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High Content Analysis - Day 1

 

Wednesday, January 12

7:00-8:00 Conference Registration and Morning Coffee

8:00-8:10 Welcoming Remarks from Conference Director

Julia Boguslavsky, Executive Director, Conferences, Cambridge Healthtech Institute

Sponsored by
Thermo
8:10-8:15 Introduction from Executive Sponsor

Emily Milsovic, Director, Commercial Sales & Marketing, Thermo Fisher Scientific




8:15-9:15 Panel Discussion with End-Users and Vendors

Chairperson: Anthony M. Davies, Ph.D., Director, High-Content Research Facility, Clinical Medicine, Trinity College

 

Discussion Questions Include:

  • What new applications and image analysis tools are expected to be launched in 2011?
  • What is the progress on imaging standards?
  • How is the need for new probes and protein-protein interaction imaging tools addressed?
  • What are the new application areas undergoing rapid adoption?

End Users:

  • Karol Kozak, Ph.D., Head, Data Handling Unit and High-Content Screening, ETH Zurich
  • Paul A. Johnston, Ph.D., Research Associate Professor, Department of Pharmacology and Chemical Biology, University of Pittsburgh Drug Discovery Institute
  • Joe Trask, Ph.D., Head, Cellular Imaging Core, The Hamner Institutes for Health Sciences

Vendors:

  • Khuong Truong, Ph.D., European Business Manager & WW Strategic Marketing Lead, BD Biosciences
  • J. Michael Honeysett, M.B.A., Market Development Leader, Global, GE Healthcare Life Sciences
  • Jacob G. Tesdorpf, Ph.D., Director, High Content Instruments and Applications, PerkinElmer
  • Scott Keefer, M.B.A., Manager, Project Management, Thermo Fisher Scientific, Life Science Research-Cellomics

9:15-10:30 Coffee Break with Exhibit and Poster Viewing

 

High-Content Screening in Drug Discovery 

10:30-10:35 Chairperson’s Opening Remarks

Jeff Haskins, Ph.D., R&D Director, Site Leader, Life Science Research – Cellomics, Thermo Fisher Scientific

10:35-11:00 High-Content Analysis at the Nano Scale: Miniaturized Cell-Based Assays - Problems and Solutions

Anthony M. Davies, Ph.D., Director, High-Content Research Facility, Clinical Medicine, Trinity College

In this presentation we will cover a variety of assay miniaturization approaches currently used in high-content analysis. We’ll outline the problems that are an inherent feature of these cell assay miniaturization techniques, and showcase a range of environmental buffering and mimetic technologies that offer the capability of performing cell based assays 1,000-10,000 X smaller than currently possible. Finally, we’ll demonstrate how new miniaturization technologies will enable entirely new cell based assay approaches.

11:00-11:25 Development and Implementation of an Androgen Receptor Nuclear Localization HCS of 220,000 Compounds on the ArrayScan VTI and ImageXpress Ultra: Head to Head Comparison of the Performance of the Two Automated Imaging Platforms

Paul A. Johnston, Ph.D., Research Associate Professor, Department of Pharmacology &
Chemical Biology, University of Pittsburgh Drug Discovery Institute

Prostate cancer (CaP) is the most common solid tumor and the second leading cause of cancer death among men in western countries. Studies suggest a relationship between cellular AR levels in primary and metastatic CaP lesions and subsequent disease progression. The AR is a member of the nuclear hormone receptor family of ligand-dependent and DNA-sequence specific transcription factors that is required for the normal growth, terminal differentiation and function of the prostate gland. Although CaP cells proliferate in androgen-depleted conditions, their growth still requires the AR. Nuclear translocation is a key regulatory step in the action of AR. In castration resistant CaP cells, AR remains in the nucleus, even in the absence of androgen, resulting in transactivation of androgen-responsive genes and tumor growth. We have recently completed a 220,000 compound AR nuclear localization HCS seeking compounds that inhibit the nuclear localization of the AR in a castration resistant CaP cell model. We will describe the development and implementation of the assay on both the ArrayScan VTI and ImageXpress Ultra automated platforms and on the hits that were identified. We will present a head to head comparison of the performance of the wide field and confocal imaging platforms.

11:25-11:50 High-Throughput for
High-Content Screens! What Else?

