2016 Archived Content

High-Content Analysis


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Monday, October 31

7:00 am Conference Registration and Morning Coffee


Opening Plenary Session

8:00 Chairperson’s Opening Remarks

D. Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation Professor of Computational and Systems Biology, University of Pittsburgh

8:10 Phenotypic Responses to Small Molecules as a Means to Illuminate Chemistry and Biology

Stuart Schreiber, Ph.D., Director, Center for the Science of Therapeutics, Broad Institute

My lecture will focus on using: modern asymmetric synthesis in generating 3D compounds having novel (previously unknown) mechanisms of action (nMoA) in probe and therapeutics discovery, phenotypic multiplexed measurements to create performance-diverse compound libraries, and real-time biological annotation of synthetic compounds as a means to increase the potential of chemistry to impact biology and medicine. Examples will be selected from cancer and microbial therapeutics discovery.

8:35 Investigating Metastatic Breast Cancer in the Liver Niche through Quantitative Systems Pharmacology

D. Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation Professor of Computational and Systems Biology, University of Pittsburgh

We are investigating the mechanism(s) of disease progression of metastatic breast cancer (MBC) using a platform based on quantitative systems pharmacology (QSP). QSP involves an integrated and iterative application of computational and systems biology combined with experimental approaches. A key component of QSP is the development and use of disease relevant experimental models. We have developed a human, microfluidic, 4-cell liver model to explore the mechanisms of extravasation and dormancy in MBC.

9:00 A High-Content Imaging Approach to Characterize and Address Heterogeneity in an Organotypic Model of Human Alveolar Epithelium

Christophe Antczak, Ph.D., Lab Head, Center for Proteomic Chemistry, Novartis Institutes for BioMedical Research

Organoid cell models that recapitulate aspects of tissue organization/ function are of great interest for drug discovery. However, their multicell type and three-dimensional organization presents a challenge for quantitative readouts. We developed methods for confocal image analysis of a spheroid model of human alveolar epithelium that helped characterize and address its heterogeneity, intrinsic to organotypic cultures derived from pluripotent cells.


9:25 Coffee Break in the Exhibit Hall with Poster Viewing


HCS Image Analysis and Modeling

10:10 Chairperson’s Opening Remarks

Anne E. Carpenter, Ph.D., Director, Imaging Platform, Broad Institute of Harvard and MIT

10:15 Learning Dynamic Models of 3D Cell Organization and Perturbation

Robert F. Murphy, Ph.D., Ray and Stephanie Lane Professor, Computational Biology and Professor, Biological Sciences, Biomedical Engineering, and Machine Learning, Head, Computational Biology, School of Computer Science, Carnegie Mellon University

Generative models provide a more powerful way of comparing sets of 3D images and 3D movies (such as from different cell types or conditions) than descriptive features. They permit comparison across different microscopes and settings, and yield interpretable insights. For example, models constructed from T cells expressing tagged signaling proteins revealed specific roles in co-stimulation by antigen-presenting cells, and models of PC12 cells undergoing differentiation revealed changes in mitochondrial distribution.

10:40 Richer Phenotypes through Image Informatics: Targeting Diseases and Characterizing Compounds via Image-Based Profiling

Shantanu Singh, Ph.D., Senior Group Leader, Broad Institute of Harvard and MIT

Microscopy images contain rich information about the state of cells, tissues and organisms. Yet most so-called “high-content” phenotypic screening experiments measure only one or two morphological features. Our laboratory aims to harvest the rich information in images by extracting patterns of morphological changes (“profiles”) from cells in response to perturbation by small molecules and/or genetic manipulation. These profiles are used to identify similarities and differences between various chemical or genetic treatments, with the ultimate goal to identify the causes and potential cures of disease. The image analysis algorithms and data mining approaches we develop are freely available through the biologist-friendly open-source software, CellProfiler (www.cellprofiler.org), for both small- and large-scale experiments.

