. By adopting two-photon excitation the light sheet illumination is far less subject to light scattering, permitting subcellular resolution to be maintained far better than conventional light sheet microscopes. This combination of attributes permits 4D cell and molecular imaging with sufficient speed and resolution to generate unambiguous tracing of cells and signals in intact systems. To increase the 5th Dimension, the number of simultaneous labels, we are refining new multispectral image analysis tools that exceed the performance of our previous work on Linear Unmixing by orders of magnitude in speed, error propagation and accuracy. These new analysis tools permit rapid and unambiguous analyses of multiplex-labeled specimens. In parallel, we have refined label-free approaches so that imaging and sensing can be more extended to patient-derived tissues and even human subjects. The low concentrations and low sensitivity of the techniques can make single cell approaches challenging. We have refined fluorescence lifetime approaches (FLIM), combining it with multispectral tools to optimize intravital imaging in these challenging settings. Combined, these imaging and analysis tools offer the multi-dimensional imaging required to follow key events in intact systems as they take place, and to allow us to use noise and variance as experimental tools rather than experimental limitations."
Base editing screens to define drug-target interactions
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Open to view video. CRISPR technology has enabled the manipulation of genetic information with tremendous scale and flexibility. Here we will present screens utilizing Base Editor technology, which enables amino-acid-level resolution of drug-target interactions. Such screens can be used to identify a resistance mutation that helps to prove the actual target of a less-characterized small molecule. Additionally, this approach can provide insight into potential resistance mechanisms long before seeing what arises in patients. The low upfront costs of generating a pooled, base editing library, coupled with the small-scale and relative ease of execution, argues for applying this technique early in the drug discovery process. 
Binding site hotspot mapping with photo-affinity labeling
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Open to view video. All biological processes are governed by chemical signals relayed through protein networks. These small molecule signals can inhibit, enhance, or impart new functions to proteins through direct associations to binding sites on a protein that drive alteration of the broader proteomic network.  To discover binding site hotspots in the global proteome, we developed a chemical proteomics platform termed small molecule interactome mapping by photo-affinity labeling (SIM-PAL).  SIM-PAL uses a small molecule carrying a photo-affinity label to capture molecular interactions within the global proteome.  After treatment of live cells with the small molecule, the resulting interactions are captured by photochemical conjugation and affinity enriched.  The enriched proteins are identified by proteomics and the exact binding sites are mapped by isotope-targeted mass spectrometry (MS).  Isotope-targeted MS enables the selection of small molecule-linked peptides, representing binding sites, against a background of unlabeled peptides for high-confidence identification of the underlying molecular structure.  SIM-PAL combines phenotypic cellular assays with high-resolution structural measurement of where and when a small molecule is binding throughout the whole proteome using the discovery power of MS.  Applications of SIM-PAL to bioactive small molecules and the structural implications of binding site hotspots from photo-affinity labeling chemistry will be described.
Biochemical and biophysical approaches for accelerating the discovery of small molecules for differentiation targets
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Chemogenomics interrogation of modulators of intestinal fibrosis using a multiparametric imaging- and biomarker-based approach
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Open to view video. Intestinal fibrosis is a common complication of several enteropathies with inflammatory bowel disease being the major cause. The progression of intestinal fibrosis may lead to intestinal stenosis and obstruction. Even with an increased understanding of tissue fibrogenesis, there is no approved treatment for intestinal fibrosis. To further understand the fibrotic mechanism and address this unmet medical need, we carried out a high throughput small molecule screen covering nearly 5000 compounds with known targets or mechanisms, which have passed Phase I clinical trial or have been approved by the FDA. The screen was performed using human intestinal myofibroblasts under pro-fibrotic TNFα stimulus. As CXCL10 is one of the most up-regulated biomarkers in intestinal inflammatory-associated fibroblasts, we used CXCL10 as a secretory biomarker as a readout for TNFα signaling modulation. In parallel, we used cell painting, a scalable image-based morphology assay, to identify compounds that are able to morphologically reverse the activated fibrotic phenotype back to normal. By using two divergent analytical methods, we identified compounds and target classes that are shared between the two approaches and a few major targets that are unique to each individual method. We validated the primary screen hits with other pro-fibrotic stimuli treated human intestinal myofibroblast cell types. The target ID platform described here represents significant improvements over conventional methods by incorporating a multi-parametric phenotypic approach using disease-relevant cells and stimuli.
Chemoproteomics applications for target deconvolution, mapping of druggable pockets and exploration of novel modalities
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Open to view video. Quantitative chemoproteomics approaches, such as the combination of small molecule affinity chromatography or photo-affinity labeling with mass spectrometry-based protein identification and quantitation, are key tools for target deconvolution for non-covalent and covalent bioactive compounds such as hits from phenotypic screens. For covalent compounds and probes, in addition to providing information about the cellular protein interactome of a compound of interest, chemoproteomics workflows also provide more granular information about the specific modified amino acid. This allows the mapping of solvent-exposed druggable pockets in a forward-looking manner, ligands for which will be either functional modulators or silent binders for which the binding event does not lead to a functional consequence. However, the recent rise of chemically induced proximity-based approaches using heterobifunctional molecules as exemplified by targeted protein degradation (TPD) has enabled the functionalization of such silent binders and thus further increased the interest in proteome-wide ligandibility studies using chemoproteomics approaches. For TPD, such a heterobifunctional molecule consists of a E3 ubiquitin ligase-recruitment module linked to a ligand for the target of interest with the resulting recruitment event leading to ubiquitination and subsequent degradation of the protein of interest. In addition to E3 ligases, an increasing number of active enzyme classes, including DUBs, kinases and phosphatases, have been successfully recruited for target modification and modulation using suitable modules for recruitment of the active form of the enzyme. These chemical biology efforts are quickly increasing our repertoire of modalities for therapeutic intervention in disease. Applications of chemoproteomics in the various contexts mentioned above will be presented and discussed.
DNA-encoded library technology (DELT) as an efficient and versatile hit finding platform in lead discovery
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Open to view video. "DNA-encoded library technology (DELT) is a powerful screening platform for the fast and efficient identification of novel chemical matter from ultra-large compound collections in a relatively simple and fast in vitro-based affinity selection experiment (= screen) against today’s most challenging therapeutic targets in biomedical research. In analogy to antibody phage display technology, DELibrary construction relies on the physical linkage of the phenotype with its genotype: specifically, DNA-encoded chemical libraries are synthesized from chemical building blocks (BBs) in a “split-and-pool” fashion or by other combinatorial means followed by a unique encoding step with DNA oligonucleotides for each BB or reaction type resulting in an exponential growth of library size (m x n → split sizes), while starting from an initial set of m + n BBs. The DNA tags serve as amplifiable and readable identity barcodes of each library member enabling multiplexed deconvolution of the chemical structure by next-generation sequencing (NGS) after elution of binders (= hits) from the target of interest. Roche has been one of the early adopters of DELT within the pharmaceutical industry, and we are continuously advancing all aspects of the technology. We are now employing DELT on a routine basis at multiple stages of our small-molecule lead discovery process and across all disease areas. In particular, the platform has become an important pillar for ligandability and tractability studies and successive prioritization of therapeutic targets in the early phase of drug discovery programs, as well as for the generation of important tool compounds, and first and foremost, for the rapid delivery of chemical starting points for our small-molecule medicinal chemistry programs. A case study presented here is using DELT to target a key component of autophagic response, ATG8 or LC3. LC3 is required for the elongation and maturation of the autophagosome and functions as an adaptor protein to recruit specific cargo for degradation. Incorporating DELT in our lead finding led to the discovery of novel ligands against this challenging target.
Evaluation of multiple immunological assay platforms to identify new targets and therapeutics
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Open to view video. Finding new therapies for immunological diseases is a significant challenge. The immune system itself is not only complex with a system of various cell types, but also highly modulated by an array of genetic and environmental factors. In addition, it is important to recognize the limitations of animal models in various aspects of recapitulating human immunity. Furthermore, potential prediction of toxic adverse events, such as cytokine release syndrome caused by antibodies can be an issue difficult to predict without the right models. In drug discovery, one way to circumvent inter-species differences is to study human immune cells directly ex vivo. Our ‘Cellular Assays and Technologies’ group is a multidisciplinary team of cellular and molecular biologists focused on supporting early and late-stage oncology and immune-oncology programs. We have developed several immunological assays using a range of primary immune cells (primary CD3+ T cells, CD4+ T cells, CD8+ T cells, macrophages, natural killer (NK) cells and PBMCs), automation and a multi-endpoint approach to both 2D and 3D in vitro models. By using tumor antigen-specific cell based assays and target- systems, we are able to perform lead selection in small molecule and antibody therapeutics. In addition, the use of these assays has allowed us to focus our work on identifying and validating new targets for immune-oncology and inflammatory diseases. Here we are presenting a selection of immunological cell assays, including T cell redirected cytotoxic assays by bridging T cells and tumor cells with bispecific T-cell engager antibodies, and antigen-specific cytotoxic lymphocyte activation assays via TCR engagement of the pMHCI (MHC class I- peptide complexes).
High content imaging of organs-on-chips: a window into colorectal cancer progression
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Open to view video. The highly complex and evolving nature of cancer makes it challenging to study. Here we describe a microfluidic organ-on-chip platform, incorporating tissue-tissue interfaces and physical forces to support novel interrogations of colorectal cancer progression. The integration of our organ-on-chip model with high content imaging and mass spectrometry based metabolomics provides for dynamic tumor cell phenotyping. Using a 3D printed organ-on-chip cradle, we employed live-cell imaging and analysis to quantify the number of tumor cells that have invaded from the epithelial channel into the vascular channel, mimicking intravasation, an early event in the metastatic cascade. The tunable nature of the organ-on-chip platform supports the modulation of tumor microenvironmental features and the resulting changes to tumor cell behavior can be measured by on-chip imaging or effluent-based analyses. We determined that peristalsis-like mechanical forces impact the invasion capacity of tumor cells, with more tumor cells undergoing intravasation into the vascular channel when peristalsis motions are present. We revealed GABAergic changes in the effluent suggestive of neurotransmitter implications in peristalsis-mediated tumor cell invasion. GABA antagonists reversed the observed tumor cell invasion phenotype, thus reducing the spread of tumor cells. This work reveals important interactions between colorectal cancer cells and their microenvironment, which can be used to prevent or delay cancer progression.
High-content analysis and Kinetic Image Cytometry identify toxic and epigenotoxic effects of HIV antiretrovirals on human iPSC-neurons and neural precursor cells
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Open to view video. Despite viral suppression due to combination antiretroviral therapy (cART), HIV-associated neurocognitive disorders (HAND) continue to affect half of people with HIV, suggesting that antiretrovirals (ARVs), themselves, may contribute to HAND. We are examining the effects of nucleoside/nucleotide reverse transcriptase inhibitors tenofovir disproxil fumarate (TDF) and emtricitabine (FTC) and the integrase inhibitors dolutegravir (DTG) and elvitegravir (EVG)) on viability, structure, and function of glutamatergic neurons and neural precursor cells (NPCs) derived from human induced pluripotent stem cells (hiPSC-neurons and hiPSC-NPCs). In studies utilizing the Microscopic Imaging of Epigenetic Landscapes (MIEL) assay, we found that TDF decreased viability of primary human NPCs and changed the distribution of histone modifications that regulate chromatin packing.  These effects may reduce neurogenesis in the adult brain, a process whose inhibition may lead to loss of cognition.  Developing methods to assay epigenotoxic effects in hiPSC-NPCs will enable further research into this process and enable testing of hypotheses regarding how dementia-associated gene variants may influence neurogenesis.  Regarding hiPSC-neurons, we are utilizing automated digital microscopy, image analysis (high content analysis, HCA), and Kinetic Image Cytometry, and we have found that DTG, EVG, and TDF decrease hiPSC-neuron viability, neurites, and synapses, and that that DTG and EVG decrease the frequency and magnitude of intracellular calcium transients.  We are also developing co-culture techniques with neurons, astrocytes, and microglia to advance the model for ARV toxicity to resemble the CNS more closely, and methods to simultaneously assay effects of test compounds on voltage and calcium activity of the cultures. Our research will establish human preclinical assays that can screen potential ARVs for CNS toxicity and develop safer cART regimens and HAND therapeutics.
Information-rich High Throughput Screening with Multiplexing Surface Plasmon Resonance
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Open to view video. "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 unlike endpoint assays like fluorescence-based assays. Multiplexing SPR systems further allow to study the interaction of a drug candidate against multiple targets simultaneously; a task which requires multiple repetitions of the same screening with other techniques. However, the throughput is often comparably low and the number of targets in a fast, efficient quantitative screening campaign is severely limited. We present an assay set-up that allows the binding assessment of a single analyte against dozens of targets or the affinity determination of one analyte against multiple targets with a single injection. Partnered with our established SPR* detection system, it’s possible to perform measurements also at high molecular weight differences between analyte and target of 10-3. Furthermore, this assay set-up facilitates the determination of thermodynamic constants at low running times due to parallel readout. Access to this information is typically relevant in subsequent lead development processes. We tested the assay set-up with multiple established assay modes for two model cases. The interaction of oligonucleotides against complementary strands and of a set of sulphonamides against multiple carbonic anhydrase isozymes confirmed the performance and robustness. Additionally, the sensitivity of our novel assay set-up was assessed with an interaction of DNP-modified amino acids (241-283 Da) against specific antibodies (150 kDa). We herewith present a SPR assay set-up with industry-leading throughput in affinity determination and multiplexing capabilities for all types of analytes. Thus, the extension of typical parameters from a SPR experiment by a quantitative selectivity assessment allows for a more informed hit selection process in screening campaigns."
Leveraging mass spectrometry for high-throughput in vitro pharmacology screening
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Open to view video. "Mass spectrometry (MS) is recognized as a key technology in biopharmaceutical research and development. Key features of the technique include compatibility with orthogonal analytical techniques such as liquid chromatography (LC), high selectivity, sensitivity, and label-free detection. Despite widespread incorporation of MS/MS in various disciplines-especially DMPK-there exists significant opportunity for leveraging the technique elsewhere in drug discovery. Early-stage in vitro pharmacology groups develop plate-based in vitro assays for a given target, measuring compound effect for purposes of hit ID as well as rank-ordering and structure-activity relationship (SAR). These assays routinely generate thousands of samples, and endpoints are typically collected by fluorescence and other indirect measurements, often requiring costly, customized reagents. Moreover, low sensitivity, specificity, narrow dynamic range and liabilities such as assay artifacts can impact screening activities and hinder project progression. In this talk we will discuss how LC-MS/MS can be applied throughout biopharmaceutical discovery, specifically early-stage in vitro pharmacology. Core benefits of LC-MS/MS will be described, and discussed in context of specific challenges, including assay biochemistry and project team needs presented in several campaigns. Additionally, emerging LC-MS/MS instrumentation and technologies will be explored as enabling platforms that can provide greater insight from high-throughput assays while conserving valuable resource."
New High Throughput Method to Automate Evaluation of Neuronal Modulatory Effects Of Glutamate Excitotoxicity Via Differential Route of Exposure
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Open to view video. Abstract: Neurological disorders affect approximately 20% of the world population and are among the top ten leading causes of disability and death. Excitotoxicity has been associated with numerous neurodegenerative diseases including amyotrophic lateral sclerosis (ALS) and Alzheimer’s. Excitotoxicity is caused by an excess of extracellular neurotransmitters like glutamate that will induce an overreaction of glutamate receptors in neurons. Excitotoxicity caused by excess extracellular glutamate could lead to cell damage and/or cellular death. Existing testing strategies are expensive, have low reproducibility and do not account for the localization (soma vs. axon) of cellular excitotoxicity. Our technology enables rapid neuronal growth on a chip, precisely organizing neuronal networks at high throughput for safety and efficacy evaluations (Magdesian et al., Biophys J. 2016; JOVE 2017). NeuroHTSTM is compatible with standard automation equipment to reproducibly test over 3,000 neurons per plate. NeuroHTSTM enables compartmentalization of neurons and supports evaluation of toxicity exposure independently to the soma as well as axon regions. Upon exposure, a suite of 7 morphological features can be evaluated in addition to biochemical screens with over 85% plate to plate reproducibility. Here we exposed soma and axons of human motor neurons grown in NeuroHTSTM to different concentrations of glutamate to model differential toxicity exposure. We measured 8 parameters per assay including: cell number, nucleic aggregation, axonal fibre thickness, axon length, branching, number of branching junctions, axon fragmentation index and neurite straightness. We observed significant differences between the two treatments in degrees of neuronal degeneration in 3 of the 8 measures: neurite length, fragmentation index, and nucleic aggregation. Neuronal degeneration is much less severe when glutamate toxicity is applied to axon only.  In this exposure, toxicity is largely localized. We demonstrated the potential of a top-down screening approach using the NeuroHTSTM. The NeuroHTSTM is the first multi-well microplate to enable compartmentalized testing of axons and soma and generate robust big data for neuronal analysis. The paradigm shift top down screening approach provides key efficiencies needed for high throughput compound screening for safety and toxicity. 
Next-Generation Pooled and Arrayed CRISPR-Cas9 screens to identify and prioritise drug targets
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Open to view video. "CRISPR screening is a transformative technology that utilises the power and precision of CRISPR-Cas9 gene editing to reveal and validate novel drug targets or to study underlying causes of disease and to explore the effect of genetic mutations on drug resistance and patient responsiveness. Horizon Discovery broadly employs two CRISPR screening formats in target ID and validation studies: pooled and arrayed, which can be utilised to answer a plethora of research questions. Pooled screens involve introducing a ‘pool’ or mixture of sgRNA into a single population of cells which enables large genome-wide screens. However, these are most commonly performed using CRISPR-knockout, which limits the exploration of biology inaccessible to knockout screening. To address this limitation, we have evolved our pooled CRISPRko screening platform to include CRISPRi (interference) and CRISPRa (activation), which can be used to down- or up-regulate endogenous gene expression, respectively. Moreover, CRISPRi and CRISPRa can be combined to deliver dual loss-of-function or dual direction screening. This strategy enables researchers to explore drug mechanisms of action, enables the identification of novel biomarkers, and can provide compelling targets for the development of combination therapies. Additionally, Horizon has recently demonstrated the amenability of our platform for conducting next generation in vivo pooled CRISPR screens in patient-derived tumor xenograft PDX mouse models, screens in spheroids/organoids and screens that utilise single-cell analysis. In arrayed CRISPRko screening, only one gene is targeted per well within multi-well plates using CRISPR libraries containing guide RNAs using the latest sgRNA design algorithms. Arrayed screens are key for functional genomic screening with multiplexed phenotypic endpoints, complex co-culture assay and for the confirmation of hits identified in pooled screens. To address the challenges of scaling arrayed screens, we have developed a range of automated workflows to perform screens in both primary and secondary cells. Finally, CRISPR-based functional studies in primary immune cells has recently received a lot of attention as it opens the doors to significant scientific discovery in crucial areas of research, specifically in immuno-oncology. However, widespread application of these screens has been limited due to their extremely technically challenging nature. To address this, Horizon has developed an innovative approach to support the robust screening of primary human immune cells including gene modified B and T cells. Any potential new target or biological behaviour identified in these screens could translate more effectively and predictively from bench to bedside. Here we present a range of these next generation pooled and arrayed CRISPR screening platforms and illustrate how each type of screen can be used throughout the drug development pipeline to speed the identification of new therapeutics and reduce the chance of late-stage failures in the clinic."
Recent developments in the selection methods for DNA-encoded chemical libraries
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Open to view video. During the past two decades, many strategies have been developed for the synthesis of DNA-encoded chemical libraries (DEL). The recent progresses in DEL-compatible chemistry have further expanded the chemical space accessible to DELs. However, the target scope of DEL has been largely limited to purified proteins. Here we will describe our recent efforts in developing new DEL selection methods for complex biological targets such as live cells.
Physiologically Relevant Cell Models for Target discovery and Screening
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Open to view video. Advances in tissue modeling are key to improve drug discovery and development as well as toxicity testing. Combining tissue complexity with assay throughput of the models represents a challenge for target discovery and screening. In this session new models and their application to drug testing and efficacy and toxicity screening of compounds are discussed. First, a multi-well microplate assay system is presented that enables high throughput growth of organized neuronal networks on a chip. Compartmentalized testing of axons and soma in this system generates big data for neuronal analysis and its application to safety and efficacy evaluations in the context of neurotoxicity is discussed. Second, a series of immunological assays are presented using primary immune cells, including PBMCs, T cells, macrophages, and NK cells in 2D and 3D in vitro models. Application to lead selection for small molecule and antibody therapeutics is discussed as well as identification and validation of new targets for immune-oncology and inflammatory diseases. Third, a primary screening platform is presented using a series of non-small cell lung cancer 3D cultures in 1536 well plate format. Application to screening of a large library of natural compounds for the identification of novel lead compounds is discussed. Efficacy as well as selectivity with respect to NSCLC mutation status is showcased for new leads. Altogether, this session will present state of the art cell models where tissue complexity and assay throughput are combined to allow application to target discovery and screening.
