Cambridge Healthtech Institute’s
Twelfth Annual
January 26-27, 2015 | Hilton San Diego Resort & Spa | San Diego, CA 

Sunday, January 25

5:00-6:30 pm Short Course Registration and Main Conference Pre-Registration

6:00-9:00 Dinner Course*: SC1: Introduction to High-Content Phenotypic Screening
Instructor: Anthony M. Davies, Ph.D., Center Director, Translational Cell Imaging Queensland (TCIQ), Institute of Health Biomedical Innovation, Queensland University of Technology 


*Separate registration required

Monday, January 26

7:00 am Conference Registration and Morning Coffee

8:00 Welcome Remarks from Conference Director


Opening Plenary Session:

High-Content and Phenotypic Screening in Predictive Toxicology

8:10 Chairperson’s Opening Remarks

Larry A. Sklar, Ph.D., Director, University of New Mexico Center for Molecular Discovery

8:15-8:40 High-Content Imaging Approaches for in vitro Toxicology

Armin Wolf, Ph.D., Professor and Director, Preclinical Safety, Novartis Institutes for BioMedical Research

HCI provides multiplexed detailed information at the level of a single cell, as well as characterization of cellular population distributions. It serves as a superior investigational tool compared to standard spectrophotometric plate readers that measure only average properties of a cell population. Moreover, mechanisms of compound-induced toxicity and the specific cellular pathways involved can be studied in vitro in combination with the use of specific enzyme inhibitors, enzyme inducers or RNA interference.

8:40-9:05 Use of HCI for Preclinical Safety Assessment at Roche

Stefan Kustermann, Ph.D., Head, High Content Imaging, Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Center Basel

High-content imaging-based profiling of drug candidates is part of preclinical safety assessment at Roche and applied either early on in the drug development process to prioritize compound series for further development, or to assess mechanisms of toxicity of compounds displaying liabilities later on in development. While selection of the appropriate assay panel is key, we also experienced that choice of the relevant time point for measurement has a strong impact on the outcome of the analysis. Multiparameter- and live-imaging approaches allow optimization of both of these aspects and subsequent establishment of tailored screening cascades to streamline drug safety testing.

9:05-9:30 High-Content Analysis for Predictive Toxicology

Mikael Persson, Ph.D., Primary Exploratory Toxicologist, Exploratory Toxicology, H. Lundbeck A/S

Predictive toxicology has been integrated in the drug discovery process, with the aim to design safer drug candidates and timely deselect drug candidates with potential safety risks. During the last decade, high-content imaging/analysis has emerged as a powerful tool for predictive toxicology as it can be used for identifying and mitigating potential safety risks early in drug discovery. By careful selection of endpoints, some cellular assays can show better predictivity than routine animal toxicity testing for certain adverse events. The perhaps most utilized high-content screening assays for predictive toxicology in the pharmaceutical industry will be presented as well as highlights from the HCA initiative in the MIP-DILI consortium. Multi-parametric imaging of cell health in simple and cost effective model systems can be used to predict human hepatotoxicity and identify potential mechanisms of toxicity, and imaging of bile salt transport inhibition in sandwich-cultured hepatocytes can be used to predict cholestasis inducing compounds. HCA is also useful for genotoxicity studies as imaging of micronuclei formation in simple cell models can be used to detect the genotoxic potential of a compound and elucidate aneugenic or clastogenic mode of actions.

9:30-9:55 Phenotypic Screening of Primary Human Cell Culture Systems to Identify Potential for Compound Toxicity

Keith Houck, Ph.D., Research Scientist, National Center for Computational Toxicology, U.S. Environmental Protection Agency

Assessing phenotypic changes in human primary cells in vitro provides a means to evaluate chemical effects in physiologically-relevant systems that can be useful for compound safety assessment. We evaluated a large library of environmental chemicals, reference pharmaceuticals and failed drugs in complex, primary human cell systems for interactions disrupting critical pathways. Chemical-response signatures derived from 87 endpoints covering functions relevant to toxic and therapeutic pathways were generated. Computational analysis identified abundant chemical clusters showing polypharmacology and potential off-target effects. This abstract does not necessarily reflect EPA policy.

9:55-10:10 Sponsored Presentation (Opportunity Available)

ThermoFisher Scientific10:10-10:55 Coffee Break in the Exhibit Hall with Poster Viewing

Increasing Throughput in
High-Content Screening

10:55 Chairperson’s Opening Remarks

Larry A. Sklar, Ph.D., Director, University of New Mexico Center for Molecular Discovery

11:00-11:25 Phenotypic Screening of Large Chemical Libraries: Balancing Throughput with Relevance

Michael Jackson, Ph.D., Senior Vice President, Drug Discovery and Development, Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute

Image-based assays using quantitative high-throughput microscopy have increased in popularity over the last decade. This is due in part to the information-rich or high-content (HC) nature of the assay, which provides multi-parametric data readouts. In addition, image-based assays enable screening of more complex biological systems, e.g. stem cell-derived models of human disease involving multiple cell types. Despite the attractiveness of this platform, conducting large HC screening campaigns has proven challenging from both a technical and cost perspective. The talk will cover examples of HC assays resulting in large chemical library screens at the Prebys Center, Sanford-Burnham Medical Research Institute’s drug discovery center.