Vincent Unterreiner, Ph.D., Scientist II, Novartis Institute for Biomedical Research, Lead Finding Platform, Novartis Pharma AG

Sub-cellular imaging using confocal and non-confocal microscopy has been available for more than 20 years. Nowadays, High-Content Screening (HCS) is actively being applied in screening of small molecules within pharmaceutical companies. With the recent improvement of the HCS instrumentation enabling higher throughput, the technology is evolving from a traditional use in focused or secondary screening to a more intensive application in full-deck primary screening. Using the example of different high-content primary hit finding approaches performed within the Lead Finding Platform of the Novartis Institute of Biomedical Research, the presentation will display the different technologies and their adaptation to different assay types and/or lead finding strategies. The topic will cover a broad range of the different aspects of the HCS/HTS challenges, from plate preparation and imaging to data analysis and data management strategies. The technical gaps to be bridged, merging High-Content with High-Throughput, will be identified and discussed. Finally, the focus will be on the benefits that the technology is bringing into the primary screening area compared to conventional assays as well as on the inherent limitations associated with it.

11:50-12:15 pm Is Phenotypic High-Content Screening the Better Pathway Screening Approach to Identify Novel Chemical Entities?

Stefan Prechtl, Ph.D., Senior Scientist, Lead Discovery Berlin, Screening, High-Content Analysis, Bayer Schering Pharma AG

High-Content Screening approaches represent drug screening in a more appropriate physiological context. Primary screening campaigns, each analyzing more than 2.5 Mio compounds, were performed in our labs and have demonstrated technical feasibility of such Ultra-HCS campaigns. Nevertheless, it is important to clarify the outcome of U-HCS campaigns when compared to standard HTS approaches. Serious efforts have to be invested in laboratory work, staff recruitment and material costs during HCA-based primary screening. Do these efforts turn to account when novel chemical entities can be identified that are of greater drugability?

High-Content Data Analysis 

10:30-10:35 Chairperson’s Opening Remarks

Karol Kozak, Ph.D., Head, Data Handling Unit & High Content Screening, ETH Zurich

10:35-11:00 The Open Microscopy Environment (OME): Informatics for Biological Imaging and HCA

Jason Swedlow, Ph.D., Professor, Quantitative Cell Biology, Wellcome Trust Centre for Gene Regulation and Expression, University of Dundee

OME is a multi-site collaborative effort across academic laboratories and commercial entities that produces open tools to support data visualization, management, and analysis for biological microscopy and high-content screening (HCS). All OME specifications and software are free, and all source code is available under GNU public “copyleft” licenses. With a strong foundation for biological light microscopy in place, OME has begun extending its coverage to HCS, electron microscopy, scanning probe microscopy, and other emerging modes of biological imaging.

11:00-11:25 Computational Analysis of Off-Target Effects in RNAi Screens

Karol Kozak, Ph.D., Head, Data Handling Unit & High Content Screening, ETH Zurich

The occurrence of off-target effects is still a challenging aspect in the interpretation of data from large-scale RNA interference screens. Up to now many methods have been found to reduce these effects, but they cannot completely be avoided. In the framework of this talk methods and tools for the analysis of off-target effects will be presented which can be applied after High-Content Screenings (HCS). Additionally, new statistical methods for hit selection in RNAi HCS experiments will be described. The general goal of this presentation is to describe an open-source informatics platform for integrating, sharing and processing HCS data using a workflow-oriented architecture.

11:25-11:50 Optimization of High-Content Assays with Multi-Parametric Analysis Using Open Source Software Tools 

Martin Stöter, Scientist, High-Content Screening, HT-Technology Development Studio (TDS), Max Planck Institute of Molecular Cell Biology and Genetics

To develop conditions for high-content assays, a multi-parametric readout is necessary. Conversely, multi-parametric readouts need to be developed on a working assay, leading to a chicken-and-egg problem. Generally, this is solved in an iterative fashion with multiple rounds of optimization with feedback loops. We have established methods for concomitantly optimizing assay conditions and readout parameters using the open source software KNIME. Application of such methods for selecting from over 800 parameters while simultaneously optimizing assay conditions for a chemical and an RNAi TGF-beta signaling screen will be presented.