Revisiting colorectal cancer tumorigenesis with spatially-resolved gene expression profiling
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Open to view video. Early detection and treatment are paramount to the clinical outcome of patients with colorectal cancer (CRC). Deciphering the dynamic interactions that occur between epithelial cells and stromal cells during tumorigenesis requires in-depth analyses of early-stage CRC lesions in spatial context. Here we employed spatially-resolved gene expression profiling to dissect molecular processes that associate with malignant transformation in CRC. We provide the transcriptional landscapes of colorectal cancer tumorigenesis from healthy mucosa, through different degrees of dysplasia, to cancer. The complementary examination of epithelial and stromal fractions allowed us to define whether specific oncogenic processes involved cancer cells, stromal cells, or the tumor microenvironment as a whole. We identified several genes that were consistently deregulated during CRC onset that could serve as clinical biomarkers for early-stage CRC. Furthermore, we uncovered an essential role for the innate immune system during CRC tumorigenesis.
Automation Technologies
Accelerating Drug Discovery: Getting to the right molecule smarter & faster with automation
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Open to view video. Over the past few years, GSK has significantly advanced it’s biopharmaceutical drug discovery process to accelerate cycle times and increase candidate quality.  Biopharmaceutical drug discovery campaigns have routinely adopted a funnel approach where only a finite selection of leads can be characterised at each stage due to limitations of material availability and assay throughput.  We will present how we have modernised and embedded automation to increase our screening capacity and remove time consuming make-test cycles.  Investments have been made in automated sample preparation, assay miniaturization & improved data management strategies.  We will present how these have allowed us to create a data-rich environment enabling selection of high-quality leads, acceleration of cycle times to candidate and reduction of time on manual tasks freeing up FTEs to focus on science.
Accelerating Medicinal Chemistry Cycle Times Through Cloud-Accessible Smart Automated Labs
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Open to view video. To advance a lead candidate through to clinical trials in traditional small molecule pipelines, it can take on average 6+ years. Iterative cycles of design, make, test and analyze (DMTA) are at the core of early stage drug discovery. Medicinal chemistry is a critical component within small molecule drug discovery and involves the design of molecules, synthesis, testing via bioassays, and analysis of results; however, bottlenecks, such as highly manual, time-intensive procedures (i.e., synthesizing and purifying compounds), whether in-house or outsourced, as well as non-standardized analog data capture lead to slow cycle times. Strateos’ goal is to automate many of the operations to enable a chemist to work on multiple programs at the same time in parallel, greatly improving the process efficiencies and shortening cycle times. In this presentation, you will learn:  The capabilities of Strateos’s 23 drug discovery automation modules, and how they can be accessed via the cloud from anywhere in the world Synergies enabled by full integration under the Strateos cloud-based software stack Lessons learned from over a year operating in production mode
AI Enhanced Collaborative V+R Drug Discovery
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Open to view video. "Artificial Intelligence (AI) has the potential to speed up the discovery phase and lower discovery costs significantly. Recent advances in molecular science and machine learning, combined with the availability of powerful cloud computing platforms, are turning this potential into reality. We will discuss an approach that applies AI and machine learning to design, test, and optimize lead molecules rapidly in silico and to suggest what molecules to make next in an ‘active learning’ process to help guide the drug discovery process and optimize R&D output. Active learning is a specialization within Machine Learning in which computation (the ‘virtual’) and experiment (the ‘real’) are combined—allowing scientists to find optimal answers in the most efficient way possible. Molecular modeling methods, such as pharmacophore screening, docking, and physics-based computations incorporate 3D and target-based data can enhance the accuracy of predictions for drug potency, efficacy, and selectivity, while also addressing multi-target effects. The Dassault Systèmes’ 3DEXPERIENCE platform offers tight integration between the virtual and real cycles (V+R). This shortens timelines by reducing turnaround time for laboratory synthesis and testing, while also reducing the number of V+R cycles. The 3DEXPERIENCE platforms allow users to collaborate in a secure and intuitive manner, independent of time and location. The platform captures the entire drug discovery process; including compound structures, molecular models and simulation, synthesis reactions, objectives, and conclusions. Finally, we will present real-world examples of our customers and partners leveraging the benefits of our integrated AI collaborative platform."
An autonomous robot automating cell culture maintenance in a normal lab environment using open standard SiLA 2
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Open to view video. """Introduction: There has been much talk and substantial progress in automated and flexible Smart lab concepts in biopharma R&D. This is acknowledged to be important in enabling the acceleration of innovation and digitisation of R&D operations. However, many proposals stop short of full automation – limiting out-of-hours operation which is particular important in tasks such as cell culture - or are locked to a particular vendor’s offering in a dedicated system - which can limit the flexibility and access so important in R&D. Motivation: In this contribution we describe a fully integrated automated cell culture system in the open lab which is multi-vendor using open standards. This creates a “cell culture autopilot” for small-scale cell culture, with repetitive media exchange, confluency checking, and splitting steps which are typically labour intensive but not very demanding in terms of throughput. Approach: The system brings together recent developments in cell imaging, collaborative cloud robotics, and small-scale automated devices such as incubator and refrigerator. The use of a free ranging mobile robot enables the automation to operate across benches in a lab that can be shared with human staff without additional constraints. This addresses a need for distributed automation that blends into existing facilities. The SiLA 2 standard facilitates straightforward communication between all system components, despite their coming from different suppliers. Results: We describe the steps and pitfalls towards a system autonomously culturing cells in a small scale format. The system is able to schedule important but tiresome steps such as prewarming media and allowing laminar flow in the biosafety cabinet to stabilise. Future Work: Given the open nature of the system implementation of further devices is currently under evaluation. Conclusion: Lab automation is becoming a new reality in scientific research. This contribution shows how automation is compatible with flexibility and innovation thanks to open standards.""
Cellpainting as a Platform for Drug Discovery
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Chemputational Drug Discovery using Modular Universal Chemical Robots
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Open to view video. "Digital chemistry or chemputation, is the universal code-enabled control of chemical reactions using a standard language and ontology, in a modular system for organic chemical synthesis, discovery, and reaction exploration. In our lab we have designed and built the world’s first ChemPU, a system that unifies all chemistry automation strategies, from solid-phase peptide synthesis, to HTE flow chemistry platforms. This system uses a chemical programming language that runs a chemical code (χDL) to ensure reproducibility and interoperability. Herein, we present a parallel ChemPU system that explores chemical space for new drug-like molecules, new reactions, and reactivity. The discovery of novel organic transformations and reactivity is a difficult problem mostly relying on serendipity with no systematic approach to search an unimagined, or unknown, chemical space. Our robotic chemical discovery system can navigate a chemical space based on a learned general association between molecular structures and reactivity, while incorporating a machine learning model that can process data from online analytics and assess reactivity without knowing the identity of the reagents. Working in conjunction with this learned knowledge, our robotic platform can autonomously explore a large number of potential reactions and assess the reactivity of mixtures, including unknown chemical spaces, regardless the identity of the starting materials. Through the system we identified a range of chemical reactions and products, some of which were well-known, some were new but predictable from known pathways and some were unpredictable reactions that yielded new molecules.   References: A Reactivity First Approach to Autonomous Discovery of New Chemistry Caramelli, D., Granda, J.M., Cambié, D., Mehr, S.H.M., Henson A., Cronin L., (2021)   A universal system for digitization and automatic execution of the chemical synthesis literature. Hessam, S., Craven, M., Leonov, A. I., Keenan, G. & Cronin, L. Science (80-. ). 370, 101–108 (2020)."
Combining bioactivity data and biosignatures using AI/ML approaches to increase success rate in drug discovery
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Open to view video. Having access to a large chemical library, annotated with high quality bioactivity data provides a rich source of information. The introduction of artificial intelligence / machine learning (AI/ML) affords the opportunity to combine historical data with information rich technologies such as high content imaging to accurately predict molecular activity on cell biology. Wanting to ensure that the content is as informative as possible, we have explored and implemented the Cell Painting imaging assay which allows the visualization of multiple cellular compartments (actin filaments, endoplasmic reticulum, Golgi, membrane, mitochondria, nucleus, nucleolus) at scale. We use Cell Painting to extract features, using conventional as well as AI-driven means, from different compound treatments to generate biosignatures in multiple cellular systems, including U2OS as well as primary cell types. Using AI/ML, the resulting biosignatures are combined with bioactivity data and translated to have a direct impact on our drug discovery pipeline: inferring mechanistic hypotheses about off-target effects, bioactivity prediction. While setting up the laboratory workflows, we have refined several liquid handling procedures to enable automation of the Cell Painting imaging assay. A dedicated automation platform with throughput and versatility in mind was established.
DashChem - Smart Laboratory Dashboard
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Open to view video. There has been little advancement in the field of chemistry automation over the past few decades. Therefore, the way chemistry is being performed on the benchtop has not changed significantly over the years. The manual work involved in laboratories to run even simple pipetting tasks poses an added burden to the chemists, since it takes away from crucial research time. In order to tackle these challenges and more, A Specialized Platform for Innovative Research Exploration (ASPIRE) initiative was launched by NCATS. One of the main objectives of ASPIRE is to enable standardization and reproducible chemistry through automation, which is an essential part of realizing this goal. The core idea is to create state of the art laboratories and retrofit existing ones with automated solutions. A significant part of this initiative is the NCATS DashChem, an Internet of Things (IoT) based dashboard centered around inductive laboratory automation. This dashboard integrates automation, chemistry, and informatics and brings together data from different instrumentation platforms, enabling the scientists to run seamless chemistry workflows. We are creating an ecosystem of old and new laboratory equipment such that a user can interact with it through a universal dashboard application, in person or virtually. The uniqueness of this dashboard comes from its ability to handle a multitude of tasks including, but not limited to, controlling laboratory devices, executing chemistry reaction flows, and providing user access to reaction data tracking. The array of devices used in our laboratories are from a variety of independent vendors, some of which are supported purely in-house, and have their own user interface, making it more difficult to track data for an entire experiment involving multiple instruments. It also makes the data tracking process dependent upon a human being in the loop, which can potentially increase chances of error. We will demonstrate how our dashboard solves these problems of data tracking, performing standardized and reproducible chemistry as well as allowing chemists to run reactions from a single dashboard remotely or at the bench.
Degradable hollow-shelled microparticles for rapid picking of hundreds of thousands of yeast colonies using flow cytometry
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Open to view video. Current colony picking technologies post-transfection of cells rely on the imaging of growing colonies on an agar plate and their subsequent removal and inoculation. This standard workflow is limited by the speed of researcher or robotics and by the need to grow cells on a two dimensional agar surface, which may not be representative of the ultimate desired physiological growth environment. On top of this, desired colonies are determined based on the size of the colony on the plate, which prioritizes growth, but may in some instances neglect the expression of a desired metabolic phenotype. By increasing the throughput of colony picking and enabling the selection of cells of varying growth rates, researchers will be able to obtain a population with much greater diversity and improve the outcomes of their studies. To improve the throughput of colony picking workflows, as well as broaden the phenotypes that can be selected for, we have developed PicoShells. PicoShells are polymeric, porous, hollow microparticles that are 40 – 100 µm in diameter, compartmentalize clonal subpopulations of yeast, and enables continuous media and waste exchange. First we encapsulate hundreds of thousands of single cells per hour into polymer-containing aqueous droplets using a microfluidic system. The polymer crosslinks into a hydrogel shell around an aqueous cavity containing the yeast cell, keeping it and its progeny confined. PicoShells are then cultured under normal conditions within an incubator or bioreactor; the porosity and biocompatibility of the shell creates an environment more conducive to the growth of Saccharomyces cerevisiae than comparable aqueous-in-oil microfluidic droplets. The porosity also makes it much easier for stains to enter the compartment, stain cells, and be washed away to enhance the signal-to-noise ratio. Cells grow into monoclonal colonies within the PicoShells, and the colonies expressing high quantities of a protein of interest or increased biomass accumulation under certain environmental pressures can be selected through standard multi-color flow cytometry workflows. Cell viability is maintained through the process, and upon chemical degradation of the shells, downstream population analysis or reculturing can be performed. Since PicoShells can be run through flow cytometers, hundreds of colonies grown in PicoShells can be picked per second based on their light scatter (biomass), their fluorescence (protein expression) or a combination of both. The PicoShell platform represents a culturing system that lends itself to high-throughput, multiplexed colony picking in order to enrich transformed populations, select colonies expressing a particular phenotype, or evolve a more efficient living foundry cell strain. With PicoShells, we have demonstrated the ability to pick colonies that overexpress an intracellular protein, as well as colonies with particular growth rates from an initial population.
Development of a 3D-optimized microplate enables confocal high content imaging with cell level resolution and the automation of immuno-staining methods for spheroid models
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Open to view video. "Homeostasis at the tissue level is maintained via finely orchestrated cell-cell and paracrine signaling which frequently involves several different cell types. Further, the cyto-architecture of tissues, including the organization and the ratio of tissue-specific cell types, plays an important role in maintaining normal tissue function and viability. Studying individual cell responses in the context of intact tissue is therefore critical to understanding the development, prevention, and reversal of human disease. To that end, we developed multi-cellular 3D liver, islet, and tumor microtissue models (a.k.a. spheroids), and an accompanying Akura™ 384 microplate technology that supports both spheroid production and high-resolution 3D imaging. The combined platform enables the cell-level analysis of tissues with added spatial resolution and architectural context. The platform is also scalable and automation-compatible making it ideal for studying tissue-level responses at early stages in the drug discovery pipeline. Using pancreatic islet microtissues we examined the compatibility of the Akura™ 384 spheroid plate with confocal high-resolution imaging. Human islet microtissues, reconstituted from dissociated native islets, were labeled with two nuclear markers, DAPI (marker for all cells) and anti-NKX6.1 (beta cell-specific marker). Using a 3D nuclear colocalization assay requiring single cell resolution, we examined the relative contributions of the Akura™ 384 plates and a u-bottom spheroid plate to light attenuation, optical aberrations, and ability to perform accurate segmentation of the nuclei.  Our results demonstrate that a continuous, flat, ultra-thin, transparent bottom significantly minimizes the refractive index mismatch and the chromatic registration issues observed with conventional u-bottom plates and enhances the overall speed and accuracy of the image acquisition. Next the automation-compatibility of the Akura™ 384 plate was evaluated via the implementation of a fully automated fixation, permeabilization, immuno-staining, and tissue clearing method for tumor spheroids on an Opentrons OT-2 pipeting station. The spheroid model, comprised of GFP-expressing DLD-1 colorectal adenocarcinoma cells, was subjected to the automated overnight Fix-Perm-Stain-Clear method. The following day the plates were imaged on a Yokogawa CQ-1 high content analysis system and evaluated for preservation of spheroids, tissue clarity, and signal uniformity in 3 channels. Our results suggest that the unique well geometry, consisting of spheroid compartment and a contoured pipeting ledge, protects the microtissue from accidental aspiration and damage and enables fully automated processing and 3D imaging, consistent with high throughput workflows. As the dependence on 3D models and high content imaging continues to expand, maximizing 3D image quality is imperative to the development of accurate and comprehensive spheroid measurements. Likewise, the implementation of reliable automated workflows is essential to the adoption of 3D models for screening applications. Innovations, such as the development of standardized 3D models and 3D-optimized microplates, may soon overcome the remaining obstacles limiting the broader utilization 3D cell models in early drug discovery."
Development of the Indigo Reactor for Advanced Automated Chemical Synthesis
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Open to view video. Indigo Reactor is an advanced chemical synthesis platform capable of running in an automated environment with 8 independently controlled reactors, allowing conventional thermal control up to 150 °C with or without an upper cooled reflux zone or under complete cryo-controlled temperatures down to -40 °C, plus controllable magnetic stirring, vessel inerting via vacuum application and dry nitrogen backfill, and/or under applied nitrogen pressure application as high as 20 bar.  Equipped with interchangeable adapters, it can either run 10 mL or 20 mL reaction vessels.  These reaction vessels can be interchangeably used with Biotage (brand) microwave reactor instruments as well.  This presentation will review the various functional capabilities of the Indigo reactor. It will cover the system testing and development that has been completed thus far. Through the testing, we get a better understanding of the thermal profile, and the ability to adjust and control the pressure inside the reaction. Equipped with an automated cleaning cycle, the reactor will wash the chemically resistant reactor seal with acetone and water after each reaction is finished to eliminate any possible cross-contamination in subsequent use. It is also possible to monitor the reaction progress under certain conditions by controlling the lidding mechanism while the reaction is underway. The system first will release the pressure and reduce the temperature to make it safe for the operator to take the sample for LC/MS or UPLC. After sampling, the reaction can be returned to a sealed state to complete the incubation cycle automatically. A key part of this project has been to conduct a series of tests through execution of a diverse set of chemical reactions to serve as a standardized set of benchmarks to characterize the functionality of the system but will also serve as a quantitative comparator as such system's functionality and capabilities evolve.  Also demonstrated will be how to transfer different complex chemical reaction conditions into a recipe that will play an important role in automated chemistry synthesis, and how to use it for running parallel reactions, tracking the reaction progress, and reproducing chemistry reactions repeatedly. Since this development effort of the Indigo Reactor was initiated, both the hardware and software have seen significant upgrades guided by this development effort. The UI is now easier to use for a first-time user. With the hardware upgrade, the automation system has become more reliable and key components more durable. The web server also gives the chemist the option to log in to the system remotely. The Indigo Reactor can provide a practical option for chemistry labs looking to further automate their chemical synthesis with a more compact design, flexibility for different scale reactions, and useful integration options.
High-throughput, Parallel Liquid-Liquid Extraction for on-Chip Purification in Nanoliter Scale
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Open to view video. "Abstract: Miniaturization and Parallelization of the chemical synthesis, characterization and screening of new molecules is an important task to accelerate the development of new biologically active molecules. The most challenging task is the purification of small amounts in a facile and time-saving way prior to the final screening of the pure compounds. This project aims to establish the liquid-liquid extraction (LLE) into the workflow of chemical synthesis in a parallel, high-throughput manner. In this work, the Droplet Microarray (DMA) is used to manipulate droplets for the miniaturized, high-throughput liquid-liquid extraction between an organic and an aqueous phase to separate a mixture of compounds according to their solubility. This powerful tool enables the parallel workup of a large number of samples with microliter volumes of solvents within minutes, with a broad range of further applications, as the platform is suitable for cell culture and microscopic analysis as well as for structural analysis like mass spectrometry or infrared microscopy. The DMA was earlier developed in our group and consists of a microscopic glass surface chemically modified with a wettability pattern. This substrate enables highly precise location of stable droplets on omniphilic spots surrounded by omniphobic areas in an array of wall-less nanoliter spots. Those spots can be addressed by a liquid dispenser for automated formation and manipulation of droplets of various solvents in a nanoliter scale. The merging of two liquids is achieved by shifted dispensing of the organic solvent, so that it spreads between the aqueous droplet and the neighbored spot. By evaporation of the aqueous phase, the two phases are separated automatically within minutes without any additional handling step. The high ratio of the interphase compared to the volume of few hundred nanoliters allows a high extraction efficiency. This efficiency is comparable to a separation funnel, that is used in common laboratories for iterative, manual workup of reaction mixtures. The whole procedure can be conducted excluding any manual shaking and thus enables an automated workflow. The basic investigations have been made by extracting a dye from water to 1-octanol on squared droplets with a side length of 900 µm. Additionally, the separation of a mixture of dyes proved that the extraction is working as selectively as the separation funnel in the bulk synthesis. By including this new technology in a semi-automated, high-throughput workflow of chemical synthesis, purification, analysis and biological screening on the same chip, this new way of liquid-liquid extraction accelerates the production and evaluation of new promising drug candidates. At the same time, this method is reducing the use of chemicals, consumables, and solvents to lead the drug development into a new level of sustainability and efficiency."
Innovating Ultra-High-Throughput Workflows for COVID-19 Testing
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Open to view video. "Shortly after the pandemic began, conventional clinical laboratories were overwhelmed by testing volumes, limiting the availability of COVID-19 tests. Corteva Agriscience quickly engaged by implementing and operating a CLIA COVID-19 diagnostics lab to support the testing needs of local hospitals, universities, and sports teams. With molecular testing supply chains stressed and the low throughput of commercially available tests, it was clear that custom solutions were needed to meet demand. Utilizing its world-class expertise in high-throughput-molecular testing platforms, we partnered with the Bill and Melinda Gates Foundation (BMGF) to develop an end-to-end ultra-high-throughput testing platform. The resulting workflow enables testing of up to 100,000 specimens per day at a single site with low cost, high sensitivity, minimal staffing, reduced reagent needs, and less lab waste. Achieving a platform that met all the desired specifications was no small task, requiring the development of numerous custom chemistries, information management, and engineering solutions. The key innovation came from Corteva and a group of collaborators in the form of a novel collection device that enables rapid accessioning, extraction-free processing, and an automation-ready workflow including newly engineered de-plugging and re-plugging and decapping automation.
JUMP-Cell Painting - Powering drug discovery and development with images
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Open to view video. "Cell microscopy images contain a vast amount of information about the status of the cell: whether it is diseased, how it responds to drug treatment, or whether a certain pathway has been disrupted, for example. These profiles can be analyzed to identify subtle cellular patterns, potentially biologically meaningful but undetectable to the human eye. The JUMP-Cell Painting Consortium, a group of pharmaceutical companies and non-profits, aims to create a critical mass of such cellular imaging data to empower discoveries about cell biology that can inform drug discovery and development. The goal is to create the world’s largest public Cell Painting image set of chemical and genetic perturbations. The community will use it to identify the effect of each gene or compound on the cell’s shape or activity — creating a morphological atlas that can be referenced as a baseline in further studies. With a large reference of image-based cellular profiles, scientists could computationally compare their images to determine a drug’s likely mechanism of action or a gene variant’s impact, accelerating basic biology research and drug discovery alike."