11:25-11:50 Finding the Right Match: Large Scale High-Content Screening on a High-Throughput Imaging System

Annie Mak, Ph.D., Research Investigator, Assay Development and HTS, Genomics Institute of the Novartis Research Foundation

Phenotypic screening in early drug discovery is a powerful approach; yet executing a large scale high-content screen (HCS) in a truly high-throughput format remains a challenge so that the various benefits of a true HTS remain largely untapped. One of the key limiting factors for running HCS is having an imaging platform which can robustly handle a large amount of image acquisition and analysis. At GNF, we have been successful in evolving our screening capabilities to maintain our goal of screening 4 million wells in a single campaign while keeping the opportunity cost low enough to encourage novel and unconventional projects. In this talk, we will discuss our effort in bringing HCS to a high-throughput environment, particularly in terms of exploring imaging systems of existing or developing technologies. Other adjunct pieces such as automations, improved workflows and informatics support will also be discussed, and examples of HCS which would benefit from such systems will be shown.

11:50-12:15 pm Multiplexed High-Throughput Flow Cytometry for GTPases as Druggable Targets

Larry A. Sklar, Ph.D., Director, University of New Mexico Center for Molecular Discovery

GTPases are an important class of ~ 150 cellular regulatory molecules. Our innovative toolset includes multiplexing with color-coded microspheres for high-throughput screening of six or more GTPases simultaneously. The screen identified novel GTPase regulators including NSAIDS which are in drug repurposing clinical trials. Taken together, these studies have identified repurposed drugs as well as new chemical entities selective for class, family and individual family members such as Cdc42, setting the stage for GTPases as druggable targets analogous to kinases.

ThermoFisher Scientific12:15-12:45 Sponsored Presentation

Speaker to be Announced

GE Healthcare Logo12:45-1:30 Luncheon Presentation
Speaker to be Announced 

Data Analysis for High-Content and Phenotypic Screening

1:55 Chairperson’s Opening Remarks

Robert F. Murphy, Ph.D., Carnegie Mellon University

2:00-2:25 Learning How to Put a Cell Together: Inferring the Spatial Relationships between Cell Components

Robert F. Murphy, Ph.D., Ray and Stephanie Lane Professor of Computational Biology and Professor of Biological Sciences, Biomedical Engineering and Machine Learning, and Director, Lane Center for Computational Biology, Carnegie Mellon University

Assembly of structures within a cell frequently builds upon other structures, and may involve transitory participation of proteins such as chaperones. To understand cell organization and how it is perturbed during disease or drug treatment requires determination of how the pattern of each protein depends on others. The number of proteins in a cell makes learning this “order of assembly” a significant challenge. I will describe approaches for automatically learning spatiotemporal dependencies from microscope images and movies.

2:25-2:50 Discovering Unexpected Phenotypes Using Image-Based Profiling

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

Microscopy images contain rich information about the state of cells, tissues and organisms. Our laboratory is extracting patterns of morphological perturbations (“signatures”) from images in order to identify similarities between various chemical or genetic treatments. Our goal is to classify drug mechanisms of efficacy and toxicity, distinguish cancer-relevant proteins, and identify biomarkers of disease. We hope to make perturbations in cell morphology as computable as other large-scale functional genomics data.

2:50-3:15 Systematic Repositioning of Drugs Using Phenotypic Data

Mark Hurle, Ph.D., Senior Scientific Investigator, Systematic Drug Repositioning, Computational Biology, GlaxoSmithKline

Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and compounds can be comprehensively characterized by the changes they induce in molecular entities and observable phenotypes. A systematic integration of these genomic, chemical and textual datasets can then be leveraged with our institutional knowledge of drugs and diseases into a set of testable and viable drug-disease hypotheses.

ThermoFisher Scientific3:15-4:15 Refreshment Break in the Exhibit Hall with Poster Viewing

4:15-4:40 Image Correction and Novel Machine Learning Methods for Phenotypic Discovery

Peter Horvath, Ph.D., Group Leader, Synthetic and Systems Biology Unit, Hungarian Academia of Sciences; Finnish Distinguished Professor (FiDiPro) Fellow, Institute for Molecular Medicine Finland

In this talk I will give an overview of the computational steps in the analysis of a single cell-based high-content screen. First, I will present a novel microscopic image correction method designed to eliminate vignetting and uneven background effects which, left uncorrected, corrupt intensity-based measurements. I will discuss the Advanced Cell Classifier (ACC), a software tool capable of identifying cellular phenotypes based on features extracted from the image. It provides an interface for a user to efficiently train machine learning methods to predict various phenotypes. For cases where discrete cell-based decisions are not suitable, we propose a method to use multi-parametric regression to analyze continuous biological phenomena. Finally, to improve the learning speed and accuracy, we recently developed an active learning scheme which automatically selects the most informative cell samples.