11:50-12:15 pm The BioAssay Ontology Project: Novel Tools to Query and Analyze Diverse Data

Stephan Schürer, Ph.D., Assistant Professor, Department of Pharmacology, Center for Computational Science, Miller School of Medicine, University of Miami

We developed the first BioAssay Ontology (BAO) to organize and formally describe high-throughput and high-content data. BAO and novel software tools that are developed in this project enable querying, browsing and, ultimately, analysis and integration of diverse data sets. In contrast to established tools, our ontology-driven semantic description of biological screening data enables reasoning and thus can uncover hidden, inferred knowledge that is not explicitly defined in the ontology or the data. Using a large number of annotated assays - primarily derived from PubChem - we show how BAO tools make it easy to ask complex queries and enable intuitive retrieval of results that would otherwise require more complicated searches or could not be asked at all. We also illustrate BAO-facilitated analyses across large number of assays; the results can be useful to evaluate and follow-up screening hits.

Live-Cell Imaging 

10:30-10:35 Chairperson’s Opening Remarks

David W. Andrews, Ph.D., Professor, Biochemistry and Biomedical Sciences, Canada Research Chair in Membrane Biogenesis, McMaster University

10:35-11:00 FLIM and FRET Readouts: From Automated Multiwell Plate Readers to Zebrafish and Mice

Paul French, Ph.D., Professor, Physics; Head, Photonics Group, Physics Department, Imperial College London

We have extended our multidimensional fluorescence imaging platform, incorporating image segmentation in our lifetime analysis of high-content data from our automated FLIM/FRET optically sectioned multiwell plate reader. We have also developed a tomographic FLIM/FRET imaging platform based on optical projection tomography (OPT) and diffuse fluorescence tomography (DFT). We will present the application of automated FLIM/FRET multiwell plate imaging of protein interactions and the application of FLIM/FRET to OPT, including of zebrafish, as well as the application to DFT of mice.

11:00-11:25 Effect of Ligand Binding on the Stoichiometry, Structure, and Distribution in Living Cells of Some GPCR Homo-Oligomers

Valerica Raicu, Ph.D., Associate Professor, Department of Physics, University of Wisconsin

Advances in multiphoton microscopy with spectral resolution and the theory of Förster Resonance Energy Transfer (FRET) recently lead to our development of a novel method for the determination of structure and localization in living cells of membrane protein complexes. An appealing feature of this method is its ability to provide such important information while remaining unaffected by spurious signals originating from stochastic FRET. This presentation will review the results obtained from our recent studies of oligomeric complexes of several G protein-coupled receptors (GPCRs) in vivo, in the presence and absence of natural and synthetic ligands.

11:25-11:50 Fluorescence Lifetime Imaging Microscopy for Quantitative Live-Cell Imaging

Ching-Wei Chang, Ph.D., Postdoctoral Scholar, Department of Bioengineering, University of California, Berkeley

Fluorescence Lifetime Imaging Microscopy (FLIM) is a useful indicator of microenvironment in cellular optical molecular imaging. It is relatively insensitive to the artifacts affecting fluorescence intensity such as variations in excitation source intensity and photobleaching. FLIM utilizes fluorescence lifetime as image contrast and has been employed to probe fluorophore microenvironments such as pH and molecular interactions via FRET. In FLIM applications to quantitative live-cell imaging, precise lifetime determination is important, yet is often difficult to accomplish. Several methods will be described to improve the accuracy, precision, and spatial resolution of FLIM by using physiological conditions, optimal (virtual) gating, and image processing methods such as denoising.

11:50-12:15 pm Automated Classification of Images Generated in High-Content Screening of Live Cells

David W. Andrews, Ph.D., Professor, Biochemistry and Biomedical Sciences, Canada Research Chair in Membrane Biogenesis, McMaster University

We are exploring the use of fluorescence proteins and unusual dyes for both genetic and chemical screens in live cells. When screening libraries of small molecules image analysis techniques permit a large amount of data to be extracted from each treatment condition but this data is then often processed to provide a single aggregate value to represent the population. While this approach gives a good estimate of population averages, the results can be misleading, as the behavior of subpopulations is neglected. Subpopulation data is a particular issue for automated analysis of the differentiation of stem cells and for the interpretation of RNAi screening data. I will describe our quest to understand what image data provides the most useful information and how best to automate classification of images from genetic and chemical screens of human stem and cancer cells.