Lead discovery under one (new) roof - a roadmap to a holistic LD assay value chain
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Open to view video. "The identification of high quality starting points for small molecule projects is the center of our Lead Discovery (LD) department. Knowing that we will move our teams into new buildings in 2024 has given us the unique opportunity to rethink and challenge our current ways of working towards new paradigms supported by holistic hardware and software infrastructure.  Based on an assessment of the status quo and the option space, we have designed our LD Assay and Screening Roadmap (LASR), covering our entire assay value chain from assay development to screening and routine assay usage during medicinal chemistry optimization. We aim at a future state that enables seamless assay development and miniaturization and tailored screening approaches, which requires increasing flexibility in screening as well as the removal of bottlenecks in assay development, compound logistics and screening plate production.  With LASR we achieve this by moving away from complex and static automation platforms and implementing a modular environment consisting of smaller, more approachable systems that can be adapted to the respective demands. Facilitated access to automation systems already during assay development will minimize the need of duplication or time intensive transfer steps. Modularity will also support the balanced parallel execution of primary screening campaigns and profiling assays, reduces equipment redundancy, and ultimately allows fast portfolio delivery. Our plan encompasses a master agreement with one key solution provider who will work with us on an iterative implementation plan, and who will be in charge of defining precise workflows and corresponding software components to integrate and run the new setup.  We will present our approach to establishing LASR, connecting our design principles with our option space and the overall architecture principles, and illustrate the decision making process that we followed to reach our solution concept as well as implementation plan."
Microphysiological lung tumor models with vascular barriers for pre-clinical research to enhance immune infiltration
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Open to view video. Lung cancers are a leading cause of death, with only a fraction of patients responding to treatment and a low survival rate.  It is now well appreciated that the aberrant physical, chemical, and biological properties of the tumor microenvironment, particularly the immune landscape, are major contributors to heterogeneity in patient response.  Conventional in vitro models have been successfully employed to understand migration of immune cells.  However, many of these platforms lack vascular and stromal barriers, and are therefore unable to cohesively recapitulate features of the tumor microenvironment that are known to exacerbate immune evasion of solid tumors.  While animal tumor models offer an opportunity to study immune cell trafficking and infiltration in a complex tumor microenvironment, they require high costs and logistical challenges of animal handling, while suffering from weak translatability to humans and ethical concerns.  Broadly, high rates of attrition of clinical compounds during drug development have motivated a demand for disease-relevant, human cellular models that can be used in early discovery research.  In response, we have developed microphysiological lung tumor models with vascular barriers (e.g. tubular or network structures) as preclinical tools for screening potential modulators of immune cell infiltration, specifically T-cells.  I will provide examples of these models, discuss how we characterized and validated them, and contextualize the insight they offer us as part of a spectrum of in vitro models that vary in throughput and complexity.  I will also highlight how complexity in these models can be leveraged to simultaneously probe efficacy and safety of potential therapeutics, enriching the information that can be obtained in early discovery efforts. 
Restoring a Classic, the BioRAPTR 2.0
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Open to view video. A key component of High-Throughput Screening (HTS) at NCATS, and in general, is accurate, reliable, and fast low-volume liquid dispensing into microtiter plates.  Options for flexible and high-quality dispensers that are both user and automation friendly have historically been limited, and we have relied heavily on the BioRAPTR dispensers that were initially supported through Aurora Discovery followed by Beckman Coulter, until their eventual removal from the market.  Given our heavy investment in these dispensers and their ubiquitous adoption across multiple laboratories, the NCATS automation team has maintained over 20 BioRAPTR dispensers in-house down to the component level for the majority of the last decade.  These dispensers are integrated onto multiple robotic platforms and used for benchtop assay optimization and validation by our biologists daily.  The ability to calibrate the 4-valve/tip dispense heads quickly and create custom multi-tip protocols on a well-level as well as dispense a 1536-well microtiter plate in less than a few minutes is essential to our HTS operations.  We have also integrated custom features such as droplet detection, designed and built in-house to add further dependability. Due to limited options for dispenser replacements that are equivalent to the BioRAPTR, NCATS invested time into upgrading the existing dispensers from Windows XP to Windows 10 to improve security as well as improve functionality by moving away from an unsupported operating system.  We also formed a collaboration with Let’s Go Robotics (LGR) to update and refurbish the existing BioRAPTR models, ensuring that we maintain the features that have made them our primary dispensers for over a decade, while also adding new capabilities to enhance their already outstanding performance.  This work will help to ensure that the daily bench and automated system operations using these dispensers will continue uninterrupted while also making improvements for future integrations.
The CellRaft AIR® System: A novel system enabling organoid imaging, identification, and isolation
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Open to view video. Two-dimensional (2D) cell-based assays have been crucial tools in research and drug discovery for decades; however, monolayer cell cultures lack complexity and physiological relevance and poorly mimic the in vivo microenvironment. The limitations of 2D cultures have powered the need for three-dimensional (3D) cell culture technologies that mimic the cellular landscape of tissues. Organoids are self-organizing 3D cell culture models that are derived from stem cells isolated from a variety of tissues and species. Their ability to closely replicate the pathophysiology of their original organs, in contrast to traditional 2D monolayer cultures, provides opportunity for use in medical research, pharmaceutical development, and toxicological studies. Organoids are currently being used to examine tissue development, in disease modeling, in testing for drug sensitivity and toxicity, and in regenerative medicine. Despite the utility of organoid models, traditional organoid culture methods are inadequate because they are low-throughput, insufficient for single organoid imaging and phenotypic assessment, and present challenges in evaluating organoid heterogeneity. To overcome the bottlenecks and data gaps in standard organoid culture methods, Cell Microsystems has adapted our CytoSort Array consumable, CellRaft AIR instrument, software, and workflows to provide automated imaging, identification, and isolation of individual organoids. The CellRaft AIR® System relies on the 3D CytoSort® Array, a cell culture consumable made of elastomeric microwells containing releasable 500x500µm polystyrene CellRafts, for establishing compartmentalized organoid culture. Individual organoids on the 3D CytoSort Array can be reliably tracked, imaged, and phenotypically analyzed by the AIR System in brightfield and fluorescence as they grow over time. Single organoids of interest, with sizes ranging from small ( < 250µm) to large (500µm – 1mm) in diameter, can be subsequently released and isolated from the array into standard 96-well tissue culture plates for continued organoid growth and clonal propagation, or into PCR plates or strip tubes for ‘omics or other destructive endpoints. Using mouse hepatic and pancreatic organoids on the CellRaft AIR System, we demonstrated the use of our technology for imaging organoids, establishing clonal organoids, subcloning organoids, and single-organoid RNA extraction for use in downstream gene expression or transcriptomic analysis. The results validate the ability of the CellRaft AIR system to yield more efficient, user-friendly, and automated workflows that are broadly applicable to organoid research by overcoming several common bottlenecks: 1) single organoid time-course imaging and phenotypic assessment, 2) establishment of single cell-derived organoids, and 3) isolation and retrieval of intact single organoids for downstream applications.
The challenges of automating thermal shift assays
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Open to view video. "High throughput screening (HTS) is frequently used in drug discovery campaigns to identify high quality hits from large screening collections. Historically, primary screens have focussed on the identification of modulators of catalytically active sites using simple biochemical assays, while target engagement assays have been placed further down the screening cascade, often due to throughput considerations. Thermal shift assays (TSA) provide measurement of compound-target engagement, measuring protein unfolding by monitoring change in fluorescence as a function of temperature. Differential scanning fluorimetry (DSF) measures the thermal stability of the target protein, binding of a drug causes stabilisation and an increase in protein melting temperature. This simple biophysical technique can be employed for HTS purposes as a primary screening technology. Within the Global High Throughput Screening Centre at AstraZeneca we have successfully deployed an automated DSF screening capability, here we describe the various challenges that we encountered during scale-up and automation to enable screening of up to 400K compound libraries. The cellular thermal shift assay (CETSA®) has emerged as a technology that allows assessment of interactions between a drug and protein target in a cellular environment, by measuring changes in the thermal stability of the target protein upon ligand binding, and this technology is amenable to testing large numbers of compounds in an HTS setting. We have explored the potential and feasibility of CETSA®-HT for large scale HTS campaigns (up to 0.5M compounds). In 2020 we reported on the development of an HT-CETSA® assay and the application of this technology within the HTS setting. This screening campaign highlighted several practical issues & challenges when automating such assays. Here we report on various improvements & modifications that we have put in place to enable delivery of robust screening assays to deliver high quality hits. These include evaluating different CETSA approaches, and their amenability to automated screening. Combining CETSA with the homogeneous bead-based AlphaLISA® technology requires the development & optimization of target specific antibody pairs, which can be time consuming to develop, and multiple addition steps can make it more complex to automate. Approaches that combine protein-based reporters such as Nano-Glo® HiBiT with CETSA, using luminescence readouts, are often simpler assays with potentially fewer steps making them more amenable to automation. We have also addressed labware issues to improve automation reliability, and investigated alternative thermal cyclers for ease of automation. Utilising both DSF and HT-CETSA® to identify target engagement in early during primary screening could shift the paradigm of hit finding and the ability to automate these different approaches enlarges the tool box of hit-finding approaches that can be used at scale."
ChemOS™ - Automatic optimization of chemical reactions
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Open to view video. Can we accelerate the process of molecular discovery by combining automation with machine learning tools? Rapid discovery of novel molecules with tailored properties is crucial for the chemical, petrochemical, and pharmaceutical industries. Autonomous optimization of chemical reactions is one of fundamental tasks in self-driving labs. Here, I will present on how Kebotix ChemOS™ orchestrates and optimizes chemical reactions in real world scenarios. In addition to state-of-the-art optimization algorithms implemented, ChemOS™ integrates lab instruments, coordinates the reaction workflows, and collects data in an AI-processable format.
Phage and Robotics-Assisted Directed Evolution
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Open to view video. Evolution occurs when selective pressures from the environment shape inherited variation over time. Within the laboratory, evolution is commonly used to engineer proteins and RNA, but experimental constraints have limited our ability to reproducibly and reliably explore key factors such as population diversity, the timing of environmental changes, and chance. We developed an automated system for comprehensive exploration of biomolecular evolution in high-throughput, which we used to evolve three distinct types of biomolecules. In this talk, I will first describe the development of our open-source python:robot integration platform (Pyhamilton) which enables substantially more advanced automation experiments than could ever be done by hand-- or with present software. Next, I will detail the development of PRANCE (Phage and Robotics-Assisted Near-Continuous Evolution), an automated platform for the comprehensive exploration of biomolecular evolution using phage-based mutagenesis and selection in high-throughput. Using PRANCE, we readily evolved three distinct types of biomolecules: quadruplet-decoding tRNA, polymerases, and amino-acyl tRNA synthetases across many conditions, replicates, and environments. Additionally, our automated continuous evolution platform allows us to adjust the stringency of selection in response to real-time evolving molecular activity measurements, thereby enabling more reproducible and reliable evolutions. Collectively, with PRANCE, we are able to  explore new evolution trajectories, quantify evolution stochasticity, and implement previously intractable evolutions involving small molecules. Additionally, by tracking biomolecular trajectories in replicate, we found that evolution is reproducibly altered by both random chance and the historical pattern of environmental changes. Thus, phage-based automated evolution both improves the reliability of protein engineering and enables the systematic analysis of the historical, environmental, and random factors governing biomolecular evolution. 
The Droplet Microarray (DMA) as a versatile platform of the future for high throughput cell experiments in nanolitre droplets
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Open to view video. "Droplet Microarray is a technology based on precise fabrication of arrays of hydrophilic spots on hydrophobic background. Such surfaces allow for formation of arrays of separated and stable droplets of nanoliter volumes either by using low volume dispensers or by discontinuous dewetting, the process of spontaneous formation of droplet arrays upon application of aqueous solution onto the surface. Each of such nano droplets serves as a well for cell culturing and screening. We have successfully adopted the DMA platfrom for culturing and screening of multiple cells types including adherent and suspension cell line, stem cells and primary patient derived cells. In addition to standard 2D culture models, the DMA platform is compatible with 3D cell culture. By simply inverting the DMA slide upside down, imitating the method of hanging droplet, we can observe formation of single-spheroid arrays. Taking advantage of two features of DMA, the fact that it is an open system and that it does not have physical barriers between the spots, we have demonstrated the possibility to combine droplets containing different types of spheroids by adding the liquid resulting in merging of neighbouring droplets in controlled way. This method opens new possibilities for co-culture models, complex screening models, tissue engineering and others. One of the main advantages of the DMA platform is miniaturization of culturing volumes, resulting in up to 2 orders of magnitude reduction of amount of cell material needed for experiment. This is especially beneficial for highly miniaturized Drug Sensitivity and Resistance Test on patient-derived cancer cells. In collaboration with University Hospital in Heidelberg, DKFZ and NCT, we developing models for screening of CLL and MM cells and had performed a screening of about 3000 FDA approved compounds on patient-derived glioma tumorspheres. In addition to phenotypic read-out based on microscopy and colorimetric based methods, we are working on developing of a toolbox of methods, which will allow us to get detailed information about the molecular changes in cells upon the treatment. We are developing protocols allowing performing MALDI, proteomic and transcriptomic analysis of live cells in individual droplets directly on the DMA chip. Considering all the advantages and the multifunctionality of the DMA platform, we are convinced that this kind of technology will represent new generation platforms of the future for miniaturization and parallezation of biological, as well as chemical experiments.
Cellular Technologies
A new stem cell-based toolkit to study biosafety level 4 (BSL4) viruses
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Open to view video. Biosafety level 4 (BSL4) viruses—including the infamous Ebola virus and Nipah virus (44% and 59% fatality rates, respectively)—are among the deadliest viruses on Earth, and have few to no approved treatments. Such BSL4 viruses are extraordinarily understudied, since they can only be handled by “space suit”-protected personnel in specialized facilities, few of which exist worldwide. Due to operational difficulties, most studies explore the effects of BSL4 viruses on cancer cell lines, which loosely resemble human cell-types in vivo, have defective interferon signaling, and are genetically abnormal. To create more accurate cellular models for viral infection, we pioneered methods to generate healthy artery and vein cells from human pluripotent stem cells (hPSCs) in vitro. This revealed new biology: Nipah virus preferentially attacked artery (as opposed to vein) cells. By live-imaging, infected artery cells fused to create massive multinucleated cells with up to 23 nuclei, yet infected arteries failed to produce interferon despite massive viral infiltration of their transcriptome. More broadly, we are deploying cutting-edge approaches in stem cell biology and cell engineering to the challenging BSL4 operational environment. hPSC-derived cell-types offer decisive advantages over cancer cell lines for studies of BSL4 viruses. This is enabling high-throughput chemical and genetic screens to discover new antiviral therapies against BSL4 viruses, using physiologically-relevant cell-types.
A Precisely 3D Bioprinted and Functional Human Liver Tissue Model
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Open to view video. The pharmaceutical industry needs reliable 3D microtissue culture systems that are relatively high throughput, stable for ≥ 14 to 28 days, reproducible & transferable, able to be assessed by meaningful endpoints, capable of human dose/exposure prediction, and able to differentiate good compounds from bad for efficacy and safety. To address this critical need, in this talk we will present results from the development and testing of an in vitro liver tissue model for use in toxicological investigation. We will show that by combining 3D bioprinting with new 3D culture materials, we created reproducible cellular structures that remain viable over the course of at least 21 days and exhibit function comparable to human liver tissue. Future stages of this project include toxicological tests and improved systems for tissue manufacturing, maturation and monitoring. The successful completion of this project, focused on 3D liver tissue models, will establish guidelines and best practices for predictable and repeatable tissue assembly and maturation culture more broadly in tissue-engineered manufactured products.
Advanced Intestinal 3D Morphogenesis by Physiodynamic Reprogramming at Single Cell Resolution in a Human Gut-on-a-Chip
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Open to view video. The establishment of a reliable and translational in vitro human intestine model is still a pressing need in biomedical research, especially given the complicated microenvironment involving host-microbiome crosstalk. One of the challenging components to model the intestine is its unique crypt-villus three-dimensional (3D) structure necessary for demonstrating intestinal homeostasis, microbial niche formation, and spatially localized cellular functions. However, conventional static cell cultures often do not offer differentiated cellular phenotypes and accessible 3D mucosal interface lacking mechanobiological milieu. In contrast, the microphysiological human gut-on-a-chip has innovated the concept of in vitro 3D recreation by which cells cultured in a gut-on-a-chip demonstrates a robust and spontaneous morphogenesis process. The in vitro morphogenesis not only enabled us to closely emulate in vivo microarchitecture but also reprogrammed cells to exhibit lineage-dependent cytodifferentiation, tissue-specific histogenesis, and reprogrammed intestinal functions. Here, we discuss a mechanistic background of 3D intestinal morphogenesis, single-cell transcriptomics, spatial visualization of cell type-specific differentiation, and applicability of intestinal organoids in the human gut-on-a-chip. We also demonstrate the implementability of the explained mechanism of in vitro 3D morphogenesis for developing a scalable multiplex high-throughput screening system. The gut-on-a-chip that contains two microchannels compartmentalized by a flexible porous membrane provides a defined space and actuatable dynamic milieu to emulate the physiological intestinal microenvironment. By independently manipulating each biomechanical (shear, flow, deformation) or biochemical factor (nutrient, oxygen, antibiotics) in a gut-on-a-chip, we found that this microphysiological control contributes to perturb biophysical cues and morphogen gradients on a polarized intestinal epithelium. The critical driver for the in vitro morphogenesis was the removal of Wnt antagonists such as Dickopf-1 in the basolateral compartment. For scalable multiplex dissemination, we expanded our new finding in a Transwell platform by applying basolateral fluid in a Transwell-insertable hybrid microfluidic device or a multi-well insert platform to robustly grow 3D intestinal epithelium in vitro.Based on the uncovered mechanism, we elucidated cellular fidelity at transcriptomic and phenotypic levels. We found that the enterocyte-specific Caco-2 cells represent reprogramming in lineage-dependent differentiation and unprecedented cellular functions such as cytochrome P450-based drug metabolism in a gut-on-a-chip. The 3D microarchitecture revealed cell migration of proliferative cells in a crypt-villus axis, reminiscent of the cellular behavioral dynamics in vivo. Most importantly, transcriptomic evolutionary process was discovered by a single-cell RNA sequencing followed by visual mapping of representative genes in subclusters with increased cellular heterogeneity. Single-cell transcriptomics revealed that not only essential intestinal functions but also cancerous characteristics of Caco-2 cells were significantly reprogrammed.Our microengineered gut-on-a-chip offers remarkable technological advances in emerging fields of cellular technology and organ-on-a-chip. We envision that our technological innovation and scientific contribution can disseminate huge translational impacts on biomedical, clinical, and pharmaceutical sciences for advancing drug development pipeline and Precision Medicine.
Coupling organoids and Organ-on-Chip technologies to study host-microbiome interactions in health and disease.
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Open to view video. "The large intestine hosts 95% of the human bacterial load also known as the gut microbiome. To maintain homeostasis, the intestinal mucosa produces a thick bi-layered mucus gel and a complex network of cytokines to segregate and in parallel facilitate the communication between the host and the trillions of inhabiting bacteria. The compromised integrity of the intestinal epithelial barrier when coupled with the unbalanced diversity and abundance of the microbial species, or dysbiosis, triggers detrimental and complex diseases such as Inflammatory Bowel Disease and Colorectal Cancer. However, because of its location in the body, this is a difficult system to study in vivo, limiting scientific advances to animal models or cell lines. Here, we combined advancements in organoids and Organs-On-Chip technologies and developed the Colon Intestine-Chip to address the need for human-relevant models to study intestinal epithelial barrier function (Apostolou et al., CMGH, 2021, and the host-microbiome interactions in health and disease. Organoids isolated from colonic biopsies have been co-cultured with tissue-specific microvascular endothelial cells and successfully expanded in a columnar epithelial monolayer, that preserves the distinct cellular and molecular signature of the human tissue. The Colon Intestine-Chip was applied to in vitro model the “leaky gut syndrome”, and captured alterations of the paracellular permeability, cytokines secretion and transcriptomic profiling of the cells within the chip driven by prototype (IFNγ) or pleiotropic (IL-22) cytokines. Lastly, employing elements of the tissue microenvironment, such as the periodical exposure of epithelial cells to Air-Liquid Interface (pALI), we established a mucus layer with thickness relevant to the human tissue, providing the necessary microhabitat and substrate to delineate the effect of commensal bacterial strains on intestinal epithelium. In the presentation, we report the development of a microphysiological human platform that can be leveraged to study how the complex host-microbiome interactions shape intestinal physiology and assess the efficacy and safety of novel drugs for gastrointestinal diseases at a patient-specific level."