11:05 Quantitative Time-Lapse Fluorescence Microscopy as a Compelling in vitro Screening Tool for Drug Combination Therapies in Cancer

Ozan Alkan, Ph.D., Principal Scientist and Research Team Leader, Discovery, Merrimack Pharmaceuticals

Our goal is to gain mechanistic understanding of DNA damage response pathway topology and to develop a predictive computational model of the involved mechanisms. The model will help rationally design therapies targeting the DDR pathway. In particular the discovery of synergistic and potentiating effects of drug combinations using standard-of-care drugs, such as topoisomerase poisons doxorubicin and irinotecan/SN38, and existing or novel DDR targeting modulators/inhibitors are in the main focus of the analysis.

11:30 Enjoy Lunch on Your Own


High-Content Phenotypic Screening

1:30 Chairperson’s Opening Remarks

Regis Doyonnas, Ph.D., Senior Principal Scientist, Primary Pharmacology Group, High Content Screening Lead, Worldwide R&D, Pfizer

1:35 Exploring Biology with Information-Rich Probes in Complex Phenotypic Screens

Jeremy L. Jenkins, Ph.D., Director, Developmental & Molecular Pathways, DMP Research Informatics, Novartis Institutes for BioMedical Research

High-content screening formats that increase disease relevance may also restrict assay throughput. Several computational strategies and experimental case studies are presented in which biologically diverse library content is used to drive biological hypothesis generation for high-content screening results.

2:00 Power and Challenges of High-Content Phenotypic Screening in Drug Discovery

Regis Doyonnas, Ph.D., Senior Principal Scientist, Primary Pharmacology Group, High Content Screening Lead, Worldwide R&D, Pfizer

Phenotypic drug discovery brings “great power that comes with great responsibility”...and many challenges. 1) As assays become more and more physiologically relevant there is a need to capture as many read-outs as possible, and the complexity of these assays increases. 2) The acquisitions of these read-outs require highly sophisticated instrumentation with maximum flexibility for kinetic experiments, 3D culture and maximum sub-cellular resolution. 3) The data generated is therefore complex and require solid infrastructure and workflow processes to run these assays at scale while mining all single cell parameters generated. This talk will highlight high-content phenotypic methods and processes developed at Pfizer to address these challenges to push the boundaries of phenotypic drug discovery programs.

2:25 Target-Centric Phenotypic Screening for Drug Discovery

Thierry Dorval, Ph.D., HCS Group Leader, Institut de Recherches Servier

2:55 Refreshment Break in the Exhibit Hall with Poster Viewing

3:45 A Phenotypic Screen for Modulators of Adipogenic Differentiation

Dana Nojima, Ph.D., Senior Scientist, Discovery Technology, Amgen

4:10 Multiplexed Fluorescence Imaging Using Nucleic Acid Probe Exchange

Mark Bathe, Ph.D., Associate Professor, Biological Engineering, MIT

Fluorescence imaging offers the potential to characterize neuronal synapse protein and mRNA levels and localizations in situ. However, current imaging approaches can simultaneously interrogate no more than four of the several dozen molecules of interest in any given neuronal sample. To overcome this obstacle, we are developing a fluorescence imaging assay that enables highly multiplexed molecular characterization of protein and mRNA expression levels and localizations in intact neurons.

4:35 Evolution on a Plate: Cancer Cell Response to Therapy as a Stochastic, Darwinian Process

Arijit Chakravarty, Ph.D., Director, Modeling and Simulation, Takeda

An emerging viewpoint in the field frames cancer progression and response as evolutionary processes. What are the implications for cell-based and high-content work? In this talk, I will discuss the practical consequences of thinking of cancer as an evolutionary process, using as specific applications the development of a novel in vitro high-content evolutionary assay platform, and the application of evolutionary theory to traditional in vitro dose-response assays.