 

 

Luncheon Technology Showcase: High-Content Screening 

Sponsored by
Molecular Devices
12:30-1:00 From Acquisition to Analysis:  Tools to Improve the High Content Screening Workflow for Stem Cell Assays 

Evan F Cromwell, Ph.D., Director, Research, Molecular Devices
High content screening (HCS) is a critical technology for capturing biologically relevant measurements from multiple cellular parameters in small molecule, genome-wide RNAi and compound profiling screens.  An emerging area where HCS tools are invaluable is in stem cell analysis.  There is a great interest in automated stem cell assays to use as screening tools in early drug development, and to evaluate potential toxic effects of new compounds.  However, while these screens yield large amounts of data crucial to scientific discoveries, the volume of metadata produced can be unwieldy to manage.  We will present examples of use of HCS and data management tools for studies of neuronal stem cells and cardiomyocytes.  We demonstrated effects of various agents on neurosphere formation and differentiation of adult or embryonic stem cell derived neuronal progenitors.  In addition, we monitored differentiation of cardiomyocytes and developed methods for automated cardioprotection and cardiotoxicity assays.  We will show how the HCS workflow can be optimized to accelerate analysis and how routine screening can be simplified by moving low resolution assays onto faster imaging platforms.


1:00-1:15 Introducing the CellInsight™ Personal Cell Imager, High-Content for Everyone!Sponsored by
Thermo Scientific logo
 

Mark Collins, Global Director, Marketing, LSR-Cellomics,
Thermo Fisher Scientific

Many traditional fields of cell biology research are benefitting from investigating multiple targets in intact, living cells, compared to traditional biochemical assays. Over the past 10 years, automated, quantitative imaging of cells has gained traction in neurobiology, oncology, infectious disease and IV toxicology as well as across the early drug discovery process. The adoption of high-content has been hindered, however, by complexity of operation, cost of current offerings, and lack of validated reagents. Thermo Fisher Scientific has developed a unique personalized cell imaging (PCI) platform, CellInsight™ that for the first time provides the cell biology researcher with a simple to operate, lower cost, compact automated imaging capability. By combining a solid state optical/light train with the best high content software in the business and coupling in a range of fluorescent probes, engineered cell lines and validated assay kits, cell biology researchers can investigate 100’s of cellular targets and advance their knowledge of cell function at their own benchtop.

Sponsored by
GE Healthcare
1:15-1:30 Cell Based Imaging Systems and the Need for GXP Compliance
Mike Honeysett, MBA, Global Market Development Leader, GE Healthcare, Life Sciences
As HCA has now become an integral part of the drug discovery process, the market demand for GxP compliance has reached a critical point, whereby global pharmaceutical markets are now seeking full validation of the technology.
In this talk, a discussion on FDA compliance, specifically 21 CFR Part 11, will be presented as an essential metric for the validation of automated cell based imaging systems.  As an illustrative example, a putative GxP compliant workflow model will be presented for validating the security, integrity, and traceability of electronic records, as well as the metrics for IQ/OQ documentation and standards.

Sponsored by
Yokogawa
1:30-1:45 Cutting Edge HCA and Live Cell Imaging Systems from Yokogawa Electric Corporation
Baggi Somasundaram, Ph.D., Sales & Marketing, BioImaging Solutions, Inc.
Yokogawa Electric Corporation is pleased to introduce the CellVoyager™ product line, which was developed based on Yokogawa’s proprietary spinning disk technology. CV6000 is a versatile HCA system featuring imaging speeds of less than 60 seconds per 96-well plate with confocal images of both fixed and live cells. CV6000 combines fluidics and plate incubation capabilities with multifunctional data acquisition and analytical software.
CV1000, the desktop real-confocal live imaging system, includes a precision incubation chamber and positioning capabilities. It features multipoint observation of long term cellular processes, and is also suitable for mid-throughput HCA.