FulcrumSeek™: A state of the art, universal platform for rare disease drug discovery using high-throughput gene expression profiling and high content imaging
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Open to view video. "At Fulcrum Therapeutics, we aim to develop treatments for rare genetic diseases by modulating gene expression at the source. In our drug discovery platform, we probe our sophisticated cell-based disease models with small molecule and genetic perturbagens at scale to swiftly identify and deliver candidate drug targets for clinical development. Here we present FulcrumSeek, an automated transcriptomic and phenotypic profiling platform for high-throughput drug discovery and functional genomics screens. The FulcrumSeek platform has been custom-built to maximize flexibility and data quality. The transcriptomic profiling branch of FulcrumSeek features a mini-bulk RNA-sequencing workflow optimized for universal compatibility with a wide range of disease-relevant cell models. A direct lysis and 3’ barcoding scheme allow for up-front sample pooling, minimizing reagent usage and labware handling in downstream steps. The barcoded reverse transcription product can be used for full transcriptome and/or custom targeted sequencing library generation. The 3’-based method, along with UMI integration for identifying and eliminating PCR duplicates, creates a robust and cost-effective platform to assess the expression of thousands of genes in each well. The high content imaging branch of FulcrumSeek utilizes a fully automated cell staining workflow to profile markers of differentiation, cell structure, and organelles. A machine learning approach to image analysis allows us to identify intracellular features and cluster phenotypic responses to chemical and genetic perturbagens. Considered together with companion transcriptomic data, the FulcrumSeek platform provides a holistic view of cellular response to perturbation for a broad range of cell models. The true power of FulcrumSeek lies in the ever-expanding high dimensional data matrix, thus far derived from over 10 highly specialized disease models, thousands of small molecule and CRISPR perturbagens, multiple treatment timecourses, and tens of thousands of genetic and phenotypic features captured from each condition. We have verified our platform by confirming identification of known targets, and now use artificial intelligence tools to classify cellular response to perturbagens and identify novel targets for rare disease. As our data matrix grows, so does our ability to draw associations between perturbation and outcome, accelerating our power to predict paths forward to treat rare diseases."
High-throughput Assessment of Cardiac Safety via Contractility Measurements of 3D Engineered Heart Tissues Using a Novel Instrumentation Platform
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Open to view video. "Stem cell models hold great promise for improving the predictive power of preclinical in vitro assays for new therapies, drug discovery, basic scientific research, and disease modeling. Complex 3D platforms, such as Engineered Muscle Tissues (EMTs) fabricated from primary or iPSC-derived cells, can directly measure tissue contractility, which is challenging in conventional 2D platforms where cells are rigidly attached to a surface. However, traditional methods to fabricate EMTs demand extensive bioengineering expertise, and measuring contractility often involves laborious, serial, and low-throughput optical measurements.  Here, we report on the design, fabrication, and validation of a novel 3D EMT platform that uses 1) facile and scalable bioengineering approaches to generate tissues from a variety of cell sources, and 2) a label-free parallel measurement technique. Our tissue casting approach has a success rate of >96% (n > 100) and produces consistently-sized constructs with a standard deviation of +/- 9% across 6 experiments. Tissue casting, media changes, and drug dosing are also highly amenable to automation.  The substrate features an embedded magnet; as tissues contract, the magnet’s displacement is quantitatively detected in a highly-parallel manner using specialized sensors. We detected 24 contractions simultaneously with a measurement rate of 100Hz, which is suitable for measuring various aspects of contractility such as upstroke velocity, decay time, and fatigability. We demonstrated that the signal voltage changes are linear with respect to EMT contraction. We will present data showing acute effects of drugs measured minutes after EMT dosing and chronic effects of structural cardiotoxicants like doxorubicin, sunitinib, and BMS-986094 on EMTs. All chronically-dosed tissues showed statistically significant dose-dependent reduction in twitch frequency over a multi-day time course (p < 0.05). We will also show that our platform can be used to generate physiologically-relevant skeletal muscle constructs and achieve tetanic responses upon stimulation.  In addition to modeling healthy tissues, our platform can also be used to study disease models. We are currently developing patient-specific Duchenne Muscular Dystrophy models for the development of personalized gene therapies. EMTs can be made from cells sourced from patients and used to test whether a new therapy will improve or recover functional contraction. We have designed a novel system that can leverage the complexity of 3D cellular models in a scalable format and can be tailored for specific applications, including personalized medicine or disease modeling. The Mantarray platform will provide a stand-alone tool capable of screening significant numbers of compounds for the rapid safety evaluation of drug candidates thereby accelerating drug discovery and development."
hPSC-derived Organoids, COVID and Drug Screening
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Open to view video. hPSC-derived cells/organoids provide a platform to systematically evaluate the tropism and cellular response upon viral infection, which can be adapted to screen for anti-viral drugs. In response to the COVID-19 pandemic, we create a panel of hPSC-derived cells/organoids to study SARS-CoV-2 tropism. By screening ten different type of cells and organoids, we found that lung, colon, heart, liver, pancreatic organoids and dopamine neurons can be infected by SARS-CoV-2. This work presented the first stem cell model to understand the tropism of SARS-CoV-2, which led to a clinical trial to study beta cell function in COVID-19 patients. Furthermore, we reported the first organoid-based screen and identified several drug candidates blocking SARS-CoV-2 entry. One identified drug, imatinib, is currently being evaluated in several phase 2/3 clinical trials globally. Using this platform, we are screening the ReFRAME library for anti-SARS-CoV-2 drugs. Finally, we created an immune-host mini-heart tissue to model macrophage-mediated cardiomyocyte damage in COVID-19 patients. A high content screen using immune-host mini-heart tissue identified JAK inhibitor, which protects cardiomyocytes from macrophage-mediated damage upon SARS-CoV-2 infection.
Screening cellular models of neurological disease
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Open to view video. Disease, injury, and aging induce reactive astrocyte states with pathological functions. In neurodegenerative diseases, inflammatory reactive astrocytes are abundant and contribute to progressive cell loss. Modulating the state or function of these reactive astrocytes thereby represents an attractive therapeutic goal. Leveraging a cellular phenotypic screening platform, we show that chemical inhibitors of HDAC3 effectively block pathological astrocyte reactivity. Inhibition of HDAC3 reduces molecular and functional features of reactive astrocytes in vitro including inflammatory gene expression, cytokine secretion, and antigen presentation. Transcriptional and chromatin mapping studies show that HDAC3 inhibition mediates a switch between pro-inflammatory and anti-inflammatory states, which disarms the pathological functions of reactive astrocytes. Systemic administration of a blood-brain barrier penetrant chemical inhibitor of HDAC3, RGFP966, blocks reactive astrocyte formation and promotes axonal protection in vivo. Collectively, these results establish a platform for discovering chemical modulators of reactive astrocyte states, inform the mechanisms controlling astrocyte reactivity, and demonstrate the therapeutic potential of modulating astrocyte reactivity for neurodegenerative diseases.
Label-free imaging and deep learning analysis of patient-derived organoids to study tumor microenvironmental interactions
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Open to view video. 3D organoids, an in vitro model system that recapitulates physiological conditions in biology, are being considered as a predictive biomarker for drug response in cancer. However, cancer cells interact with a complex stromal microenvironment, including cancer-associated fibroblasts (CAFs), that impact drug response and patient prognosis. To examine how tumor-stromal interactions alter cancer cell survival, growth dynamics and drug effects, we established a tumor organoid-CAF co-culture model in a 3D gel matrix. A small liquid dispenser was used to automate the co-culture seeding process in 96-well plates. To build a faster and dynamic imaging-based drug screening pipeline, we performed the following: (1) label-free confocal imaging using a resonant scanner that scanned 3D organoids 2-3 times faster than conventional galvano scanner, resulting in a significant reduction in image acquisition time, (2) generated a new image analysis workflow with several image pre-processing steps including extended focal imaging, (3) created a macro file to facilitate large-scale batch image analysis, (4) used a deep learning algorithm, U-net, to train convolutional neural networks (NNs) to analyze label-free organoid images with live and dead organoid classifications over multiple timepoints and with drug treatments, and (5) generated drug dose response curves using the NN classifications and compared the results to a traditional cell viability assay, CellTiter-Glo 3D. Quantification of morphological features revealed more cystic shaped organoids when co-cultured with CAFs versus organoid monoculture conditions. The trained NN distinguished live and dead organoids and morphological shifts in organoid-CAF co-cultures with multiple drug treatments. On the contrary, viability readouts from the luminescence-based CellTiter-Glo 3D method were unable to distinguish drug effects on organoids in the organoid-CAF co-culture setting due to the population-based readout. Therefore, our label-free organoid imaging workflow can be implemented for drug screening to expedite the identification of new stromal targeting drugs in cancer therapy.
Novel Patient-derived Organoid Models to Develop Drug Treatment Strategies
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Open to view video. "Organoids such as IPSC derived brain organoids (Lancaster et al Nature 2013) or our adults epithelial stem cell derived organoids (Sato et al., Nature 2009, 2011) are proving to be a major breakthrough in preclinical models. The new patient like models are fundamental change in the way drug discovery and development can be performed. The development of the HUB Organoids started in the lab of Hans Clevers with the discovery of the identity of adult stem cells in human epithelial tissues such as intestine and liver (Barker et al., Nature 2007; Huch et al., Nature 2013). With the identification of these stem cells, we were able to develop a culture system that allowed for the virtually unlimited, genetically and phenotypically stable expansion of the epithelial cells from animals including humans, both from healthy and diseased tissue (Sato et al., Nature 2009, 2011; Gastroenterology 2011; Huch et al., Nature 2013, Cell 2015; Boj et al., Cell 2015). We have now generated HUB organoid models from most epithelial organs. Recently, we and others have demonstrated that the in vitro response of organoids correlates with the clinical outcome of the patient from which the organoid was derived (Dekkers et al., Sci Trans Med 2016; Sachs et al., Cell 2018; Vlachogiannis et al., Science 2018). In addition, we have developed a coculture system using HUB Organoids and the immune system to study this interaction and drugs that target the role of the immune system in cancer and other diseases. We have recently developed new models to study intestinal and lung barrier function and transport of the epithelium of these organs. These experiments show how organoids can be used to study mechanism that underlay barrier function disruption in IBD or COPD. Furthermore, we have developed new models to study the interaction between immune system and epithelium. The combination of the new coculture models and assay development to study the epithelium allows us new insights into disease mechanisms and drug treatment strategies.
Genesis of a Phase I clinical trial for a Parkinson's disease
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Open to view video. Will discuss the preclinical data leading to a trial of human ES-derived dopamine neurons for Parkinson's disease.
Data Science and AI
A.I. for the Future of Work in Biotech
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Open to view video. "The Artificial Intelligence (A.I.) industry has created new jobs that are essential to the real-world deployment of intelligent systems. Part of these new jobs typically focus on labeling data for machine learning models or having workers complete tasks that A.I. alone cannot do. The human labor behind our A.I. has powered a futuristic reality with self-driving cars, voice based virtual assistants,  or search results with minimum hate speech. However, the workers powering the A.I. industry are often invisible to end-users. Their invisibility has led to power dynamics where workers are often paid below minimum wage,  and have limited career growth. Part of the problem is that these platforms are currently also black boxes, where we have limited information about the labor conditions inside. I will present how we can start to address these problems through my proposed ""A.I. For Good"" framework. My framework uses value sensitive design to understand people's values and rectify harm. I will present case-studies where I use this framework to design A.I. systems that improve the labor conditions of the workers operating behind the scenes in our A.I. industry; as well as how we can use this framework to audit digital labor platforms and hold them accountable of the conditions they provide to workers. I conclude by presenting a research agenda for studying the impact of A.I. in society; and researching effective socio-technical solutions in favor of the future of work, especially within the context of biotechnology.
Accelerating the Drug Discovery Process with AI-driven Automation technologies: De novo design, Retrosynthesis and Scheduling
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Open to view video. The drug discovery and development process is notably complex and iterative, and is therefore time-consuming and expensive. This process follows the DMTA (Design-Make-Test-Analyze) iterative cycle to optimize the pharmacological and drug-like properties of potential drug candidates. Owing to the challenges of each component of this cycle, bringing a new drug from the discovery stage to market can take up to a decade and can cost well over a billion dollars. This process can be accelerated by addressing the underlying challenges, and streamlining the components of the DMTA cycle. At Iktos, we have developed a pipeline that incorporates robotic automation with an Artificial Intelligence (AI) based approach to make the drug discovery process significantly more efficient. Beneath the challenges of automating this process, i.e. automating drug design, synthesis, and testing, lies a critical organization and scheduling problem. It is crucial to use the available time and resources efficiently to minimize failure rates and improve scalability. Specifically, synthetic routes to molecules of interest have to be planned, organized, executed, and starting materials have to be available or ordered. Molecules should be made so as to not waste effort or resources. Biological tests have to be carried out efficiently and in a parallelized fashion, and prioritization decisions have to be made and modified as the cycle evolves. All the generated information needs to be used to better inform the next generation of molecule design. Finally, all of these processes need to occur through an orchestration of AI, robotics, automated reactors, and analytical instrumentation to reach the goal of a fully automatic drug discovery platform. We have developed a pipeline to accomplish this and it is comprised of our AI platforms for drug design (Makya), retrosynthesis (Spaya), and the automated task scheduling platform called Ilaka that can propose a detailed long-term schedule to maximize efficiency, and is also capable of scheduling robotics jobs. Using an active learning approach, the components of this pipeline work together seamlessly which allows for faster convergence towards optimal drug candidates by quickly recognizing any potential failure modes, thereby increasing the likelihood of success. For instance, if a high throughput molecular design and synthesis job encounters unexpected failures, Ilaka will appropriately reorganize the workload schedule to maximize the output. Overall, our pipeline can achieve (i) efficient chemical space exploration; (ii) drastic acceleration of the DMTA cycle thanks to short synthesis time; and (iii) dramatic cost savings in molecule synthesis by relying on robust and proven chemistry. This is the first automated AI-driven drug discovery platform of its kind. Innovations in AI and automation are impacting how we approach drug discovery and development, and we expect tools such as Makya, Spaya and Ilaka to become vital components of this changing landscape.
Accessible AI for Small Molecule Discovery Research: Considerations and Value Drivers
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Open to view video. New advances in data science and AI bring valuable insights and cost-savings that drive discovery projects. We will explore the challenges and drivers impacting the adoption of AI in discovery organisations including pharma, biotech, academia and not-for-profit. We will illustrate these using case studies on the application of Optibrium’s Cerella™ platform for deep-learning imputation with collaborators in drug discovery and other chemistry optimisation fields. Common themes highlight bottlenecks and gaps in current discovery approaches and valuable applications of AI that address them.
Automated Image Analysis with Deep Learning to drive Cardiac Safety Profiling
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Open to view video. "Cardiotoxicity is a crucial consideration during early stages of drug development to de-risk new therapies and maximise patient safety. Current in vitro models are restrictive as they are either highly target-centric (e.g. hERG) or have limited translatability for structural cardiotoxicity due to simplified cell systems or analysis methods. In answer to this, a deep learning based image analysis approach (Genedata Imagence) was deployed on a 3D cardiac microtissue (CMT) high content imaging assay, with the aim of deriving increased mechanistic insight and increased sensitivity. One of the main challenges here was to maintain tissue-level phenotypic information while achieving a high enough object count for robust classification at scale. A solution was found in analysing 50-100 tissue subregions from widefield or 2D projections of the CMT images. This enabled phenotypic classification on a tissue level while maintaining high enough throughput for production-level profiling. Applying this approach, a neural network was trained using a collection of known cardiotoxins in live CMTs to annotate phenotypes that represent a potential cardiac safety risk. Around a dozen distinct phenotypes were identified and trained to a high degree of confidence, based on a triple stain for mitochondria, ER and nuclei. To guide in the phenotype interpretation for a range of end-users, the most similar phenotypes were grouped to fall into 6 categories, but drill-down options were kept available for detailed analysis. In addition, the neural network was also able to identify and flag a broad spectrum of interference, including (cellular) debris and fluorescence artefacts. From a test set of roughly 80 in-house compounds, phenotypic classification achieved excellent correlation with the legacy segmentation-based analysis approach. In addition, we observe several benefits of the deep learning approach: 1) Direct correlation of test compounds to known cardiotoxins that were used to train the network enables increased mechanistic insight; 2) Identification of novel phenotypes even while the assay is in production, allows for the continuous improvement of the neural network and phenotypic clustering of test compounds; 3) Increased assay robustness; 4) Time-savings through automated analysis of production-level screens and easy of development/transfer. Finally, early data suggests we observe higher assay sensitivity, which could enable detection of cardiotoxins that were previously missed."
How Artificial Intelligence techniques can be employed to increase the success rate for identifying Datamatrix Barcodes
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Open to view video. "Datamatrix barcodes play a key role in tracking and tracing both biological and compound samples. These barcodes are usually lasered onto the underside of sample tubes, and the tubes are stored in racks. Barcode reading is conducted using a barcode reader that scans the bottom of a rack of tubes and decodes all barcodes in one go. This is nice in theory, but there are regular issues with identifying the barcodes on the bottom of the tubes. Ambient lighting, background image noise, and variation in lasering and material quality yield tube barcodes that are often difficult to detect with traditional machine vision techniques. However, it can be noted that a human can always resolve these barcodes, even in adverse conditions. Therefore, it is reasoned that artificial intelligence techniques can be employed to increase the success rate for identifying datamatrix barcodes. Convolutional Neural Networks (CNNs) are a well understood technique for feature extraction of images. In this work we take the notion of the CNN and apply it to the new application for locating 2D datamatrix barcodes on sample tubes. The chosen CNN is designed to be very lightweight allowing for quick execution. When compared to the pre-existing heuristic methods, the CNN approach was almost ten times faster to execute with virtually 100% accuracy. The CNN is implemented on embedded technology, in this instance a Field Programmable Gate Array (FPGA). FPGAs allow for custom circuity to be created for specific application; due to the custom nature of the implementation this yields a very high-speed CNN, faster than can be achieved on a standard PC processor. The inclusion of the FPGA to the system opens new possibilities to the way in which the barcode scanners can be implemented. The power of the embedded FPGA means it is now possible to build a stand-alone mobile scanner, capable of decoding an entire rack in a sub-second timeframe while having low power requirements and outperforming a traditional high-spec laptop or desktop PC. Future work will build on the current achievements of the project and look to introduce more artificial intelligence techniques into the decoding step of rack scanning."
How to position your biotech startup to be an innovation leader with a well-crafted data strategy
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Open to view video. Conversations about data are ubiquitous across the biotech and pharmaceutical industries, but so many organizations still miss the mark on the strategy and execution of digitized research and analytics. Technology and data science leaders in the startup space have a rare and short-lived opportunity to create a framework from the beginning that can set their companies apart and create value for the rest of the organization. The speed of innovation, research, and the scale of competition across the industry has positioned the use of data as a huge differentiator in successful outcomes. This presentation will focus on how to create an executable digital data strategy, and perhaps more importantly, why it must be justified and bought into by the rest of the early team - both in leadership all the way through to bench scientists. Data is a core asset and while the typical FAIR principals still apply, setting up an ELN and calling it a day won't provide the deep insights and transformative knowledge that accelerates drug discovery and research. A long-term strategy with built-in adaptability will allow a startup biotech to surface knowledge from data at an exponential rate, and will pay dividends in research speed, operations, and in the avoidance of costly data transformation projects in the future. Well-organized data and a culture of citizen data analysts within the research team can open the doors for your data to set you apart among the crowded biotech industry.
Integrating Experiments and Machine Learning Models: Examples from the ATOM Consortium
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Open to view video. Predictive data-driven machine learning models are an important component of emerging approaches to accelerate molecular design. An integrated process for connecting targeted experiments with model algorithms and architectures is central to predictive performance and domain of applicability. The presentation will focus on two examples of this experiment-AI integration: 1) development of new drug-induced liver injury (DILI) models for assessing the safety of a proposed molecule; and 2) the development and use of efficacy, safety, and pharmacokinetic models for multiparameter design optimization of novel and selective histamine inhibitors.
Why a LIMS isn't enough: Building robust laboratory software landscapes
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Open to view video. "Many laboratories purchase a LIMS in the hope that it will be the answer to all laboratory software questions and struggle to know what other systems could be beneficial and when their lab might need a larger software ecosystem to fully support it’s operations. Like all software, each LIMS has a specific set of features and functions which makes it better suited to some tasks than others. As the marketplace grows, LIMS have emerged which are increasingly tailored to certain disciplines (e.g. microbiology, chemistry, bioinformatics) providing increased support for specialized areas but reducing the likelihood of flexible, broad range applicability across organizations. And while many enterprise LIMS vendors provide additional applications in order to fully support laboratory operational needs, they can be prohibitively expensive or require more support than desired depending on the feature sets provided.  In this talk, we will provide information on the various processes within laboratory operations where software can prove beneficial by reducing errors, creating efficiency gains, or both. We will demonstrate through case studies how different needs can produce different laboratory software landscapes. During the talk, listeners will learn about overall software strategies, such as enterprise vs. best of breed and the benefits and risks to each approach. We will review the types of software they might consider to meet their needs, (LIMS, ELN, QMS, integration engines, data analytics platforms, etc.), what the focus of each software application is and the task it is best suited for, as well as what questions to ask when assessing these systems for fit within their own laboratory. Finally, we will provide information on the trigger points that commonly cause laboratories to consider adding new software or upgrading current systems. At the end of the talk, listeners will emerge with an overall picture of how and where software can support laboratory operations as well as the set of applications (in addition to LIMS) commonly found in laboratories and strategies to assess their own software landscape for improvements in the future."