Affymetrix logo large4:40-5:10 QuantiGene Assay: ELISA for mRNA Detection without mRNA Isolation

Lishan Chen, Ph.D., Senior Research Scientist, RNAi Unit, Biochemistry Department, Kyowa Hakko Kirin California, Inc.

QuantiGene®, a signal amplification technology is used for the quantitation of gene expression transcripts. This technology quantitatively measures directly from cell or tissue homogenates without RNA purification, in addition to measuring or visualizing RNA directly in cells with flow cytometry or imaging. We’ve adapted QuantiGene assays to high content analysis. Examples will be given to demonstrate the versatility and the effective detection achieved with the QuantiGene platform in various cell based assays.

ThermoFisher Scientific

5:05-6:05 Welcome Reception in the Exhibit Hall with Poster Viewing

6:00 Short Course Registration

6:30-9:00 Dinner Course*: SC2: Introduction to High-Content Data Analysis
Instructor: Peter Horvath, Ph.D., Group Leader, Synthetic and Systems Biology Unit, Hungarian Academia of Sciences; Finnish Distinguished Professor (FiDiPro) Fellow, Institute for Molecular Medicine Finland 


*Separate registration required


Tuesday, January 27

7:30-8:15 am Breakfast Technology Showcase

Nikon Instruments7:30-7:45 Intelligent Acquisition; Image Analysis Steps Dictate Acquisition Path for Performing Automated HCA Experiments. Case Study: Evaluating Phenotypic Stem Cell Screening  

Ned Jastromb, Senior Application Product Manager, Product and Marketing, Nikon Instruments, Inc.

Improving the efficacy of stem cell derivation methods results in faster production of pure populations. Combining Nikon’s confocal HCA platform and software with live cell detection reagents, we evaluated the stem cell differentiation process, in real-time, devising new strategies for extracting meaningful measurements which should lead to optimized phenotypic screens.

ThermoFisher Scientific7:45-8:15 Sponsored Presentation

Speaker to be Announced

HCA Assay Development for
Drug Discovery

8:25 Chairperson’s Opening Remarks

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

8:30-8:55 Heterogeneity in Drug Discovery and Diagnostics

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

Biologically-relevant heterogeneity has been demonstrated in basic biological processes, drug discovery, drug development and diagnostics. Metrics for identifying and quantifying heterogeneity have been developed and can be easily incorporated into cell and tissue profiling studies. Identification of heterogeneity in phenotypic assays can indicate sub-populations that respond distinctly to perturbagens and can impact the development of lead compounds. Metrics have also been developed for tumor diagnostics that identify distinct microenvironments in multiplexed fluorescence studies of tissue sections.

8:55-9:20 Phenotypic Screening from Image Acquisition to Hit Selection

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

Imaging-based phenotypic screens are able to produce extremely rich data sets with large numbers of extracted features. The analysis of this data has been assisted by a web browser-enabled review and analysis software that combines image data storage and analysis. The analysis of this multivariate screening data is further facilitated with the incorporation of images and data into a high-content screening system providing data normalization, outlier detection, feature selection, secondary analysis and data visualization.

9:20-9:45 High-Content Imaging and Analysis New High Value Assays for Translational Research

Anthony M. Davies, Ph.D., Center Director, Translational Cell Imaging Queensland (TCIQ), Institute of Health Biomedical Innovation, Queensland University of Technology

This talk will cover the advances we have made in the field of advanced assay technologies for high-content imaging. Apart from our already developed 3D assay and bioreactor technologies, we are now moving into incorporating a whole range of new cellular assay technologies into our high-content imaging experimental work-flows. The aim of this work is to make the bench-to-bedside concept a reality by further refining in vitro cell-based assays technologies to a point where the improved physiological relevance will allow for a true convergence between traditional mechanistic cell biology and the very latest clinical research approaches.

ThermoFisher Scientific

9:45-10:45 Coffee Break in the Exhibit Hall with Poster Viewing

10:45-11:10 Identification of Sensitivity Biomarkers and Compound MoA Using High-Content Imaging and Analysis

Yangzhong Tang, Ph.D., Research Investigator, Sanofi

Discovery of promising cancer targets depends on uncovering their biological context and identifying biomarkers in responding patient populations. Gaining such insights as early as possible in the preclinical phase will be highly valuable. We’ve been systematically performing high-content imaging on 641 compounds across a panel of 300 cancer cell lines. The imaging dataset has been combined with the genomic profile of the cancer cell lines. Bioinformatic analysis has helped identify sensitivity biomarkers and assisted with determining the mechanism of action of compounds.