Luncheon Technology Showcase: High-Content Data Analysis 

12:30-12:45 Lights, Camera, Action…iView!Sponsored by
Thermo Scientific logo
 

Joseph Zock, Cell Solutions Marketing Manager,LSR-Cellomics,

Thermo Fisher Scientific

A new addition to the Thermo Scientific High-Content 2.0 platform, iView software takes our users to a new level of image visualization from the plate level to the individual cell level. Plate, well, and cell QC has never been easier. Viewing all target channels, RGB’s, field montages, and overlays with quick zoom functionality reduces assessment times, while industry first features like the “phenotype gallery” makes identifying interesting cell subpopulations from the data quick and painless. iView also dramatically increases kinetic experiment visualization with new time lapse movie rendering and multi-movie visualization capability. Together with the LED Light Engine, iDEV assay development environment, and hardware like the Zeiss Z1 optical train, iView provides yet another innovative advance for the most productive high-content platform in the world.

Sponsored by 
GeneData logo
12:45-1:00 Genedata Screener Solves Current Issues in HCS: Image and Data Access on Multiple Instruments while Streamlining the Data Analysis Process
Jon Tupy, Ph.D., Head of US Professional Services, Genedata
Scaling up HCS operations remains an issue for most screening laboratories; employing multiple instruments from different vendors creates challenges with data organization and access. At the same time, throughput per instrument has increased and operational efficiency at high data quality is harder to attain.
Genedata Screener's High Content Analyzer solves these issues by importing data from any instrument and allowing instant access to HCS images in any format, providing ready-to-be-used integrations for most popular instruments. Interactive analysis and the quality control capabilities of Screener will be emphasized in this talk, and real world applications from Genedata’s customer-base will be given.

Sponsored by
GE Healthcare 
1:00-1:15 Automated Imaging and Organ-Based Analysis of Zebrafish

Robert Graves , Ph.D.,  Senior Applications Scientist, GE Healthcare
Zebrafish is a model organism of increasing interest for early-phase testing of drug efficacy and toxicity.  The appeal of this organism mainly relates to published studies in validation of the model’s predictive potential (80-90% concordance); ease of husbandry; a short generation time to fully developed organs at 5 days post fertilization (dpf); small size of the larvae for use in well plates (~ 4mm, at 5-dpf); and near transparency of the organs enabling label-free brightfield imaging. A major advance in automation of the workflow was the recent introduction of IN Cell Analyzer 2000, enabling whole-well imaging for 96-well plates with sufficient organ-level resolution. Automatic organ-based analysis of label-free and fluorescence images of zebrafish have also been developed, based on extensive GE software research experience in areas of face-recognition, clinical image analysis applications and high-content cellular image analysis algorithms.

 

 

 

High-Content Screening in Drug Discovery (continued) 

2:15-2:40 High-Content Screening for Inducers of Autophagy

Andreas Vogt, Ph.D., Research Assistant Professor, Pharmacology, Drug Discovery Institute, University of Pittsburgh

Autophagy is a fundamental biological process regulating energy metabolism and intracellular homeostasis. Aberrant autophagy has been linked to a variety of diseases such as cancer and neurodegenerative diseases. Morphologically, autophagy is defined as a double membrane structure (autophagosome) that encapsulates misfolded proteins and subcellular organelles. The formation of autophagosomes can be monitored by translocation of a fluorescently labeled marker protein to vesicular membranes. I will present the development of a high-content assay for autophagosome formation and its implementation as a primary screen for autophagy inducers using the NIH Molecular Libraries and Screening Center Network compound library.

Sponsored by
GE Healthcare 
2:40-3:05 Dissecting Oncogenic Induced Signaling Pathways Using Whole Well High Content Imaging 
Christina N. Ramirez, Assay Development Scientist, HTS Core Facility, Memorial Sloan Kettering Cancer Center
Oncogenic activation is one of the hallmarks of transformed phenotype resulting in foci formation. While many attempts to study this phenomenon have been made thus far, they have as yet to be fruitful. We have developed a simple high content assay platform to study the consequence of signaling pathways in a transformed phenotype induced by an oncogene as compared to the parental phenotype; the platform was optimized and validated against two oncogenes: KP, a recently discovered oncogene and HRas, a classical oncogene. In this talk, I will describe the development and validation of this high content assay and discuss the merits of using whole well imaging together with its applications to both chemical and RNAi screening.