Why Data Maturity is Essential to the Lab of the Future
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Open to view video. "Yesterday’s data differentiator was universal connection. Today, it all comes down to access. And tomorrow, the data advantage will be held by those who leverage artificial intelligence to analyze reactions and optimize operations. The evolution of laboratory data collection has evolved faster than most LabOps players predicted — and many legacy brands are able to respond. The way scientific organizations embrace or reject data maturity will determine whether they disrupt an industry or find themselves disrupted. This presentation will harness years of experience working alongside hundreds of lab leaders and feature insights regarding the future application of deep tech to data collection and analysis. Attendees will walk away with best practices for optimizing their operations, both today and in the future. Takeaways: How lab managers can optimize their lab’s usage of data to measure the long-elusive ROI of R&D Why legacy organizations face steeper hurdles to data maturity than nimble startups How research and researchers will be impacted by the advance of artificial intelligence and automation
The Sweet Spot for Sustainable Labs of the Future
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Open to view video. "Science moves fast. Technology moves fast. Investment cycles rarely do. Money isn’t unlimited.   In the world of the modern automated and connected laboratory, sustainable data and technologies need to be both nimble and robust, resilient over time to enable lab research to evolve whilst not spiraling in cost.   We want the smart scientist to focus on using her expertise for insights and decision making.    We want to build around her a world of augmented and distributed environments with frictionless interfaces that enables her to easily engage with a dynamic range of equipment as she executes her experiments. Paperless labs work around her, data is automatically documented directly from smart equipment, laboratory automation performs standard tasks, and the first drafts of reports are automatically built using AI-ML enabled authors. Equipment runs 24/7 but she doesn't have to, fully utilising IoT, industry 4.0 and remote-control connections that seamlessly live stream for real time and off-line decisions. No experiment is wasted as all data flows into AI-ML enabled models which inform future upstream experiment designs. Quality is embedded and data integrity is bullet-proof.   However, historically siloed, narrow decisions of functional laboratory leaders across the life sciences industry have inadvertently shaped the current application landscape in what the outside world sees as a relatively niche area.  Technology solutions rarely support both R&D and manufacturing laboratory environments or the regulated vs non-regulated spheres. No discovery scientist wants to be locked into GXP for no reason, no manager wants to pay for GXP and non-GXP versions of the same technology. Single-purpose lab applications also frequently require extensive professional services to integrate. Rarely does a solution come off-the-shelf.   If not managed carefully, the research scientist interacts with more products than any other user in any other industry!  Her time is too important to train on yet another system.   So, what do we do?   There is a sweet spot between full flexibility to operate in an ever-evolving dynamic way and managing the technical debt for a consistently sustainable laboratory environment.   We will outline strategic approaches to make a data science and AIML enabled laboratory robust, relevant and sustainable."
Impact of Remote and Changing Workforce on Lab of the Future
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Open to view video. We will look at the key workforce drivers that are going to impact future lab operations. We will then dive into the use of remote, augmented, and virtual reality technologies and discuss how they will be necessary for the lab of the future.
Micro- and Nano Technologies
Automation of in situ sequencing and high-resolution imaging for spatial transcriptomics
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Label-free biosensor of phagocytosis for diagnosing early and intracellular bacterial infections
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Open to view video. Phagocytic cells recognize and phagocytose pathogens for elimination. After being internalized by immune cells, bacterial pathogens can remain hidden at low levels or replicate intracellularly. This may pose significant challenges in research and clinical settings, where phagocytosis-detection approaches involve flow cytometry or microscopic search often have difficulties detecting rare bacteria-internalized phagocytes among large populations of uninfected cells. Hence it is important to develop a rapid, non-disruptive, and label-free phagocytosis detection approach. Using deformability assays and microscopic imaging, we have demonstrated for the first time that phagocytes with internalized bacteria display more aberrant physical properties, including stiffer surface and larger size, compared to uninfected monocytes. Taking advantage of these physical differences, a novel microfluidics-based biosensor platform for phagocytosis detection was developed to passively sort, concentrate and quantify rare monocytes with internalized pathogens (MIP) from uninfected monocyte populations. The clinical utility of the MIP platform was demonstrated by enriching and detecting bacteria-internalized monocytes from human blood samples rapidly (1.5 h). Patient-derived bacterial isolates were further used to validate the clinical utility of the MIP platform. In conclusion, our proof-of-concept platform could be used to rapidly diagnose microbial infections via detection of phagocytosis, thereby improving the clinical outcomes for point-of-care management of early infections.
Liquid Biopsy in Hematologic Malignancies – Promise and Challenges
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Open to view video. " For most hematologic malignancies, the main diagnostic sample is from bone marrow biopsy or the use of imaging to detect lymphadenopathy. These procedures are either uncomfortable or maybe associated with radiation and may lack sensitivity. Some of the hematologic malignancies such as multiple myeloma may have patchy involvement, and also spatial heterogeneity, as such a single biopsy may not adequately represent disease biology. These issues could potentially be overcome by liquid biopsies which allow disease detection, biological assessment and disease monitoring using the ease of a blood sample. The range of information that can be obtained has also increased significant to now include, circulating tumor cells, cell free DNA (mutations of genes or aneuploidy), miRNA, and DNA methylation. Microfluidics devices has been developed to quantitate circulating tumor cells. Some of these devices are based on physical properties rather than protein makers and may allow the recovery of live cells for further studies. In addition, the ability to harvest circulating tumor cells also allow the study of drug resistant residual cells, so that these may be specific targeted. The use of blood allows regular monitoring as opposed to regular scans or bone marrow examination which is not feasible. While liquid biopsy holds much promise, there are several areas that are unresolved. For one, which type of information will be most useful? Is the sensitivity good enough for minimal residual disease monitoring? Can it replace current diagnostic, prognostic or monitoring test? Liquid biopsy is an important advance even for haematologic malignancies but there are some issues that requires further resolution. Ongoing studies will provide further insights in the coming years.
MARS® Advanced Cell Separation Platforms Provide Turnkey Solutions for Single Cell Multi-Omics and Cell Therapy Manufacturing
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Open to view video. "Tumor biology, immunology, and immune-oncology from multi-omics at single cell level has witnessed unprecedented acceleration in recent years, with a major contribution of such speedup from new technologies and products bursting into market. New technological solutions also contributed deterministically to the promise of cell-based therapy. However, standard sample preparation protocols widely practiced to obtain single cell suspension still involves decades-old centrifugation processes which are tedious and greatly affected by human factor. In development of cell therapy drugs, robust cell manufacturing systems that are flexible, adaptable to various processes, and involving minimal human factor, are widely sought after. MARS Cell Separation Platforms incorporate innovations in multiple cell separation technologies. MARS are constructed as modular platforms to support wide range of applications in life science arena, including single cell analysis, precision medicine, as well as cell therapy. In this talk, we will present to you - 1) Case studies of using MARS high speed tunable acoustic chip technologies to purify single cells and sing cell nuclei from solid tissue dissociation cell suspension and demonstrate the reagent-free timesaving process on MARS compared to the conventional method. 2) Examples of MARS “add-add-run” magnetic cell separation solutions, reagents, and protocols, which allow both positive and negative selection of target cells from whole blood, apheresis product and bone marrows. 3) Closed fluidic systems which are designed to run large scale cell separation, in both magnetic cell separation and acoustic cells separation, to support cell therapy development. We will show you how automated MARS cell separation platforms married the benefits of acoustic and magnetic cells separations in realizing first-of-its-kind cell separation results, and offering a simple, effective, and revolutionary solution to prepare cell samples for downstream applications.  "
Maximizing multiomic insights with Single Cell high-throughput (HT) gene expression
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Open to view video. Combinatorial drug treatment has been proposed as a strategy to overcome rare resistant clones. However, rapid progress in drug discovery and the numbers of possible combinations make it challenging to find suitable combinations. In this talk, we demonstrate how high-throughput (HT) single cell gene expression and multiomic analysis coupled with cell multiplexing enables high-throughput screening of multiple combinatorial conditions.  Non-small cell lung cancer (NSCLC) cell lines are great models for a combinatorial drug screen as they possess multiple forms of resistant clones. Taking the advantage of the scale of Chromium Single Cell Gene Expression HT assay, we analyzed a total of 192 samples, or ~960,000 cells on a single microfludic chip. UMAP projection of all of the treatment and time point conditions showed that H1975 cells, bearing a EGFR mutation, are more responsive to combinatorial drug treatment than that of A549 cells, bearing a KRAS mutation. The cell cycle and DNA repair pathways were down-regulated as early as 4h and continued until 24hr. The main affected gene network by the combinatorial treatment are cell cycle checkpoints and DNA double-strand break repair. We see less effect in the single treatment conditions, suggesting the regulation of the networks is a result of synergistic regulation of multiple pathways.  In a separate study, we profiled single cell transcriptomes and surface protein markers from 7 multiplexed primary NSCLC cell lines. Single cell multiomic studies are easily carried out with the HT platform. By adding protein detection alongside single cell transcriptome analysis, cell types can be better inferred, making cell annotation less challenging. The scale of HT provides an opportunity for identifying low occurrence tumor types, e.g., ELF3+/EPCAM+ tumor. The identification of rare tumor types is key to understanding evolution of drug resistance and metastasis clones. This kind of study will shed light on therapeutic discovery of actionable targets. Finally, we found the common signaling pathways shared by the primary NSCLC models and A549 cell line. This suggests that A549 would be a great option to perform future large-scale screening for the KRAS-mutated type of NSCLC. Overall, this study highlights the scalability of single cell approaches using Chromium Single Cell HT, and the applicability of multiomic technologies on the HT platform to enable the high resolution study of biology.
Microfluidics-Guided in situ Barcoding for Spatial Omics Tissue Profiling
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Open to view video. Despite latest breakthroughs in single-cell sequencing that revealed cellular heterogeneity, differentiation, and interactions at an unprecedented level, the study of multicellular systems needs to be conducted in the native tissue context defined by spatially resolved molecular profiles in order to better understand the role of spatial heterogeneity in biological, physiological and pathological processes. In this talk, I will begin with discussing the emergence of a whole new field – spatial omics in the past years and then discussing a new technology platform called DBiT-seq – microfluidic Deterministic Barcoding in Tissue for spatial multi-omics sequencing – developed in our laboratory. It demonstrated, for the first time, co-mapping of whole transcriptome and a large panel of proteins with high spatial resolution directly on fixed tissue slides in a way fully compatible with clinical tissue specimen processing. First, I will show the application of DBiT-seq to spatial transcriptome and protein mapping of whole mouse embryo tissues that revealed all major tissue types in early organogenesis, brain microvascular networks, and a single-cell-layer of melanocytes lining an optical vesicle. Second, I will discuss spatial transcriptome mapping of FFPE tissue slides including archival human tumor specimens. Third, I will show the power of integration with single-cell RNA-seq for cell type annotation in relation to spatial location in tissue. Finally, I will discuss the latest progress of DBiT as a platform technology to enable spatial epigenome sequencing (spatial-ATAC-seq, spatial-CUT&Tag, etc) at cell level. The rise of NGS-based spatial omics is poised to fuel the next wave of scientific revolution in biological and biomedical research. Emerging opportunities and future perspectives will be discussed with regard to the impact on biomarker discovery and therapeutic development.      
Uncovering gene regulatory programs and understanding human disease using single-cell epigenomics and transcriptomics
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Open to view video. Genomes are more than abstract sequences of nucleotides. Epigenomic technologies have revealed how they exist in situ bound by proteins, modified by enzymes, and folded in complex 3-dimensional structures within a cell's nucleus. This epigenetic information regulates gene expression and is critical for understanding how cells function and malfunction in health and disease. However, conventional technologies to profile the epigenome mask the cellular heterogeneity that exists in biological samples by assaying samples in aggregate. Thus, tissue heterogeneity poses a significant challenge to reading this epigenetic information. Therefore, we have implemented optimized workflows for single-cell omics - including single nucleus RNA-seq and single nucleus ATAC-seq – to profile cells/nuclei from normal and diseased tissue samples across more than 50 sample types - including primary brain, heart, and lung tissue. Here, we present our streamlined workflows for sample preparation, experimentation, library construction, as well as data processing and QC analysis. We employ standardized protocols, semi-automation via liquid handling robotics, rigorous quality control, and uniform data processing to enable all aspects of large-scale data generation including, but not limited to, 1) the rapid optimization of protocols to maximize data quality 2) data quality consistency from sample-to-sample during data production, and 3) the minimization of failure rate. To date, we have deployed our workflows across multiple small- and large-scale efforts, having generated >1,800 datasets and assayed >50 unique sample types spanning >16 species in the process. We will discuss this process and several case studies of generating large-scale datasets via these approaches – including our efforts to generate a cell-type resolved gene regulatory atlas of 30 primary tissues spanning the human body. All together, we will present our efforts to standardize, scale, and combine -omics such as single-nucleus RNA-seq and single-nucleus ATAC-seq, as well as discuss the application of such methods to deconvolute the cellular composition of tissues, identify rare cell populations, and study epigenetic gene regulation in the context of human disease.
Increasing throughput of targeted in situ sequencing
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Open to view video. "Single-cell RNA-seq (scRNAseq) is a powerful tool to classify cells into molecularly defined cell types. However, information about spatial location within the original tissue is lost. I will present work on developing and applying targeted in situ sequencing (ISS) to build spatial maps of scRNAseq-defined celltypes in cm2 sections of human and mouse tissues (Ke, R., et al. (2013) Nature Methods 10, 857-860). We have applied the method to draw spatial cell maps of human developmental heart tissue, where marker genes were selected from both Spatial Transcriptomics and scRNAseq data (Asp et al. (2019) Cell, 179, 1647-1660). We have continued this work and have finalized human developmental lung maps (manuscript in prep) and a complete map of the nervous system of a E10.5 mouse embryo (La Manno, G., et al. (2021) Nature 596, 92-96). We have improved the ISS chemistry to improve signal-to-noise, and detection efficiency which has allowed us to map expression of 160 genes in human brain cortex, samples that are challenging to analyze due to high autofluorescence (Gyllborg, D., et al. (2020) Nucl. Acids Res. 48, e112), also allowing us to draw the first spatial map of transcriptomically defined cells in a human cortical region (Mattsson Langseth, C., et al. (2021) Communications Biology 4, 998).  We are also using our targeted in situ sequencing to map expression- and mutational heterogeneity in tumors (Lomakin, et al. (2021) bioRxiv). By targeting mutations identified by deep sequencing, we create maps of clones of subtypes of cancer cells across tissue sections. We then overlay these maps with in situ expression profiles of tumor marker genes, as well as, immune celltype- and activity markers, to create oncomaps where we aim to predict treatment responses for different sub-clones of the tumor. I will particularly focus on our work towards increasing the throughput of the ISS method through improved chemistry, automation, imaging, and image analysis."
Leukemia-on-a-Chip for modeling and decoding the heterogeneous mechanisms underlying therapy resistance
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Open to view video. B-cell acute lymphoblastic leukemia (B-ALL) blasts may hijack the bone marrow (BM) to form chemo-protective leukemic BM ‘niches’, facilitating chemo-resistance and ultimately disease relapse. However, the ability to study these heterogeneous interactions among distinct B-ALL subtypes and their BM niches is limited by current in vivo methods. Herein we report an in vitro biomimetic 3D ‘Leukemia-on-a-Chip’ model to dissect the evolving heterogeneity of the BM niche in regulating B-ALL chemotherapy resistance. The 3D microfluidics-based organotypic ‘Leukemia-on-a-Chip’ device is composed of three distinct functional regions: a central sinus region vascularized by endothelial cells (ECs), an inner ring region serves as an interface of leukemia blasts (B-ALL cells) and niche cells (ECs and MSCs) interactions, and the outer ring for cell culture media supplies and waste removal. The system was characterized by time-lapse imaging, single-cell mRNA sequencing (scRNA-Seq) and fluorescence immunostaining, as well as drug testing. The bioengineered model faithfully replicated the in vivo leukemia BM pathology. Using the model, we monitored dynamic behaviors of B-ALL blasts with or without niche cells and found that B-ALL blasts without niche continuously migrated during culture, whereas those with niche cells became less motile after 2-day culture. To understand the heterogeneity of distinct human B-ALL types, such as favorable REH and unfavorable SUP, we mapped the two niches with scRNA-Seq and found that B-ALL blasts in both niches were variously activated in TNFA signaling via NF-κB. We confirmed this finding with on-chip immunostaining NF-κB and found that NF-κB was significantly enhanced in those with niche cells. Finally, we tested the preclinical use of our platform to screen niche-co-targeting regimens. In conclusion, we have demonstrated a unique organotypic Leukemia-on-a-Chip microphysiological system and comparatively dissected the underlying heterogeneous mechanisms regulated by niche cells to drive leukemia progression and chemo-resistance. We anticipate this platform can be applied to many other hematological malignancies, presenting a powerful tool for drug development under a more physiologically relevant context.
Novel Techniques for Integrating Hydrogel Biointerfaces in Organ-on-a-Chip (OOC) Systems
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Open to view video. The vast majority of organ-on-a-chip (OOC) devices currently being developed for biological research involve the use of polymeric device materials (e.g., PDMS, PMMA, PETE membranes) containing rigid planar surfaces that do not accurately mimic the physiological stiffness of the extracellular matrix (ECM) found in vivo. To address this issue, three-dimensional (3D) hydrogels are frequently used in OOC devices to model the ECM more accurately, and to serve as a scaffold for embedded cells. These hydrogels, however, are typically inaccessible for off-chip analyses and surface probing, limiting our ability to study complex cell-matrix interactions and matrix remodeling. Novel micro-engineered approaches are beginning to emerge that allow enhanced access to OOC-embedded hydrogels, including the analysis of whole hydrogel constructs as well as hydrogel surfaces, enabling the study of more complex questions and deeper examination of the OOC matrix microenvironment. Here we discuss recent advances in the integration of 3D hydrogels as biointerfaces for organ-on-a-chip (OOC) applications. First, we describe an extractable and suspended hydrogel-based airway-on-a-chip model called E-FLOAT used to study aerosolized particle delivery under physiological airflow. We demonstrate that the extractability of the hydrogel enables the study of particle-cell-matrix interactions using off-chip histological sectioning, H&E staining, and scanning electron microscopy that would be difficult or impossible with on-chip analyses alone. Second, we describe a unique microfluidic device architecture called TANDEM that enables multiplanar arrangements of aligned microchannels where both normal and transverse diffusion can occur “in tandem” to facilitate multidirectional cell-cell communication. In addition, TANDEM allows access to hydrogel interfaces in a manner that enables direct on-chip measurement of hydrogel stiffness using techniques such as atomic force microscopy. Together, these advances highlight the development of integrated hydrogel interfaces in OOC systems that can be extracted, probed, and examined using analytical techniques more commonly used for ex vivo tissues and tissue-engineered constructs.   
New Modalities
Arvinas' PROTAC® Discovery Engine
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Open to view video. Arvinas aims to treat cancer and neurological disorders by specifically targeting disease-driving proteins for degradation by the ubiquitin-proteasome system using PROteolysis-TArgeting Chimeras (PROTAC® protein degraders). A PROTAC protein degrader is a bifunctional small molecule that recruits a specific ubiquitin ligase (E3) to a target protein of interest, thereby inducing proteasome-mediated degradation of the ubiquitin-modified target. ARV-110, a PROTAC protein degrader that drives androgen receptor degradation, is currently being evaluated in clinical trials for treatment of metastatic, castration-resistant prostate cancer. The estrogen receptor (ER)-targeting PROTAC protein degrader ARV-471 is being evaluated for treatment of ER+ locally advanced or metastatic breast cancer. Preclinical and early clinical data for these two programs will be presented. Our PROTAC discovery engine is also being employed to develop a robust pipeline beyond ARV-110 and ARV-471. Data will be presented on our discovery of PROTAC protein degraders that recruit an E3 not previously reported for use with protein degrader technology. Topics discussed will include approaches for target and E3 selection, target and E3 ligand identification, and considerations for PROTAC design for human therapeutics.
Toolbox to discover new molecular glue degraders
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Open to view video. Monte Rosa’s QuEEN™ (Quantitative and Engineered Elimination of Neosubstrates) platform enables us to rationally discover and develop selective molecular glue degraders (MGDs) to disease-relevant proteins. We have compiled a growing catalogue of over 1500 proteins identified through our AI-driven approach, containing proteins of diverse protein classes across therapeutic areas, including highly credentialed targets previously deemed undruggable. Monte Rosa uses a proprietary diverse and continuously growing chemical library of drug-like MGDs that are rationally designed based on our expertise in molecular glue anatomy. To discover new MGDs we use a tailored glueomics™ toolbox of highly automated biochemical, biophysical, structural biology, cellular, proteomics and in silico screening tools that connect degrons to MGDs. By leveraging QuEEN and running multiple assays in parallel, we have identified and validated selective MGDs to highly validated and therapeutically relevant but previously undruggable proteins.