11:10-11:35 Fluorescent Biosensors for Fast Quantification of Membrane Protein Trafficking Activity

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

We develop fluorescent biosensors toolkits for pathways of living cells. Focus is on smart biosensors for high-throughput methods. Our biosensor platform consists of Fluorescence Activating Protein (FAPs) labels that bind fluorogen dyes with large fluorescence increases. Proteins of interest in cells can be easily genetically labeled with FAPs. For example, sensors have been developed to rapidly and selectively track FAP labeled proteins such as GPCRs, ion channels and transporters to and from the surface of cells. Trafficking defects and modulation such as in CFTR are important and provide a new range of targets for drug discovery.

11:35-12:00 pm Targeting Profilin-1, a Cytoskeletal Gatekeeper for Metastatic Outgrowth, by a High-Content Cell Motility Assay

Andreas Vogt, Ph.D., Associate Professor, Computational and Systems Biology, University of Pittsburgh

Profilin-1 is a small actin-binding and -regulating cytoskeletal protein that is downregulated in breast cancers and has tumor suppressor properties. In preclinical models, profilin-1 overexpression inhibits tumor growth, motility, invasion and metastatic colonization, suggesting restoration of Pfn1 expression as a strategy for antimetastatic therapy. In this talk I will describe the HTS implementation and validation of a high-content cell migration assay multiplexed with profilin-1 measurements.

12:00-1:30 Enjoy Lunch on Your Own

Closing Plenary Session:
High-Content and Phenotypic Screening of 3D Cellular Models

1:30 Chairperson’s Opening Remarks

Aron Jaffe, Ph.D., Investigator, Developmental and Molecular Pathways, Novartis Institutes for BioMedical Research

1:35-2:00 Developing and Utilizing 3D Culture Systems for Novel Target Discovery

Aron Jaffe, Ph.D., Investigator, Developmental and Molecular Pathways, Novartis Institutes for BioMedical Research

Target identification and validation have historically relied on immortalized or tumor cell lines grown on plastic. Recent techniques involving growth of cells in three-dimensional matrices have enabled modeling of cellular processes in an environment that more closely resembles the in vivo setting. This presentation will highlight the strategies for designing complex cellular assays for target discovery using medium- and high-throughput screening methods in three dimensions.

2:00-2:25 Leveraging the Use of 3D Spheroid Models in Oncology Drug Discovery

Lesley Mathews Griner, Ph.D., Investigator & Lab Head, Molecular Pharmacology/Oncology, Novartis Institutes for BioMedical Research

2:25-2:50 Novel Methods for 3-Dimensional High-Content Analysis

Daniel V. LaBarbera, Ph.D., Assistant Professor, Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado

The multicellular tumor spheroid (MCTS) model has been used for decades with proven superiority over monolayer cell culture models at recapitulating in vivo tumor growth. Yet its use in high-throughput drug discovery has been limited, particularly with image-based screening, due to practical and technical hurdles. This presentation will describe recent advances that we have developed for volumetric high-content analysis using MCTS suitable for high-content screening drug discovery.

ThermoFisher Scientific

2:50-3:10 Networking Refreshment Break

3:10-3:35 Comparative Analysis of Pharmacological Responses in 3D Tumor Models

Marc Ferrer, Ph.D., Team Leader, Preclinical Innovation, NCATS, NIH

The use of physiologically-relevant three dimensional (3D) cellular systems is being explored as more predictive in vitro tumor models for drug discovery. We sought to further understand and delineate the differences in cytotoxic responses by chemotherapeutics agents in different cellular models of cancer by screening a library of 1912 small molecule chemotherapeutics, both as single agents and in combination. The biological annotation of the compounds screened enabled the identification of key cellular pathways driving chemotherapeutic responses in each of the 3D tumor models tested.

3:35-4:00 Phenotypic Profiling of Intracellular Dynamics in 3D Tissues for Therapeutic Screening

David Nolte, Ph.D., Professor, Physics, Purdue University; President, Animated Dynamics, Inc.

Doppler spectroscopy of intracellular dynamics can extract drug responses from as deep as 1 mm inside living tissue using biodynamic imaging. There are a growing number of different types of 3D tissue models, but not all 3D models are created equal. Multicellular tumor spheroids, co-cultures, organoids, tissue biopsies and engineered tissue matrices all have different structural and cellular morphological differences that can lead to different responses to therapeutic compounds. The leading question is: Which of these responds most like an in vivo response?

4:00 Close of Conference