3:05-3:30 High-Content Assay to Identify Inhibitors of Dengue Virus Infection: Merits of Cell-Based Screens
David Shum, Ph.D., Assay Development Specialist, HTS Core Facility, Molecular Pharmacology and Chemistry Program, Memorial Sloan Kettering Cancer Center
We have developed a high-content assay using a live virus infection, during which we monitor entry and replication by means of immunofluorescence staining of the DENV Envelope glycoprotein (E), while simultaneously evaluating cytotoxicity of test compounds in HEK293 cells. The assay was screened against a collection of well-characterized and FDA-approved bioactives and resulted in the identification of several known drugs. This newly validated assay offers the opportunity to rapidly identify and repurpose known drugs in an effort to make candidates available for this and other neglected tropical diseases. 

 

High-Content Data Analysis
(continued)
 

2:15-2:40 Quantitative Analysis of High-Content Screens: Machine Learning, Normalization, Ranking

Peter Horvath, Ph.D., Image Processing Scientist, Light Microscopy Center, ETH Zurich

In my talk I will present the major steps of high-content analysis, especially concentrating on machine learning and different normalization techniques we developed for RNAi and drug screens. First, I will show method selection algorithms based on cross validation and multi-parametric Z-factors. I will propose a novel single cell-based approach using high-dimensional regression for target identification. Finally, I will present non-linear normalization techniques we use for infection screening.

2:40-3:05 High-Throughput,
High-Content Screening: Automating
the Pipeline

Rajarshi Guha, Ph.D., Research Informatics Scientist, Informatics Department, NIH Chemical Genomics Center

Traditional high-throughput screening (HTS) projects have performed a large primary screen, followed by manual analysis of the screen data to select a set of compounds for follow up in a secondary screen. When performing a high-content screen in high-throughput format, the requirement of performing an entire primary screen up front can be burdensome. Instead, the ability to make follow up decisions for certain compounds during the primary screen allows us to interleave the primary and secondary screening processes. In this talk I will discuss the approach taken at the NCGC to enable parallelization of high-content qHTS screens, focusing on the use of multiple imaging technologies coupled by a messaging architecture.
I will present the informatics architecture underlying our approach and data highlighting the efficiency of the process in terms of confirmation rates as well as time savings. As part of this project I will also describe a generic REST interface to query for images generated in these screens. The interface is independent of any specific image store technology and allows any image collection to be queried in a uniform manner.

3:05-3:30 Quantitative Morphological Assays Using Pattern Recognition: Phenotype Similarity, Markerless Cell Fate Tracking, and Physiological Age

Ilya G. Goldberg, Ph.D., Head, Image Informatics and Computational Biology Unit, Laboratory of Genetics, NIH

Pattern recognition was developed in fields outside of biology but is increasingly being applied to biological image data. Pattern recognition relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for a specific image processing task. We have developed a multi-purpose image classifier that can be used in a wide variety of image-based quantitative assays. The ability of this method to characterize several biological processes will be presented, including clustering phenotypes by morphological similarity, tracking stem cell lineage without the use of biomarkers, and characterizing the morphological transitions in an aging population. 

 

Novel Probes and Biosensors 

Chairperson's Opening Remarks

Paul A. Johnston, Ph.D., Research Associate Professor, Department of Pharmacology & Chemical Biology, University of Pittsburgh Drug Discovery Institute

2:15-2:40 Fluorescent Biosensors for Cell Regulation Pathways

Alan S. Waggoner, Ph.D., Professor, Biological Sciences; Director, Molecular Biosensor and Imaging Center, Carnegie Mellon University

We are developing a “toolkit” of fluorescent probes (biosensors) for quantifying the protein regulation pathways of living cells at high resolution. Biosensors for membrane protein trafficking, intracellular protease activity, protein modification and protein-protein interactions would be very useful for basic research and drug discovery. Our new biosensors are genetically encoded for expression in and on cells and have an advantage in versatility over fluorescent proteins like GFP. The new biosensor paradigm is based on combining an engineered protein with an engineered fluorescent dye that has a large sensitivity to its local molecular environment.