5:00-6:00 Welcome Reception in the Exhibit Hall with Poster Viewing

5:45 Short Course Registration

6:00-9:00 Dinner Short Course*
(SC1) Introduction to High-Content Phenotypic Screening

*Separate registration required

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Tuesday, November 1

7:30 am Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee


High-Content Screening of 3D Models

8:25 Chairperson’s Remarks

Matthias Nees, Ph.D., Coordinator, HCS Lab, Turku Science Park/Finland

8:30 Supporting Phenotypic Drug Screening Efforts with 2D & 3D High-Content Analysis during Early Pharmaceutical Drug Research

Stefan Prechtl, Ph.D., Senior Scientist, Bayer HealthCare AG

Automated imaging systems in combination with sophisticated IT infrastructure meet the needs for high-content analysis (HCA) of large data sets and can efficiently support modern pharmaceutical drug research. By evaluating, analyzing and quantifying the impact of compound treatment under physiological conditions, when it cannot be done by standard screening systems, HCA-driven approaches positively impact the lead-finding process. At Bayer Healthcare, we exploit this technology in several different therapeutic areas ranging from cell signaling via tumor metabolism to epigenetic regulation to support research projects that are aiming for the identification of novel chemical entities. Two-dimensional cell culture systems as well as three-dimensional cell culture systems are routinely used in a wide range of assay methods that are based on immunocytochemistry, reporter gene expression and live-cell imaging. Especially, three-dimensional cell culture systems enable an improved drug research support as these systems mimic the different metabolic microenvironments found in tumors under physiological conditions. A well-established and reliably running HCA facility significantly supports pharmaceutical research. Nevertheless, remarkable challenges not only pop up during the initial setup of such a complex system, they also routinely emerge whenever new assays are developed, and need to be overcome for a consistent HCA-based compound profiling support.

8:55 Fast & Curious: Combining Speed of Analysis with Physiologically Relevant, Complex Tissue Models for Informative High-Content Screening

Matthias Nees, Ph.D., Coordinator, HCS Lab, Turku Science Park/Finland

Model systems for oncology typically do not address the complex tissue architecture of clinical, solid cancers—and only few approaches aim to capture the complexity, heterogeneity and dynamics that occur in the tumor microenvironment. To facilitate this goal, ultrafast, automated image analyses are required that reconcile the needs for significant experimental throughput with an option to faithfully capture the biology of cancers in drug discovery.

9:20 High-Throughput, Open-Source Analysis of Three-Dimensional Structures Using CellProfiler
Allen Goodman, Ph.D., Senior Software Engineer, Broad Institute of Harvard and MIT

9:50 Coffee Break in the Exhibit Hall with Poster Viewing


Phenotypic Screening in Human iPSC Models

11:05 Chairperson’s Remarks

Mark Mercola, Ph.D., Professor, Department of Medicine and Cardiovascular Institute, Stanford University School of Medicine

 

11:10 High-Content Analysis in Human iPSC-Derived Cardiomyocytes to Identify Future Heart Failure Therapeutics

Charles C. Hong, M.D., Ph.D., Associate Professor, Cardiovascular Medicine, Pharmacology, and Cell and Developmental Biology, Vanderbilt University School of Medicine

In a manner analogous to classic mutagenesis screens, the Hong Lab conducts high-content chemical screens using zebrafish and cell-based platforms to discover small molecules with therapeutic potential. We recently developed a Matrigel Mattress method to assess both systolic and diastolic functions in cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). Using this method as a platform for drug discovery, we identified a novel class of potential heart failure therapeutics that exerts inotropic and lusitropic effects in vitro and in vivo without the deleterious chronotropic effects.

11:35 Using Patient-Derived iPSC Cardiomyocytes to Optimize Drugs for Heart Rhythm Disorders

Mark Mercola, Ph.D., Professor, Department of Medicine and Cardiovascular Institute, Stanford University School of Medicine

The advent of patient iPSC-derived cardiomyocytes promises to reintroduce the patient into the early stages of drug discovery. To bring “disease-in-dish” models into drug and drug target discovery tools, we have developed statistically robust high throughput physiological screening to evaluate the effects of small molecules, genes, and proteins on cardiomyocyte cell cycle, contractility, Ca2+ transient and action potential (AP) kinetics. We are developing a pipeline of combinatorial screening, and biochemical target identification is used to decipher disease mechanisms and point to new drug targets. Examples of large-scale physiological screening include cardiotoxicity of oncology drugs, progress to elucidate mechanisms of familial dilated cardiomyopathy, and the use of screening to develop structure activity relationships for specific on-target and proarrhythmic effects of a small molecule drug.

12:00 pm Close of Conference.

Stay on to attend Phenotypic Screening.



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