RNA Modifying Protein (RMP) Targeted Cancer Drug Discovery
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Open to view video. RNA modifying proteins (RMPs) represent a large class of novel targets for oncology and other disease indications that can be targeted with small molecule inhibitors. The enzyme ADAR1 (Adenosine Deaminases Acting on RNA) catalyzes the majority of A-to-I editing, where it has been demonstrated to effect coding sequence, miRNA function and the detection of repetitive elements by innate immune pathways. Inhibition of ADAR1 has potential as both a monotherapy for tumors with high Type I interferon signaling and in combination with checkpoint inhibitors in relapsed/refractory tumors; target validation and current efforts in drug discovery will be discussed.
Rapid Discovery of Helical Peptide Therapeutics Using Phage Display and Multiparameter Mass Spectrometry Screening
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Open to view video. Helically constrained peptides are an emerging drug modality that allow the targeting of intracellular protein surfaces that are ordinarily inaccessible to small molecules or biologics. We have developed a unique stapled phage display platform that enables the de novo discovery of helical peptide binders to target proteins, and have used this platform to identify dozens of chemical series for a wide range of undruggable targets. High-resolution crystal structures and biochemical studies reveal a diversity of binding modes and mechanisms, including inhibitors, activators, and multimerizers. To rapidly advance these helical hits to molecules with drug-like properties, we have also developed a multiplexed hit-to-lead platform that combines combinatorial peptide synthesis with mass spectrometry-based screening assays for binding affinity, physico-chemical properties, and direct quantification of cytosolic exposure. This platform enables the synthesis and screening of thousands of peptides per week, and we report a case study where this platform is used to optimize a low-micromolar phage hit to a compound with in vivo pharmacodynamic modulation of an intracellular target in less than six months.
Automated high-throughput preparation and characterization of oligonucleotide-loaded lipid nanoparticles
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Open to view video. Lipid nanoparticles (LNPs) are increasingly employed to improve delivery efficiency and therapeutic efficacy of new pharmaceutical modalities, especially nucleic acids. LNP is one of the most effective delivery platforms for mRNA antigens and has led to the success of mRNA-based COVID vaccines. LNPs are also complex formulations composed of helper lipids, PEGylated lipids, as well as charged lipid species for encapsulating nucleic acids, resulting in their unique nanoscale structures. Various formulation parameters can affect the quality attributes of LNP formulations, but currently there is a lack of systemic screening approaches to address this challenge. In this work, we developed an automated high-throughput screening (HTS) workflow for streamline preparation and analytical characterization of LNPs loaded with antisense oligonucleotides (ASOs) in a full 96-well plate within a timeframe of ~3 hrs. ASO-loaded LNPs were formulated by an automated solvent-injection method using a robotic liquid handler, and assessed for particle size distribution, nanoparticle structure, encapsulation efficiency, and stability with different formulation compositions and ASO loadings. Results indicate that the PEGylated lipid content significantly affected the particle size distribution; whereas the ionizable lipid / ASO charge ratio determined the encapsulation efficiency of ASOs. The HTS approach has also been successfully applied to formulation screenings of various LNPs including liposomes loaded with small molecules and LNPs loaded with mRNA. Furthermore, results from our HTS approach correlated with those from the state-of-the-art, scale-up method using a microfluidic formulator, therefore opening up a new avenue for robust formulation development and design of experiment methods, while reducing material usage by 10 folds and improving analytical outputs and accumulation of information by 100 folds.
Discovery and characterization of a VHL molecular glue degrader for cysteine dioxygenase 1
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Open to view video. "The Von Hippel-Lindau tumor suppressor (VHL) is one of the most widely exploited E3 ligases for inducing targeted protein degradation. Over the past several years, VHL chemical probes have been conjugated to various ligands to generate Proteolysis Targeting Chimeras, or PROTACs, which are hetero-bifunctional molecules that bind both VHL and the intended target independently to form a ternary complex leading to selective targeted protein degradation. However, to date no bona fide molecular glue degraders for VHL have been reported. Molecular glues overcome several shortcomings of PROTACs due to their conventional drug-like small molecule character. We describe the discovery of a bona fide VHL molecular glue degrader for CDO1 by screening protein arrays with VHL chemical matter. We demonstrate using biochemical, biophysical and cellular assays that this molecular glue degrader facilitates the assembly of a VHL-Compound-CDO1 ternary complex and brings about VHL-dependent degradation of exogenously expressed CDO1 in engineered 786-0 cells, and endogenous CDO1 in HUH7 liver cells. Applying SAR, we developed an improved molecular glue molecule which results in higher ternary complex affinity. The x-ray structure of the ternary complex reveals key interactions that drive the recruitment of CDO1 to the novel protein interaction surface created on VHL by the glue degrader molecule.  
Discovery of novel degrader molecules with a PROTEINi screening platform
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Open to view video. "In the postgenomic era, opportunities are rich for large-scale, omics approaches for target discovery. Gene editing technologies have significantly improved the landscape for drug development, but blind spots in the reach of these tools are now starting to become apparent. Programme failure due to poor druggabilty profiles is a common theme and progressing new undruggable targets without due support is still perceived as an untenable risk. An ability to modulate the nuances of biological function in high throughput is crucial to adequately probe the druggable space for any disease pathophysiology, and crude on/off perturbation tools are rarely able to screen with this degree of sensitivity. Without such improved tools, the substantial efforts in unbiased drug target ID are likely to yield a pool of promising and yet unactionable candidates.   To fulfil this critical need in drug discovery, we have developed SITESEEKER®, a novel screening technology operating at a substantially greater magnitude of complexity than extant screening platforms. Our unique approach exploits protein interference (or PROTEINi), targeting diseases with computationally-derived coded peptide fragments, evolutionarily enriched for function that can enact precise phenotypic perturbations. The use of a peptide-based element in the context of a functional genomic screen allows for the pre-discovery of the mechanisms for drug development in addition to the ID of new phenotypically tractable targets and significantly truncates the path from target ID to drug development.   We have applied PROTEINi screening in several new areas in serious need of new clinical assets, uncovering new and unprecedented targets and drugs now in late stages of pre-clinical development. In particular, we have deployed SITESEEKER to the challenges of new E3 ligase discovery towards the pursuit of new bifunctional degrader molecules, capable of modulating otherwise undruggable targets. Our cache of novel E3 ligase ligands are active against numerous therapeutic targets and showcase the breadth of proteome space yet to explore in this critical field. We have used combinatorial CRISPR-based screening to unpick the functional dependencies of each degrading PROTEINi and map novel ligands to their cognate E3 ligase. Eight such ligases have progressed through to the early stages of small molecule development, yielding several series primed for development as either bifunctional degraders or monovalent molecular glues. Our SITESEEKER platform is therefore uniquely positioned to dramatically decrease the time taken for new molecules to reach the clinic and positively impact patient outcomes."
Droplet squeezing for CRISPR/Cas9-based T cell genome editing
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Open to view video. Original cell functions can be specifically reprogrammed and manipulated by internalizing external biomolecules such as DNAs, RNAs, plasmid DNAs, proteins, or nanomaterials into cells. For example, clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 genomic editing is accomplished by delivering RNA-guided Cas9 nuclease into target cells. Traditionally external cargos have been introduced into cytosol or nucleus using viruses, lipid nanoparticles, or electroporators; however, they are suboptimal for achieving desired levels of cellular engineering due to their inconsistent and ineffective genome editing quality, cytotoxicity, high cost, and/or low scalability. To bring cellular engineering to the next level, a novel droplet-based intracellular delivery platform is presented by leveraging droplet microfluidics with mechanical cell permeabilization. In our approach, a single cell and external cargos (e.g., mRNAs, plasmid DNAs and CRISPR/Cas9 ribonucleoproteins) were encapsulated into droplets. Then, the droplets were accelerated by the sheath flow and as they pass through a single constriction at high speed, the cell membrane is mechanically permeabilized where the cargos in the vicinity are effectively internalized. Using this platform, we demonstrated a high level of functional macromolecules delivery into various immune cells, including human primary T cells. Furthermore, we demonstrated superior genome editing via CRISPR-Cas9 delivery compared to that of current benchtop techniques such as lipofectamine and electroporation while maintaining high cell viability and biostability, providing a practical and robust approach anticipated to critically impact cellular engineering.
Evaluation of 3D Brain Spheroids as a Predicative Model for RNAi
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Open to view video. "Evaluation of 3D Brain Spheroids as a Predicative Model for RNAi   Tuyen Nguyen, Alex Eaton, Adam Castoreno, Kirk Brown, Samantha Chigas, Haiyan Peng Alnylam Pharmaceuticals, Cambridge MA 02142  RNA interference (RNAi) is a process where double-strand RNA (dsRNA) inhibits the expression of a target gene by specifically degrading the complementary messenger RNA (mRNA). RNAi therapeutics are a new class of medicines that can address unmet medical needs across therapeutic areas including neurological disorders by silencing disease-causing genes. Drug development is a lengthy and expensive process ranging from target identification to lead discovery and optimization, preclinical validation, and clinical trials. A reliable predicative model in early stage can significantly accelerate the drug discovery process.  Currently, the majority of cell-based assays are being carried out in two-dimensions (2D) settings, lacking the complex tissue microenvironment.  To achieve biological relevance and improve in vivo translation to larger species, cell-based models need to better mimic the cellular architecture in organs, such as, three-dimensional (3D) cell culture models, which are more closely resemble in vivo cell environments. Here, we report the delivering of siRNA with various chemical modifications resulting in sustained and robust target mRNA knockdown in 3D brain spheroids and secreted target proteins in culture media.  In contrast, minimal siRNA activity was observed in 2D culture that consists of the same cells.  Importantly, data from co-culture 3D brain spheroids correlates strongly with efficacy data in non-human primate (NHP), suggesting the powerful translatability of the 3D brain spheroids model in CNS research."
Large-scale validation of AlphaLISA SureFire kits to enable target engagement quantification via high-throughput CETSA screening
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Open to view video. "Validating target engagement of compounds utilizing a high-throughput CETSA® approach can generate valuable leads, discover novel chemistry and drive SAR with the benefit that hits are on the endogenous target within a physiological environment. The development of high-throughput CETSA® assays can be expediated by employing ‘off-the-shelf’ AlphaLISA® SureFire® Ultra kits for detection in a 384-well assay format. Previously, setting up optimal assay conditions for these kits has been limited to single or few targets. This study was conceived to tackle a large-scale kit validation approach, allowing for rapid assessment of many targets investigating whether the proteins are detectable, meltable and shiftable using commercially available tool molecules. The resultant findings allow for a wide overview of which target classes, proteins and tools are amenable ‘off the shelf’ for target engagement assessment. We first set out to determine the optimal cell type(s) in which most targets are expressed. Therefore, all targets were cross-referenced with their expression levels in all available cell lines of the Human Protein Atlas. This resulted in the selection of two cell types, THP1 and U2OS cells, and 46 intracellular proteins to be examined in both cell types in six-point temperature melting curves. The selected proteins belong to diverse classes and are localized in different cellular compartments. 41 proteins demonstrated good detectability and qualified for full twelve-point temperature melt curves in a single cell line. Having pinpointed the optimal melting range, the proteins were examined for their ability to shift upon target engagement with up to three commercially available tool compounds. A thermal shift was observed for most targets using standard conditions, and a few selected examples were further followed-up with lysate experiments and thermal proteome profiling. In summary, we demonstrate an approach that allows for rapid validation of large batches of AlphaLISA® SureFire® kits to test individual proteins for their ability to be detected, melted and shifted in high-throughput CETSA®. Further, the newly validated kits were employed to focus on a few selected proteins illustrating the effects of compounds on pathways, and follow-up of selected compounds via thermal proteome profiling."
Plexium’s DELPhe platform expedites targeted protein degradation drug discovery
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Open to view video. "Targeted protein degradation using the endogenous Ubiquitin Proteasome System (UPS) represents a fundamentally new approach to drug discovery that potentially allows proteins that cannot be modulated by conventional small molecule inhibitors to be brought under therapeutic control. This provides the opportunity to develop therapeutics for traditionally undruggable targets including scaffolding proteins, protein-protein interactions and transcription factors. Traditional medicinal chemistry approaches have not been transferrable to drugging protein-protein interactions; consequently, prospective design of compounds to induce degradation is not well precedented, and to date has relied on empiricism and serendipity. Plexium has developed the DELPhe platform, which combines solid phase synthesis of DNA encoded libraries with high-throughput ultra-miniaturized cell-based assays, to screen large amounts of chemical space to identify monovalent or molecular glue degraders. Targeted libraries of drug-like molecules are created for each protein target or E3 ligase and are then assayed for their ability to cause degradation in intact cells. The DELPhe platform incorporates flexible readouts for identification of small molecule degraders by monitoring the loss of protein expression through immunofluorescence staining or through the generation of unique RNAseq signatures. We describe here the use of Plexium’s DELPhe platform to sample extensive chemical space and discover small molecule monovalent degraders that demonstrate selective and sustained degradation of BRD4. Validation of screening hits identified monovalent degraders with rapid and potent degradation of BRD4 without any appreciable degradation of the highly homologous BRD2 and BRD3 proteins. Co-treatment with either proteosome or neddylation inhibitors blocked BRD4 degradation, demonstrating that loss of BRD4 protein was mediated by the ubiquitin proteosome system. Validated hits were further characterized in a ubiquitin ligase-focused CRISPR screen to identify the E3 ligase complex responsible for degradation. Collectively, these data demonstrate that Plexium’s DELPhe platform enables the rapid discovery of selective and potent monovalent degraders of BRD4."
Rational molecular glue discovery as new frontier in targeted protein degradation
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Open to view video. Recently, targeted protein degradation (TPD) has shown its potential to be a powerful approach in identifying novel therapeutics. With at least 15 clinical programs by end of 2021 and more than 400 preclinical assets, TPD is fundamentally changing the landscape of drug discovery industry. While heterobifunctional molecules represent the largest class of small molecule degraders under preclinical and clinical evaluation, monovalent degraders, also known as “molecular glues”, offer significant advantages, including lower molecular weight, better physicochemical properties, and a much broader target space regardless of ligand availability. Current molecular glue discovery is limited to a few E3 ligases and phenotypic screen. The exciting new opportunity in TPD is to rationally discover novel molecular glues that can induce proximity between any target and a ubiquitin ligase of choice. I would like to discuss new technologies that can potentially enable rationale molecular glue discovery, including advancement of novel computational tools and next generation DNA-encoded compound libraries.
Robust neo-substrate ubiquitylation by Cullin-RING ligases depends on the identity of the ubiquitin-carrying enzyme
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Open to view video. The cullin-RING ligases (CRLs) are the largest family of ubiquitin ligases in humans and are currently being used as vehicles for proteolysis-targeting chimeric drugs (PROTACs) that hold great promise to target and degrade disease-causing proteins. Despite the justifiable exuberance for this novel area of drug discovery, it is fair to say that CRLs are exceptionally complex enzymes and that several key aspects regarding their mechanism of action still await elucidation. For instance, the enzymes that collaborate with CRLs by bringing activated ubiquitin to the CRL-substrate complex, referred to here as ubiquitin-carrying enzymes, are numerous and appear to display distinct biochemical activities that depend on factors such as the identity of the CRL, the substrate receptor module, and even the substrate itself. I will present unpublished results demonstrating that the human CRL enzyme system displays exquisite specificity with neo-substrates targeted to cullin-RING ligases by PROTAC-based drugs. These results will be pertinent to ongoing therapeutic approaches that employ induced proximity-based protein degradation.
Site-specific Dolasynthen ADCs: A platform to generate a wide range of drug-to-antibody ratios and maintain consistent exposure
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Open to view video. "Key defining attributes of an antibody-drug conjugate (ADC) include the choice of targeting antibody, linker, and the drug-to-antibody ratio (DAR). The choice of DAR, within the constraints of acceptable physicochemical properties for the given platform, is a function of balancing delivery of sufficient payload to targeted cells with the ability to achieve sustained in vivo exposures. Previous reports have described lower DAR mc-VC-MMAE conjugates, DAR = 1-2, that demonstrated higher in vivo exposure and lower clearance when compared to higher DAR (e.g. 4-8) counterparts. In theory, high DAR conjugates may be especially desirable when targeting low antigen expressing tumors or when lower potency payloads are used, as each binding and internalization event results in greater payload delivery. Here we report a systematic exploration of DAR across a much wider range than has been previously reported, by combining THIOMAB® protein engineering technology with the Dolasynthen platform. Homogeneous, site-specific ADCs spanning a discrete range of DARs – 2, 4, 6, 12, and 18 – were made by conjugation of Trastuzumab IgG1 THIOMAB® constructs with 1, 2, or 3 engineered cysteines to monomeric or trimeric Dolasynthen. The cytotoxicity of the resulting well-defined ADCs was assessed in vitro in cell lines with high or low expression of HER2 antigen. Pharmacokinetic data for all test articles in mice were generated in tumor bearing mice.  In high HER2 expressing cell lines, in vitro cytotoxicity by payload was comparable across DARs. In a lower HER2 expressing system, the higher DAR ADCs performed better. In vivo, our data demonstrated comparable pharmacokinetics for the Dolasynthen conjugates across all DARs. These results illustrate the utility of a DAR ranging platform, such as Dolasynthen when evaluating ADCs as it enables the interrogation of a range of antibody and payload dosing regimens."
Small Molecule Drugs Targeting RNA splicing
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Open to view video. The emergence of splicing modulation with anti-sense oligonucleotides (ASO) and more recently small molecules, has opened up many opportunities to target gene products that were previously thought to be undruggable.  Furthermore, small molecule splicing modulators for neurodegenerative diseases provide the potential advantages of greater distribution, non-invasive delivery methods and higher patient accessibility compared to ASOs. The development of small molecules that modulate the splicing process of primary RNA is discussed with examples from SMN2 splicing modulators for spinal muscular atrophy (SMA) and huntingtin (Htt) splicing modulators for Huntington's disease. In particular, the origins of the chemical starting points and screening cascade will be presented. 
Transitioning from Drug Screening to Drug Design for Next Generation Antibody Drug Conjugates
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Open to view video. Antibody drug conjugates (ADCs) are coming of age with the approval of six new drugs in the past three years. These therapeutics combine a potent small molecule payload, often a cytotoxic drug, with a tumor antigen targeting monoclonal antibody paired through a chemical linker. However, the gains in this field have been hard won following a significant investment and many initial failures in the clinic. The increased complexity of ADCs compared to small molecule drugs or biologics makes them challenging to develop, and previous methods of drug screening and down-selecting candidates along the pipeline don’t work well for ADCs. The tumor delivery challenges of large molecules can limit the tumor uptake and distribution of ADCs in vivo, and toxicity from the small molecule can limit tolerability. Therefore, the most potent compounds in vitro may be too toxic for efficacy in vivo. Similarly, the antibody cross-reactivity and payload tolerability in animals is different than humans, meaning preclinical results may not adequately capture the clinical therapeutic window. All this results in traditional development pipelines selecting for drugs that may lack a therapeutic window, leading to many failures in the field. Even worse, this approach can screen out compounds that may be clinically effective but don’t perform well in preclinical assays. However, by combining experimental data with computational simulations of drug distribution, the clinical efficacy at tolerable dose can be predicted to identify promising ADC designs. These include selecting the right payload potency, linker type, drug to antibody ratio (DAR), and internalization rate for a given target. The success of these designs is illustrated with currently approved ADCs for solid tumors. In particular, we highlight how the physicochemical properties of the released payload determine its ability to reach all cells within a tumor, including antigen-negative cells that can escape targeting by the ADC. The significant investment in ADC development over the past two decades has generated an enormous number of useful tools for constructing ADCs. By utilizing this knowledge in computational ADC drug design, we can assemble the next generation of ADCs tailored to a particular target to increase the rate of clinical success.
Emergent cellular ecosystems in melanoma revealed by single cell analysis
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Open to view video. Anti-cancer therapies can often kill the vast majority of tumor cells but a few rare cells remain and grow despite treatment. Non-genetic variability has emerged as a potential contributor to this behavior. However, it remains unclear what drives this variability, and what the ultimate phenotypic consequences are. We have developed a set of new single cell barcoding technologies (Rewind and FateMap) that have enabled us to show how different types of variability can translate into different drug-resistant outcomes upon treatment with drug. In particular, we found that even a genetically and epigenetically clonal population harbors enough latent variability to produce an entire ecosystem of different resistant cell types, and show preliminary evidence suggesting that these cell types can contribute to tumor development in distinct ways.
Exploring the physical genome in health and disease
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Open to view video. Congenital heart defects, the most common birth defects, are the clinical manifestation of anomalies in fetal heart development - a complex process involving dynamic spatiotemporal coordination among various precursor cell lineages. This complexity underlies the incomplete understanding of the genetic architecture of congenital heart disease (CHD). To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human embryonic heart tissues. These data identified eight major differentiation trajectories involving primary cardiac cell types, each associated with an array of continuous transcription factor (TF) activity signatures. This atlas allowed molecular comparison of the regulatory similarities and differences between iPSC-derived cardiac cell types with their in vivo counterparts. We interpreted deep learning models that predict cell-type resolved, base-resolution chromatin accessibility profiles from DNA sequence to decipher underlying transcription factor motif syntax and infer the regulatory impact of noncoding variants observed in CHD trios. De novo mutations predicted to affect chromatin accessibility in arterial endothelial clusters were significantly enriched in CHD cases vs controls with 1.7-fold enrichment. We used CRISPR perturbations to validate three of the enhancers harboring nominated regulatory mutations from these models, linking them to effects on the expression of JARID2, NFATC1, and TFAP2A. Together, this work defines the cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements as a component of the genetic etiology of CHD.