2:40-3:05 HCS Assays to Identify Protein-Protein Interaction Disruptors: Characterization of the Hits Identified by Screening the p53-hDM2 and AR-TIF2 Protein-Protein Interaction Biosensors

Paul A. Johnston, Ph.D., Research Associate Professor, Department of Pharmacology &
Chemical Biology, University of Pittsburgh Drug Discovery Institute

Protein-protein interactions (PPIs) are essential for all cellular functions including the assembly and maintenance of morphological structures, DNA replication, mRNA transcription, protein translation, protein folding, and the regulation of cellular metabolism and signaling pathways. PPIs therefore represent a large number of potential therapeutic targets distinct from the ligand binding or active sites most commonly exploited for drug discovery. We have recently developed and implemented a novel imaging based p53-hDM2 positional biosensor HCS assay to screen 220,017 of the NIH’s compound library where we identified three novel structurally related methylbenzo-naphthyridin-5-amine (MBNA) hits. In HCT116 cells expressing wild type p53, the MBNAs enhanced p53 protein levels, increased expression of p53 target genes, caused p53 dependent cell cycle arrest in G1, induced apoptosis, and inhibited cell proliferation with IC50s ~ 4 µM. Using a similar PPIB format we have developed an HCS assay to measure the ligand induced translocation of the androgen receptor (AR) from the cytoplasm to the nucleus and the subsequent recruitment interactions with the Transcription Initiation Factor 2 (TIF2) co-activator. We will present data on the screening of this biosensor assay to identify disruptors of
AR-TIF2 PPIs.

3:05-3:30 Domain-Based Biosensor Technology to Measure Endogenous Receptor Activity and Trafficking: The EGF Receptor as a Case Study

Hakim Djaballah, Ph.D., Director, HTS Core Facility, Molecular Pharmacology and Chemistry Program, Memorial Sloan Kettering Cancer Center

The presentation will discuss recent assay development and validation efforts using novel biosensor approaches to screen for inhibitors of the EGFR activation, internalization, and recycling in live cells and highlights this strategy as a novel biosensor screening approach with applications to other signaling receptors; for which no drugs are currently available.


3:30-4:45 Refreshment Break with Exhibit and Poster Viewing

 

HCA for Toxicity Assessment 

Chairperson's Opening Remarks

Peter J. O'Brien, D.V.M., Ph.D., Veterinary Clinical Pathologist, Pathology, University College Dublin

4:45-5:10 Novel Applications of HCA Cytopathology in Toxicology, Oncology, and Clinical Pathology 

Peter J. O’Brien, D.V.M., Ph.D., Veterinary Clinical Pathologist, Pathology, University College Dublin 

We have shown HCA cytopathology effectively assesses human toxicity potential of early drug candidates, provides mechanistic information on their toxicity, and is useable as an in vivo biomarker of toxicity. We refined and extended this work and studied additional cases. Furthermore, we demonstrate first application of HCA cytopathology a) in the food industry in a program to identify novel, safe, health-promoting ingredients, b) in drug delivery for testing safety of polymers for use in drug formulation, and c) in its clinical application in lymph node oncology for automated diagnosis
and immunophenotyping for prognosis and directing therapy.
 

5:10-5:35 Predicting Hepatotoxicity Using High-Content Screening Data

Amit Bahl, Ph.D., Research Associate, Applied Computer Science and Mathematics Group, Merck

5:35-6:00 Understanding Toxicity Using Pharmacogenetics: Assay Development, Strategies & Workflow Approaches Using High-Content Imaging

Joe Trask, Ph.D., Head, Cellular Imaging Core, The Hamner Institutes for Health Sciences

Advances of genomic centric target approaches have led to better understandings of biological functions following treatment of chemical compounds or insult from disease. Assessment and continuation of testing in the field of personalized medicine used to treat disease with great specificity we will soon achieve advances to cure and treat illnesses. At the same time using similar approaches we have developed methodologies to mimic human genetic diversity to understand the biological functions and pathways involved from the effects of chemical compound insult and injury in a representative sample panel of 32 different primary inbred mouse strain cells. These mouse embryonic fibroblast primary cells are representative of the heritability or genetic variation within a population as it relates to a defined environment. To measure these phenotypic variations we built a multiparametric screening assay strategy to identify candidate genes involved in cytotoxicity using high-content imaging (HCI) at two different time points in dose response. I will discuss the strategies, assay design, challenges, and the development of bioinformatic tools require to analyze HCI data from 75 distinct compounds.

High-Content Data Analysis 

(continued) 

4:45-5:10 Managing and Analyzing High-Throughput HCS Cell Level Data across Multiple Instruments, Platforms and Sites 

Michael Lenard, Ph.D., Solutions Architect, Applied Biotechnologies & Biology Informatics, Bristol-Myers Squibb Company 

HCS cell level data enables the analysis of correlations between measurements at the cellular level, the use of alternative data reduction algorithms such as the Kolmogorov-Smirnov distance, classification of subpopulations by cell cycle phase, and other approaches beyond basic well-level summaries. In this presentation, we describe how management and analysis of cell features are addressed in HCS Road, our internally developed enterprise multi-platform HCS data management and analysis system. We describe how cell data is integrated in BMS HCS workflow, the approaches we took for cell data storage and data analysis, along with the scientific and business reasons for those decisions. 

5:10-5:35 Phaedra, an Integrating Environment for High-Content Data Validation and Analysis 

Emmanuel Gustin, Ph.D., Principal Scientist, Informatics, Tibotec BVBA 

The routine use of high-content assays requires the seamless integration of images, numerical data and contextual information in a powerful and user-friendly environment, with tools to explore the statistics of the data set, and the ability to apply quality markers and annotations. A team in J&J Informatics developed the Phaedra environment on the basis of the Eclipse framework and JPEG2000 technology. Phaedra provides a flexible interconnection between our different HCS instruments in our laboratories and the various LIMS environments of the therapeutic areas, and permits integration of the screening environment with OMERO. Its highly adjustable user environment can be tuned for routine use as well as advanced exploration of the data set. Phaedra supports dynamic quality assurance with a collection of interconnected views, which permit users to drill down from experiment level to individual cell level, and identify and annotate artifacts. 

5:35-6:00 Image-Based Screens of Co-Cultured Cells 

David Logan, Ph.D., Computational Biologist, Imaging Platform, Broad Institute of MIT and Harvard 

Co-cultures of two or more cell types can be a physiologically relevant model system in which to screen for chemical regulators of complex biological processes. However, extracting quantitative biological measures using automated algorithms is difficult, given that cell types with diverse morphologies are present in each image. We have developed image analysis methods combined with machine learning approaches to address multiple independent high-throughput chemical screening assays of co-culture systems. The approach is robust to situations where perfect segmentation is infeasible, because cells can be over-segmented and their sub-regions can be classified using the same approach. 

Neuronal Screening 

Chairperson's Opening Remarks

Paul A. Johnston, Ph.D., Research Associate Professor, Department of Pharmacology & Chemical Biology, University of Pittsburgh Drug Discovery Institute

4:45-5:10 Insights into Regulation
of Neuronal Morphology by Protein Kinases Using Over-Expression and Chemical Inhibitors
 

John L. Bixby, Ph.D., Professor, Pharmacology and Neurological Surgery; Associate Dean for Graduate Studies; Director, Graduate Program in
Biomedical Sciences, University of Miami, Miller School of Medicine
 

The regulation of protein phosphorylation by protein kinases and phosphatases is a key step in the control of neuronal growth and regeneration. Although a number of kinases and phosphatases have been implicated in control of axon and/or dendrite growth, a global understanding of these processes is still lacking. We are taking a variety of approaches to the problem, using HCS to examine morphological changes of primary neurons in response to changes in gene expression and challenge with inhibitors of protein kinases. Differential responses by neurons of different ages and cultured at different densities can provide insights into the value of particular neuronal model systems. 

5:10-5:35 High-Content Analysis for Neurodegenerative Diseases 

Eugenio Fava, Ph.D., Director, Services & Facilities, German Center for Neurodegenerative Diseases 

Neurodegeneration is characterized by the progressive loss of structures and consequently function of neurons. Although neurodegenerative disorders, such as Alzheimer’s and Parkinson’s diseases, have a high social cost impact, the drug discovery pipeline is dire and no drug has an indication for delaying or halting the progression of the diseases. Here we discuss how high-content analysis (HCA) and high-content screening (HCS) might play a role in the neurodegenerative discovery pipeline. We will also discuss about the technical needs and the challenges to implement end-point and kinetic cell based assays for neurodegenerative disease based on primary cells. 

 

6:00-7:00 Reception with Exhibit and Poster Viewing


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