Interpreting microbiome health effects in the context of longitudinal multi-omic data
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Open to view video. Healthcare in the 21st century will need to become increasingly focused on wellness as a key strategy for dealing with the chronic diseases that account for 86% of healthcare costs in the US. To enable the precision health strategies of the future — what we call ’scientific wellness’ — it is necessary to generate large amounts of data on healthy people to quantify wellness states and to observe the earliest transitions to disease in order to enable predictive and preventive medicine. In this talk, I will discuss how such 'deep phenotyping’ data has been used in particular to study health effects of the microbiome, including: (1) to inform about how our gut microbiome and blood metabolites are related; (2) how the gut microbiome becomes more unique to each individual in healthy aging (3) insights from microbiome analysis and technical advancement through ongoing efforts at Thorne HealthTech.
Multi-Domain Data Integration in the Light of Drug Repurposing for SARS-CoV-2
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Open to view video. Massive data collection holds the promise of a better understanding of complex phenomena and ultimately, of better decisions. An exciting opportunity in this regard stems from the growing availability of perturbation / intervention data (drugs, knockouts, overexpression, etc.) in biology. In order to obtain mechanistic insights from such data, a major challenge is the integration of different data modalities (transcriptomic, proteomic, structural, etc.). I will first discuss our recent work on coupling autoencoders to integrate and translate between data of very different modalities such as sequencing and imaging. I will then present a framework for integrating observational and interventional data for causal structure discovery and characterize the causal relationships that are identifiable from such data. We end by demonstrating how these ideas can be applied for drug repurposing in the current SARS-CoV-2 crisis.
Precision Health Through Multi-scale and Multi-Modal Biomedical Data Integration
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Open to view video. Recent technological advancements make it possible to closely and continuously monitor individuals on multiple scales in real time while also incorporating genetic, environmental, and lifestyle information. We are collecting and using this multi-scale biomedical data to gain a more precise understanding of health and disease at molecular and physiological levels and developing actionable, predictive health models for improving infectious disease and cardiometabolic outcomes. We are simultaneously developing tools for the digital health community, including the Digital Biomarker Discovery Pipeline (DBDP), to facilitate the use of mobile device data in healthcare.
Profiling chromatin associated oncoproteins in heterogeneous tumor samples
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Open to view video. " Single cell genomic technologies have been extremely useful to understand how differences in the mutational landscapes (genetic heterogeneity) as well as the metabolic, cell signaling and gene regulatory states (non-genetic heterogeneity) of tumor cells can result in different responses to therapeutic intervention. Many recurring oncogenic mutations are found in genes that encode chromatin regulatory proteins. In this talk, I will discuss how the CUT&RUN and CUT&Tag chromatin profiling methods can be used to examine chromatin associated oncoproteins and the regulation of non-genetic tumor heterogeneity.             Chromosomal translocations that produce in-frame fusion proteins involving the chromatin modifying enzyme Lysine Methyl-Transferase 2A (KMT2A; also referred to as Mixed Lineage Leukemia-1) are found in approximately 10% of new acute leukemia cases each year. Despite bearing related mutations, KMT2A-rearranged (KMT2Ar) leukemias are extremely heterogeneous and can present as pro-B-cell acute lymphoblastic leukemia (B-ALL) acute myeloid leukemia (AML) and mixed phenotype acute leukemia. In addition, high-risk KMT2Ar leukemia subtypes are associated with an unusual degree of lineage plasticity, and occasionally undergo a B-ALL-to-AML phenotypic shift to evade targeted therapies. We used automated CUT&RUN and CUT&Tag in combination with single-cell CUT&Tag to characterize the chromatin landscapes of a diverse panel of KMT2Ar leukemia cell lines and patient samples. We identified a subset of KMT2A oncoprotein binding sites that are marked by both the active chromatin modification H3K4me3 as well as repressive chromatin modification H3K27me3. Strikingly, we identified groups of oncoprotein target genes that show divergent patterns of active and repressive chromatin in the same leukemia, suggesting the KMT2A oncoproteins contribute to lineage plasticity by activating multiple different oncogenic networks. Recently, several multi-modal single cell CUT&Tag methods have been developed in the lab, and I will also discuss novel applications of these single cell datatypes. "
Single-cell RNA-seq coupled with clonal analysis reveals systemic T cell characteristics in melanoma
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Open to view video. The introduction of single-cell high-throughput measurement technologies (such as single-cell RNA-seq) have recently transformed the breadth and depth at which the immune component can be characterized and studied. Excitingly, the recent ability to generate coupled RNA-seq and TCR / BCR data at single-cell resolution and at high-throughput (using 10X technology) has enabled exploring relationships between cellular states and clonal distributions within and across tissues. In this talk we will discuss systemic aspects of T cell immunology during cancer or autoimmune disease, as they are revealed with coupled single-cell RNA-seq and TCR annotation. We will present a study in which we assess the extent to which peripheral blood can be used for tracking a host response to tumor by characterization of the CD8+ T cell tumor-directed component in blood. Additionally, we will discuss annotation of the transcriptional and clonal characteristics and function of Th17 cells throughout multiple mouse organs in autoimmune disease, as well as validation in follow-up experiments in the lab.
Exploring Immune Cell Infiltration of CNS Malignancies with scRNA-seq and Digital Spatial Profiling
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Open to view video. One current aspect of research in pediatric brain tumors involves the investigation of changes in the infiltration of immune cells into the tumor microenvironment during progression.  This interest reflects the results of studies from adult GBM, illustrating that macrophage infiltration sets up an immunosuppressive environment.  As such, information obtained from these studies of the tumor immune microenvironment may yield insights into the development of new immunotherapy-based treatments or the use of existing immunotherapies.  Our lab has focused on the use of technologies to decipher changes in the immune microenvironment of pediatric CNS tumors, including single cell or single nucleus RNA sequencing of CD45-sorted cell fractions, coupled with digital spatial profiling (DSP) evaluation of the immune cell components as identified by CD45 fluorescent antibody stained regions using the Nanostring GeoMX platform.  My lecture will focus on the technical details of these platforms and our results, including exploring the concordance across platforms and the synergies therein.  
Big Data, Health and COVID-19
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Open to view video. Recent technological advances as well as longitudinal monitoring not only have the potential to improve the treatment of disease (Precision Medicine) but also empower people to stay healthy (Precision Health). We have been using advanced multiomics technologies (genomics, immunomics, transcriptomics, proteomics, metabolomics, microbiomics) as well as wearables for monitoring health in 109 individuals for up to 11 years and made numerous major health discoveries covering cardiovascular disease, oncology, metabolic health and infectious disease. We have found that individuals have distinct aging patterns that can be measured in an actionable period of time as well as seasonal patterns of health markers. Finally, we have used wearable devices for early detection of infectious disease, including COVID-19 and built an alerting system for detecting health stressors that is scalable to the entire planet. We believe that advanced technologies have the potential to transform healthcare
Precision Medicine and Diagnostics
Clinical Utility of Functional Precision Medicine in the Management of Relapsed/Refractory Childhood Cancers
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Open to view video. Pediatric cancers are fundamentally different from those in adults, with a lower frequency of genetic mutations and fewer options for targeted therapies. The implementation of functional precision medicine (FPM) – the integration of ex vivo drug screening and mutation profiling- can, therefore, provide better treatment options for pediatric tumor patients. In this study, we investigated the feasibility and clinical utility of FPM in the management of pediatric patients with recurrent and/or refractory cancers. We use a functional ex vivo drug screening test (DST) panel encompassed 40 formulary drugs frequently used at Nicklaus Children’s hospital and 47 non-formulary drugs approved by FDA for cancer treatment, as well as drugs from phase III and IV clinical trials. Drug sensitivity scores (DSS) were calculated for each drug based on cancer cells’ responses. DST results were then combined with results from targeted mutation profiles to match actionable mutations with selective targeted therapies. We have recruited a total of 21 patients into this ongoing clinical trial (number NCT03860376) and were able to perform drug testing and mutation profiling on 17 patients. We optimized and successfully performed DST on at least 13 different tumor types including acute myeloid leukemia, chronic lymphoblastic leukemia, ependymoma, osteosarcoma, Ewing’s sarcoma, rhabdomyosarcoma, glioblastoma, medulloblastoma, astrocytoma, neuroblastoma, rhabdoid, lung, and liver. Our feasibility study, so far, has demonstrated that ex vivo DST can be performed within a clinically actionable time frame (median: 7 days). Ex vivo DST returned between 10 and 30 treatment options for each patient. These patients showed different responses to the 103 FDA-approved compounds used on the screen. More than half of the evaluated compounds were not active in any of the patients. Remarkably, DST provided valuable information to the oncologists on drug dosing and treatments that may not be effective and should be avoided. DSS synergizes with genomic data to further refine treatment recommendations. FPM-guided treatment regimens resulted in encouraging partial and complete responses as compared to progressive disease in prior regimens and physician choice regimens. Thus, our study shows the technical feasibility of integrating functional precision medicine approaches for patients with refractory/relapsed pediatric cancers. Routine clinical integration of FPM for treatment selection is technically feasible and led to improved treatment of pediatric cancer patients with refractory malignancies in an initial patient cohort, warranting further investigation.
Next-generation tumor organoids to recapitulate complex biological systems for screening applications
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Open to view video. "There is increasing interest in leveraging patient-derived tumor organoids for high-throughput drug screenings aimed at investigating tumor biology as well as identifying personalized medicine solutions. Tumor organoids recapitulate many features of the cancer they are derived from and are considered accurate preclinical models to rapidly mirror a patient’s drug response. We have developed a fully optimized high-throughput screening approach to test the response of tumor organoids to hundreds of therapeutic agents, with results available within a week from surgery (Phan et al, 2019; Nguyen and Soragni, 2020; Al Shihabi et al, 2021). Here we show how our platform can be effectively used to investigate drug susceptibilities, tumor heterogeneity and evolution in rare cancers and sarcomas in particular. In addition, we will discuss bioprinting implementations for automated organoid seeding and multi-organ co-culture models that further expand the applicability of the pipeline."
Multi-regional Micro-sampling Reveals Extensive Intratumor Proteomic Heterogeneity - Scientific & Clinical Implications
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Open to view video. This lecture will highlight cutting edge applications in applying laser microdissection and microscaled quantitative proteomics to uncover exquisite intra- and inter-tumor heterogeneity. These paradigm-shifting results offer unprecedented opportunities to speed progress in identifying novel molecular sub-types of cancer, therapeutic targets, prognostic signatures, and companion diagnostics.
Patient in the Lab®: Downscaling Patient Derived Organoid screening
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Open to view video. "Adult epithelial stem cell-derived organoids (Sato et al. Nature 2009, 2011), or HUB Organoids™, are proving to be a major breakthrough in preclinical modelling of human diseases. These patient-derived models fundamentally change the way drug discovery and development can be performed as they can be used as patient avatars in the lab to test multiple treatments in parallel and determine which treatment would benefit a patient the most. Multiple publications have shown that the pharmacological response of patient-derived organoids (PDOs) in vitro correlates with clinical response (Vlachogiannis et al. Science 2018, Yao et al. Cell 2020). However, these correlations are based on small cohorts of models and lacks the statistical strength needed to ensure acceptance of organoids as clinical diagnostic tools by governing agencies. Additionally, a faster workflow from initial patient diagnosis and biopsy to diagnostic test result is still required to maximize the benefits from PDOs and achieve the best clinical outcome. HUB is collaborating with Yamaha Motor to overcome these challenges and improve the overall diagnostic process for patient benefit. This collaboration aims at demonstrating a correlation of treatment response between HUB Organoids in the lab and patients in the clinic using a larger cohort of models. Additionally, the Yamaha CELL HANDLER™ will be validated as a tool to automize and improve the accuracy of the pick-and-place process of organoids, resulting in faster timelines and an overall saving in reagents usage. Together, the personalized approach offered by HUB Organoid Technology combined with improved operational efficiency by the Yamaha CELL HANDLER will enable accurate and fast prediction of treatment response to improve clinical outcome."
Beyond Genomics: Protein Drug Target Activation Mapping to Change the Paradigm in Precision Medicine Based Cancer Therapy
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Open to view video. " Genomic analysis of cancer has revealed the tremendous heterogeneity of cancer at the individual level, and that ultimately cancer is a protein pathway disease at the functional level. However, since genomic and transcript profiling likely cannot alone sufficiently predict protein pathway activation in each patient’s tumor, and it is these signaling pathways that represent the targets for current and new molecular guided therapeutics, it is critical that we begin to define and treat human cancer at a functional protein pathway activation level. Indeed, systems biology type approaches that use proteomic, transcriptomic, and DNA mutational analysis concomitantly may hold the key for effective therapy. Post-translational modification such as phosphorylation drive and underpin nearly all cell signaling processes that are aberrantly activated in cancer and therapeutic resistance, and are epigenetic events that are not predictable using genomic approaches alone. In fact, cancer, as a model for human disease, is a manifestation of deranged cellular protein molecular networks and cell signaling pathways that are underpinned by genetic changes. These pathways contain a large and growing collection drug targets, governing cellular survival, proliferation, invasion and cell death. The reverse phase protein microarray (RPPA) technology, when coupled to laser capture microdissection (LCM) is now being routinely utilized to generate a functional map of known cell signaling networks or pathways for an individual patient obtained directly from a biopsy specimen.  From a single biopsy specimen, the activation or “in use” state of over 200 protein drug targets can be quantitatively measured at once, providing unprecedented opportunity to measure the direct targets of nearly every FDA cleared and experimental targeted inhibitor at once from just a small piece of a single biopsy sample. The LCM-RPPA technology platform is now available as an automated commercial CLIA LDT assay that has now been launched as the Theralink Assay™, which measures a targeted panel of 32 proteins and phosphoproteins and is delivered in a 14 day turn-around-time from FFPE material.  This patient-specific pathway activation map provide key information that identifies actionable targets for individualized or combinatorial therapy through the quantification of phosphorylation states of proteins. In addition to the commercial CLIA LDT assay, protein pathway activation mapping via the LCM-RPPA platform is being implemented in a number of ongoing precision oncology trials and as a key component of therapy decision making and CDx development.
Molecular Profiling of Advanced Malignancies Guides First-line N-of-1 Treatments in the I-PREDICT Treatment-Naïve Study
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Open to view video. "Background: Malignancies are molecularly complex and become more resistant with each line of therapy. We hypothesized that offering matched, individualized combination therapies to patients with treatment-naïve, advanced cancers would be feasible and efficacious. Patients with newly diagnosed unresectable/metastatic, poor-prognosis cancers were enrolled in a cross-institutional prospective study. Methods: A total of 145 patients were included in the study. Genomic profiling (tissue and/or circulating tumor DNA) was performed in all patients, and PD-L1 immunohistochemistry, tumor mutational burden and microsatellite status assessment were performed in a subset of patients. We evaluated safety and outcomes: disease-control rate (stable disease for ≥6 months or partial or complete response), progression-free survival (PFS), and overall survival. (OS). Results: Seventy-six of 145 patients (52%) were treated, most commonly for non-colorectal gastrointestinal cancers, carcinomas of unknown primary, and hepatobiliary malignancies (53% women; median age, 63 years). The median number of deleterious genomic alterations per patient was 5 (range, 0–15). Fifty-four treated patients (71%) received ≥1 molecularly matched therapy, demonstrating the feasibility of administering molecularly matched therapy. The Matching Score, which reflects the percentage of targeted alterations, correlated linearly with progression-free survival (R2=0.92; P=0.01), and high (≥60%) Matching Score was an independent predictor of improved disease control rate [OR 3.31 (95%CI 1.01–10.83), P=0.048], PFS [HR 0.55 (0.28–1.07), P=0.08] and OS [HR 0.42 (0.21–0.85), P=0.02]. Serious adverse event rates were similar in the unmatched and matched groups. Conclusions: Personalized combination therapies targeting a majority of a patient’s molecular alterations have antitumor activity as first-line treatment. These findings underscore the feasibility and importance of using tailored N-of-1 combination therapies early in the course of lethal malignancies."
Understanding drug-drug interactions: how to use ex vivo drug sensitivity screening to improve cancer treatment
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Open to view video. "Cancer is a heterogeneous group of diseases characterized by the uncontrolled and abnormal growth of cells. Cancer is heterogeneous in its genetics, its response and adaptation to the environment, in its metabolic rewirement to adapt to this environment and in its interaction with the immune system.  It is often considered that each tumor in each patient, and even different tumors within the same patient are unique. As an example of a very heterogeneous cancer type, we have melanoma of the skin, classified in four genomic subtypes depending on the mutational state of BRAF, NRAS, and NF1, all of them contributing to deregulation of the MAPK/ERK pathway, leading to uncontrolled cell growth. This cancer heterogeneity is a problem for treatment-decision making. The future of cancer treatment is in precision medicine, or moving from a scenario where patients get the same standard treatment to other where they get a treatment adapted to their individual characteristics. But this is not the only problem. Most of cancer deaths are due to development of treatment resistance, and this resistance development is associated with tumor heterogeneity and cancer´s evolution capability. During cancer development and due to its heterogeneity, there will be different subclones inside a tumor. These subclones can show different sensitivities to cancer treatment, which creates a selective pressure for the resistant clones, causing treatment resistance development, tumor progression and patient relapse. In order to overcome resistance, we need to block cancer’s evolutionary escape routes using treatment combinations that target multiple oncogenic pathways at once.  In our study we are focused in understanding the drug combination effects when treating cancer. We have set up a system to screen large amounts of drug combinations in a high-throughput format using ex-vivo drug sensitivity screening. We have analyzed the response of 22 well characterized melanoma cell lines to the effect of 61 drugs that target major cancer pathways and their pair wise drug combinations. We have identified synergistic and antagonistic drug combinations for each of the cell lines. But more importantly, we have crossed the results with information of the expression patterns and mutational profile for all the cell lines, identifying biomarkers that predict drug combination and treatment efficacy. After validation of these biomarkers in-vivo we expect to implement new drug combinations to be used in clinic, that will improve the treatment of cancer patients. Our long-term goal is to identify personalized synergistic drug combinations for each patient that comes to our clinic."
This is the Organoid you are looking for: Leveraging automation in organoid research at Cincinnati Children’s Center for Stem Cell and Organoid Medicine (CuSTOM)
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Open to view video. "Cincinnati Children’s Hospital Medical Center (CCHMC) has a long and successful history of innovative research and development in pediatric diseases. The emerging field of organoids has presented CCHMC it next focus for innovation. Organoids are increasingly used in applications involving drug discovery and development, predictive diagnosis and organoids-based therapies. Advancements in stem cell methods and technology now allow researchers to use organoids to quickly identify potential drug candidates through a ‘Quick win, fast fail’ approach to be used for the treatment of childhood disease. Lowering drug discovery costs associated with these candidates can result in significant time and cost savings. CCHMC and its Center for Stem Cell and Organoid Medicine (CuSTOM) develops, manufactures and delivers stem cell and organoids-based research tools applications and therapies that will improve child health. High content screening and workcell automation are viewed as vital to CCHMC’s work, as they fulfill a need to standardize experimental techniques, provide scalability to ongoing research and permit CGMP production practices required by the US FDA. This talk discusses the life-saving benefits of automation through tangible, peer-reviewed results including the creation of a patient-derived Individual pluripotent stem cell line library, prediction of drug safety using liver organoids, human organoid-based clinical trials and organoid-based predictive diagnostics. New areas of development made possible by the addition of automation include fully-automated organoid screening workflows and the ability to grow and image 3D organoids from single cell suspensions. Through current initiatives and future collaborations, CCHMC looks to drive the field of Organoid and Regenerative Medicine forward not only to benefit pediatrics but the population at large.
Intestinal organoids for cystic fibrosis drug development
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Open to view video. Patient-derived cells can be used for disease modeling to study preclinical and clinical interventions and variation thereof in the human population. Here, we explore the ability of a 3D intestinal organoid model to study individual disease and treatment of cystic fibrosis, a monogenic, recessive disease caused by CFTR mutations. The 3D organoid structure enables rapid measurement of CFTR function in vitro, and provides a drug testing platform that links the preclinical and clinical domains of drug development. We demonstrate the standardization of the CFTR organoid assay across laboratories, the collection of >500 organoid samples from >40 different clinical sites across Europe and the screening of potential drug responders in these >500 samples to enable clinical trial design. Together, it shows how living cell technologies can be engineered for improvement of drug development pipelines in rare genetic diseases.
Modeling Colon Cancer Drug Resistance and Stemness with Tumor Spheroids
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Open to view video. Modeling Colon Cancer Drug Resistance and Stemness with Tumor Spheroids Astha Lamichhane, Pouria Rafsanjani Nejad, Jacob Heiss, Hossein Tavana Department of Biomedical Engineering, The University of Akron, Ohio 44325, United States Despite targeted therapies of 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 improve outcomes for patients. Using our aqueous two-phase system microtechnology, we robotically microprinted tumor spheroids of KRASmut and BRAFmut colon cancer cells. To mimic how patients receive chemotherapy, we cyclically treated the spheroids in a four-week regimen with MEK inhibitors (MEKi) due to the constitutive activity of MAPK/MEK pathway in the cells. Despite an initial response to the MEKi during the first treatment round, cancer cells developed resistance during subsequent cycles and gained proliferative activities. Our molecular analysis showed activation of several oncogenic pathways such as PI3K/AKT, JAK/STAT, and WNT/β-catenin in cancer cells under cyclic treatment regimen. Additionally, we investigated whether cells displayed cancer stem cells (CSCs) and epithelial-to-mesenchymal transition (EMT) phenotypes that are associated with cancer drug resistance. We found significant upregulation of several CSC gene markers including ALDH1A3, CD166, and CD133, and enhanced clone forming capacity of the MEKi-resistant cells. Treatments with different MEKi also significantly upregulated EMT markers including ZEB1 and E47 and promoted invasion of cancer cells from spheroids into a human collagen matrix. Next, we examined different therapeutic strategies against adaptive resistance of cancer cells to MEKi. First, we selected drug combinations based on activation of oncogenic pathways. Despite strong anti-proliferative effects of combinations of (1) MEK/ERK and PI3K/AKT inhibitors, (2) MEK/ERK and JAK/STAT inhibitors, and (3) MEK/ERK and WNT/β-catenin inhibitors, they were ineffective against CSCs and invasiveness of cancer cells. Thus, we hypothesized that direct targeting of CSCs was critical and found that a combination of MEK/ERK and CSC inhibitors to successfully downregulate the CSC and invasive phenotypes of cancer cells. Overall, our approach to use a 3D tumor model and perform high throughput screening of drug combinations that block compensatory signaling and CSC and EMT phenotypes will facilitate treatment selections for validation in animal models and progress to clinical trials.
WomXn and the Path to Computer Science
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Open to view video. There is a gender gap that exists in the Computer Sciences field, and that gap has grown significantly in the last few decades. Join us for a panel discussion to explore this trend in computer science and determine ways to address the gender gap head-on. Our panel includes two entrepreneurial women who have started software development companies in the life science and diagnostic markets and an up-and-coming computer scientist currently in high school. We will pose questions to gain insights on what influenced their career paths, who were their sources of encouragement and mentorship in their selected fields of study, and how they are giving back to help change the future for women in the computer sciences field.
Startup 101
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Funding Trends in Life Sciences
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Open to view video. Presentation about the funding trends in Life Sciences from an early-stage European point of view.
Ignite Award Finalist Presentations
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Open to view video. Ignite Award Finalist - BennuBio The global 3D cell culture market is rapidly increasing the use of 3D tissue and tumor models, called spheroids or organoids. These 3D co-cultures better replicate drug effects in vivo by mimicking natural extracellular matrix, cellular physiology, cell-cell interactions, and drug transport limitations. Widespread use of spheroids as a drug screening system has been impeded by the lack of techniques for rapidly analyzing the response of this system to drug exposure. Current systems rely on microscopic analysis of single spheroids held in stationary culture (e.g., on top of, or embedded in agar). Not only is this microscopy process slow (~1 spheroid analyzed per second in the fastest automated systems) but maintaining spheroids in a stationary culture produces large and irreproducible gradients, as well as inconsistent and time-varying drug concentrations in and around the spheroids. Flow cytometry has long been the standard for many forms of cellular analysis. However, traditional flow cytometers contain a single particle stream with an analysis rate of 50,000 events per second; large particle analysis, rare cell event monitoring, and large volume analysis is either time-consuming or impossible. BennuBio Inc. has developed a transformational analytical system, the Velocyt®, that addresses the challenges of flow cytometry by delivering technology that can analyze samples regardless of particle size or sample volume. The Velocyt has a unique flow cell design, which enables large particles to be analyzed. Currently, particles up to 300 µm in diameter can be processed. While outstanding for assessing single cells, most traditional cytometers are unable to analyze particles greater than 40 µm and are limited to measuring 50,000 cells (events) per second. The Velocyt operates at speeds up to 100x faster than traditional flow cytometry, due to multiple, parallel flow streams, versus traditional, single stream. Particles are aligned by acoustic standing waves instead of sheath fluid; lack of sheath fluid coupled with our patented fluidics path means samples are processed and can be returned for downstream analysis unaltered and undiluted. In addition, the Velocyt® has a patented optics path that is robust and simple. This makes the Velocyt® a reliable instrument that is very user-friendly. By developing the Velocyt, researchers will now be able to accelerate their studies by having a multi-parametric, high-throughput analyzer for their spheroid and organoid analysis. The Velocyt® system will also transform workflows; by culturing spheroids in 3D vs 2D environments, researchers can develop more robust models and analyze their results faster and with more consistency. With this new technology comes the opportunity for the discovery of new, efficient, and automated solutions to complete studies with precision and speed, accelerating the timeline from idea conception to patient treatment."" Ignite Award Finalist - Celldynamics ISRL In biomedical research, 3D cell cultures are steadily emerging as more realistic and predictive in vitro model that does not involve the use of animals. However, the large adoption of 3D cell models is still hampered by heterogeneity in culture protocols and the lack of suitable analytic technologies; as a consequence, the results in 3D can be controversial and difficult to interpret. CellDynamics works in this direction: the company develops a flow-based analytic technology, which characterizes 3D cellular models with quantitative biophysical measurements of size, weight, and mass density. Although few prototypical solutions have been presented for single-cell analysis, no similar technologies already exist for characterizing thick 3D models such as spheroids or organoids. The first product launched in the market in January 2021, called the W8 Physical Cytometer (, represents the only available technology for the biophysical characterization, physical-based sorting, and sterile recovery of sphere-like 3D cell cultures. The system innovatively combines flow-based sample manipulation with a gravimetric and image-based analysis to quantify biophysical observables at 99.9% precision and 99.0% accuracy. The homogeneity of 3D cell cultures, in terms of size, shape, and 3D architecture, can be difficult to achieve, and their generation is often time- and resource-consuming. Usually, when tracking spheroids' growth via imaging analyses, attention is focused on their size- and shape variation over time. However, this approach is not fully representative of 3D models, as spheroids undergo specific compaction processes over time, depending on factors such as cellular heterogeneity, growth environment, and pharmacological treatments. For this reason, the W8 Physical Cytometer empowers researchers with a quality control assay for 3D cell cultures, by gathering precise information on sample biophysics. These features are crucial to optimize protocol standardization and achieve homogeneous and reproducible samples. In addition, variations in mass density, weight, and volume are also connected to changes in the cell cycle, induced by external stimuli. Therefore, the measurement of these biophysical parameters represents a useful tool, both for disease modeling and drug testing. In this regard, the W8 Physical Cytometer provides a label-free, non-destructive assay to evaluate the in vitro efficacy of chemotherapeutics or cell-based therapies (immunotherapy) on 3D cell cultures, without compromising sample viability. Indeed, while weight loss and diameter shrinkage are coherently related to drug-induced apoptosis, mass density represents a valuable marker of the 3D sample’s impaired compactness linked to drug (or immune cells) penetration rate. After the analysis, the sorted and collected samples are prone to be re-plated and exploited for further downstream analysis. This represents a great advantage when compared to more invasive techniques such as super-resolution microscopy, flow cytometry, or immunohistochemistry, which are meant to be end-point assays. To conclude, CellDynamics’ approach shares common goals within the SLAS vision, as an enabling technologies manufacturer for drug discovery in many research fields. The W8 Physical Cytometer method is patent-pending, and three scientific papers are available in the attachments. Ignite Award Finalist - Celtarys Research In the drug discovery process gold standard techniques have relied on radioactivity for identifying and characterizing new drug candidates. In the last years, due to radioactivity stringent requirements, high costs and environmental concerns, fluorescence-based assays started to be used. However, fluorescent ligand employment has not been adopted widely due to the challenging chemical development process and the consequent lack of optimal fluorescent probes available for the majority of the therapeutical targets. Our technology allows to overcome this bottleneck making fluorescence-based techniques a real option in drug discovery. Celtarys Research has developed a highly versatile conjugation methodology for the efficient optimization of fluorescent probes for drug discovery. We can develop fluorescent ligands in a timely manner with optimal pharmacological and photophysical properties for any target with therapeutic interest outperforming radioligands and other available fluorescent probes, thus improving drug discovery. The relevant role of GPCRs in drug discovery led us to start applying our technology for these targets, developing fluorescent probes for different receptor families and applications. We have developed >20 GPCR fluorescent ligands for Adenosine, Serotonin, Dopamine and Cannabinoid receptors. Celtarys fluorescent probes have been validated in a variety of High Throughput Screening (HTS) assays, including HTRF-based assays, High Content Screening, Fluorescence Polarization, Flow Cytometry and Fluorescence Microscopy. Celtarys probes have been successfully used in transfected and native cells and its validation has been conducted both in house and in collaboration with distinct European research groups expert in the different HTS assays. The fluorescent probes obtained applying our technology are built upon a pharmacophore representative of the target, show high affinity (Ki < 100 nM) and selectivity and are engineered with ad-hoc spacers tuned to allow target recognition; moreover, their fluorophores are stable, guarantee the affinity for the target and display a variety of photo-physical properties meeting market demands. Further to our catalogue, our technology, together with our expertise in Medicinal Chemistry, Chemical Biology, Photophysical methods, Pharmacology and HTS, enables us to develop in a competitive manner and short time ( < 3 months) personalized fluorescent ligands with optimal pharmacological and photophysical properties for any target of interest. The application of our proprietary Lego-like conjugation approach to other important target families (e.g., Kinases and nuclear receptors) is currently in progress, thus validating the scope of Celtarys technology with novel tailored fluorescent probes. In summary, we have a solution to the present barriers that prevent an effective deployment of fluoresce-based techniques in drug discovery: our efficient and versatile semi-combinatorial conjugation strategy that enables the ad-hoc generation of optimal fluorescent ligands for diverse targets in a time and cost-effective manner. Celtarys technology emerges as a game-changing technology destined to revolutionize and accelerate fluorescence-based methods in drug discovery. At Celtarys Research we believe that our innovation fits within SLAS’s area of life science because we propose a technological advance that will help to improve the performance of the early phases of drug discovery, through the offer to the scientific community of innovative fluorescent ligands suitable for High Throughput Screening (HTS) assays, outperforming radioligands and other available fluorescent probes."" Ignite Award Finalist - Magnitude Biosciences Ltd Magnitude Biosciences is a specialist CRO that couples the world’s leading C. elegans expertise and unique automated imaging technology to help researchers accelerate drug discovery and toxicity testing. Co-founders Dr. David Weinkove and Dr. Chris Saunter from Durham University came up with the idea to bring together the power of the tiny nematode worm C. elegans and Dr. Saunter’s automated imaging expertise in 2018. Dr. David Weinkove has a wide breadth of experience in biological research and drug discovery research and recognised that C. elegans, for all its drug discovery potential in the areas of ageing, neurodegeneration and microbiome, was very under-utilised in industrial research. The benefits of these tiny worms as research tools were almost exclusively being realised by C. elegans academic labs and their limited network of academic and non-academic collaborators. In the first year of the company, we investigated these barriers as to why industry has not and could not yet tap into C. elegans as a research tool, and concluded that a big factor was that in order to get C. elegans research right, you had to both deeply understand the best practices and use cases for these worms (be a C. elegans expert) and also how they were to be applied to the research challenge at hand (be a customer problem expert and emphasise quality control, time management, efficiency, and other lab practices which would be expected of a tightly run industrial lab). There was also a scalability challenge concerning how manual C. elegans research is, which we address with our unique automated healthspan assays and automated imaging technology, which enables us to yield data endpoints far richer and more telling about health impact of compounds than traditional C. elegans manual lifespan assays, which are still the industry standard. You can see an example of our technology at work in this video: A big focus for SLAS is on raising awareness and facilitating the use of cutting-edge and transformative life science technologies and approaches. This value is at the heart of Magnitude Biosciences’ mission as a company -- to bring our unique C. elegans approach to all the drug discovery and biological R&D researchers who can benefit from it. Our customers consistently feedback that the data we have generated for them with our healthspan assays has enabled breakthroughs in their research, informed critical R&D decisions, and helped them secure their next round of investment for their drug discovery project. Our attachments include a list of customer testimonials that illustrate the value we bring to the life science industry, a PDF slide deck illustrating our data and approach, our eBook with practical tips for ageing drug discovery researchers, and a recent poster on our neurodegeneration research approach. We also attach some recently published thought leadership pieces on the impact we are having in microbiome and ageing research."" Ignite Award Finalist - Partillion Bioscience Partillion Bioscience is an early-stage life science company commercializing an award-winning innovation from UCLA that enables the democratization of advanced single-cell assays. Our nanovial products provide the revolutionary capability to rapidly isolate millions of individual cells into nanoliter compartments to perform sophisticated assays that can drive biological discovery at the single-cell level. Our unique reagent platform is compatible with existing instruments in customer’s labs, enabling rapid penetration of multi-billion dollar markets in the single-cell space. The foundational intellectual property was developed over five years of research at UCLA by Partillion’s co-founders and microfluidics experts Dr. Joseph de Rutte and Dr. Dino Di Carlo and received the prestigious Innovation Award from the Society for Laboratory Automation and Screening (SLAS) in early 2020. Partillion’s unique single-cell reagent platform leverages cavity-containing hydrogel particles or “nanovials”, that hold single cells in sub-nanoliter volumes of fluid, 100,000 times less volume than a single well of a 1536-well microwell plate. Fluids are easily exchanged in the suspendable nanovial containers by centrifugation and pipetting, and each compartment can be sealed and unsealed using biocompatible oils to prevent cross-talk between samples. The nanovial surfaces are easily modified to facilitate attachment of different cell types or capture biomolecules to support high-throughput single-cell functional assays. For example, antibody-coated nanovials are used to capture secreted molecules from individual cells and secretions can then be stained with fluorescently tagged antibodies or antigens to quantify secretion quantity and antigen-specificity. Assay operations with nanovials are highly parallel enabling users to scale assays as needed from tens of thousands to millions of compartments. Importantly, nanovials are engineered to be compatible with existing flow cytometers enabling seamless integration with existing workflows and the capability to screen at high-throughput. The flexible nature of the nanovial platform enables rapid development of new assay formats that address our customer’s specific needs. For example, different affinity agents against cell surface markers can be utilized to isolate and retain specific subsets of suspension cells. Extracellular matrix materials such as gelatin or cell binding motifs such as RGD can be integrated into the nanovial matrix to facilitate binding and growth of adherent cells including producer cells (CHO, HEK), fibroblasts, and mesenchymal stem cells. We have demonstrated a number of single-cell secretion workflows with our nanovial product, including high throughput screening of producer cells based on relative IgG production as well as screening of B lymphocytes and hybridomas based on antigen-specific antibody production using commercial fluorescent activated cell sorters. We have also demonstrated the ability to isolate and screen primary T cells based on expression of multiple cytokines as well as surface presented proteins. Sorted cells remain intact and viable, enabling regrowth for downstream analysis. Single-cell RT-PCR enables RNA recovery and amplification from single cells on nanovials allowing for the recovery of antibody sequences. Nanovial-enabled workflows promise to democratize antibody discovery and cell line development, and also empower researchers to investigate single-cell secretions, as a key cellular function, with unprecedented precision and scale.""
Controllable Microfluidic Devices for High-throughput Characterization of Bacterial Communication
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Open to view video. Cellular communities use inter-cellular signals to divide the labor of complex biological functions among species. Despite the advancement of synthetic biology tools for engineering complex genetic circuits with programmed functions, synthetic communities still lack mechanisms that provide co-cultures with robustness to environment fluctuations present in natural systems. Microfluidic devices can improve the robustness and sensitivity of co-cultures to varying environmental contexts. With spatial and temporal control, such devices enable the studies of novel intercellular signals in controlled conditions and their deployment in natural conditions. Here, we first developed a massively parallel microfluidic device to study the dynamics of bacterial communication in synthetic microbial communities. Namely, custom biocommunication channels and precise control over experimental conditions simultaneously allow for the characterization of multiple co-cultures. Next, cell-cell communication was designed to leverage quorum-sensing systems and activate a fluorescence reporter system downstream. We built five pairs of sender-receiver cells carrying five intercellular signaling systems, independently, in which the receiver cells produce YFP signals after successful communication. Then, bacterial co-cultures were grown and maintained in long-term experiments (around seven days) in microfluidic devices under time-lapse microscopy. Signal processing tools were used to independently detect, track, and analyze fluorescence signals at the single-cell level for each pair of cells.
Drug repurposing for Cancer Precision medicine: High-Throughput Drug Screening as an integrative precision medicine platform in drug repurposing
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Open to view video. Optimizing Drug discovery and Translation is one of the key tracks in Global Challenges Annual meeting 2019 and is the critical factor in achieving UN Sustainable Development Goals 3 Good Health and Well Being. WHO reports Cancer is the second leading cause of death globally with the estimated 9.6 million deaths in 2018 (1 in 6 death is due to cancer). In additional, 70% of mortality from cancer occur in low- and middle-income countries such as South Africa. Relevance to the low- or middle-income country setting and Grand Challenges: Recent report from Discovery Medical Schemes states that cancer causes more death in South Africa than HIV, Tuberculosis and Malaria. Leukaemia is one of the top ten most common cancer in South Africa. In addition, leukaemia is the most common childhood cancer (25.4% of all cancers) in South Africa, which is similar to rates in other countries. Currently, there is drive at South Africa by DSI, CSIR and MRC to establish a precision medicine program that would address the needs of South African Patient cohort. My functional precision medicine strategy is designed to directly identify tailored drug regimens that target individual patient´s cancer cells and give benefit to the same donors by supporting clinical decision-making. We aim for this project to serve as a proof of concept to showcase whether individually designed high throughput drug sensitivity screening along with microfluidics based single cell drug screening can provide patient benefit with limited material available and to build competence on existing drug sensitivity screening at CSIR using newly developed platform technologies such as microfluidics based single cell drug screening. The proposed project is therefore well aligned with the strategy of present drive of South African Precision Medicine initiative. 
How Artificial Intelligence techniques can be employed to increase the success rate for identifying Datamatrix Barcodes
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Open to view video. "Datamatrix barcodes play a key role in tracking and tracing both biological and compound samples. These barcodes are usually lasered onto the underside of sample tubes, and the tubes are stored in racks. Barcode reading is conducted using a barcode reader that scans the bottom of a rack of tubes and decodes all barcodes in one go. This is nice in theory, but there are regular issues with identifying the barcodes on the bottom of the tubes. Ambient lighting, background image noise, and variation in lasering and material quality yield tube barcodes that are often difficult to detect with traditional machine vision techniques. However, it can be noted that a human can always resolve these barcodes, even in adverse conditions. Therefore, it is reasoned that artificial intelligence techniques can be employed to increase the success rate for identifying datamatrix barcodes. Convolutional Neural Networks (CNNs) are a well understood technique for feature extraction of images. In this work we take the notion of the CNN and apply it to the new application for locating 2D datamatrix barcodes on sample tubes. The chosen CNN is designed to be very lightweight allowing for quick execution. When compared to the pre-existing heuristic methods, the CNN approach was almost ten times faster to execute with virtually 100% accuracy. The CNN is implemented on embedded technology, in this instance a Field Programmable Gate Array (FPGA). FPGAs allow for custom circuity to be created for specific application; due to the custom nature of the implementation this yields a very high-speed CNN, faster than can be achieved on a standard PC processor. The inclusion of the FPGA to the system opens new possibilities to the way in which the barcode scanners can be implemented. The power of the embedded FPGA means it is now possible to build a stand-alone mobile scanner, capable of decoding an entire rack in a sub-second timeframe while having low power requirements and outperforming a traditional high-spec laptop or desktop PC. Future work will build on the current achievements of the project and look to introduce more artificial intelligence techniques into the decoding step of rack scanning."
Miniaturized, single-cell imaging of mature feeder layer-free human iPSC-derived neurons
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Open to view video. Human induced pluripotent stem cell (iPSC)-derived neurons are being increasingly used for high content imaging and screening.  However, differentiation and maturation iPSC-derived neurons is time-intensive, often requiring >8 weeks. The differentiating/maturing iPSC-derived neuronal cultures also tend to migrate and coalesce into ganglion-like clusters making single-cell analysis challenging, especially in miniaturized formats. Using our optimized extracellular matrix and low oxygen culturing conditions, we further modified neuronal progenitor cell seeding densities and feeder layer-free culturing conditions in miniaturized formats (i.e., 96 well) to decrease neuronal clustering, enhance single-cell identification and reduce edge effects usually observed after extended cell culture. Subsequent algorithm development refined capabilities to distinguish and identify single mature neurons, as identified by Calbindin and NeuN co-expression, from large cellular aggregates. Incorporation of astrocyte conditioned medium during differentiation and maturation periods significantly increased the percentage (i.e., ~10% to ~30%) of mature neurons (i.e., Calbindin+/NeuN+) detected at 4-weeks post-differentiation. This miniaturized, feeder layer-free format and image analysis algorithm provides an imaging and screening platform, which enables quantitative single-cell documentation of mature human neuron populations.    
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Panel on The Clear Case for Diversity, Equity and Inclusion in Life Sciences
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Emerging Trends in Digital Health: The Future of Healthcare
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AI in Labs: Improving Research, Products and a Look to the Future
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