Monday, September 26th

7:30-8:30 Workshop Registration and Morning Coffee

8:30-8:35 Welcoming Remarks from Conference Director
Julia Boguslavsky, Cambridge Healthtech Institute

8:35-8:40 Chairperson’s Opening Remarks

8:40-9:20 Is There Any Value in Using Gene Expression Profiling for Compound Prioritization and Elucidating Possible Mechanism of Action?
Dr. Timothy Perera, Principal Scientist, Oncology Discovery Research, Johnson and Johnson Pharmaceutical Research and Development 
High-content data sources, such as gene expression profiling, are now commonly used in compound characterization and prioritization. However, the full value of this approach requires a systematic experimental design that is instigated from the start. Some of the issues and benefits of using such a ‘systems biology’ approach that unfolded in a study aimed at uncovering the mechanism of action of a multi-targeted kinase inhibitor will be presented. Further value of this data for identifying ‘responder’ and ‘non-responder’ signatures will also be discussed.

9:20-10:00 High-Throughput Screening, Lead Optimization and Development Candidate Selection Using Gene Expression Profiling
Dr. Jeffery W. Strovel, Staff Scientist, Development, Avalon Pharmaceuticals, Inc.
Gene expression profiling enables us to describe both the target-specific pathway effects as well as the off-target effects that compounds have on disease cells. We have developed a suite of applications for multiparametric gene expression assays to screen compound libraries for novel pathway activities, discriminate amongst screening hits, and select lead compounds for optimization. Following lead selection, we use gene expression microarrays to identify a set of biomarkers that describes the most desired effects of the compound series, and use this core gene set to drive chemical optimization toward the identification of a development candidate. Additionally, gene expression biomarker sets are used in in vivo experiments that accelerate pharmacologic optimization and establish clinical biomarkers to 1) guide dose escalation 2) correlate patient responses with pre-clinical efficacy results, and 3) enrich for responsive patients.

10:00-10:30 Networking Coffee Break

10:30-11:10 Integrated Computational and Experimental Approach for Identifying Compound Mode-of-Action
Dr. Guillaume Cottarel, President, Systems Biology, Cellicon Biotechnologies Inc.
A major challenge in drug discovery is to distinguish the molecular targets of a bioactive compound from the hundreds to thousands of gene products that respond indirectly to changes in the activity of the targets. Here, we present an integrated computational and experimental approach for identifying the gene products and pathways that are targets of a compound. This is achieved by filtering the mRNA expression profile of compound-exposed cells using a reverse-engineered model of the cell’s gene regulatory network. Using this method, we successfully predicted the molecular targets of multiple compounds, including a potential new anticancer compound, PTSB. PTSB inhibits growth in human small lung carcinoma cells and in the test organism (baker’s yeast). In follow-up experiments, we verified that PTSB acts on thioredoxin and thioredoxin reductase, the molecular targets predicted by our algorithm. These findings have validated the algorithm’s capabilities and facilitated investigation of a novel class of therapeutic compounds.

11:10-11:50 Transcriptional Profiling for Drug Candidate Selection
Dr. Simon Plummer, Senior Scientist, Pre-Clinical, CXR Biosciences Ltd.
The assessment of risk using animals is limited by difficulties in data extrapolation to man. Integration of transcriptional profiling with conventional toxicity tests can provide mechanistic information enabling the design of in vitro studies in ‘target’ cells. This facilitates a comparison of toxic effects in rodent and human cells. The paradigm provides a basis for assessment of potential toxicity to man and the comparison/selection of drug candidates.

11:50-1:15 Lunch (on your own) 

1:15-1:45 Technology Solutions Showcase (sponsorship available, contact Arnie Wolfson at awolfson@healthtech.com or 781-972-5431)

1:45-2:25 Exploring Compound Activities Through Pathway Analysis of Expression Profiling Data
Dr. Petra Ross-Macdonald, Senior Research Investigator, Applied Genomics, Bristol-Myers Squibb Co.
It seems that the more we look for drug selectivity, the less we find. Genomic technologies such as expression profiling should dramatically increase our ability to analyze the biological effects of compounds - if we can effectively use the large amounts of data that they produce. At some level, we need to understand the changes that occur. Databases and tools for interpreting profiling data have proliferated recently. To compare several such resources with the benefit of 20/20 hindsight, we applied them to an expression profiling data set from a well-characterized group of compounds. 

2:25-3:05 Activity-Based Profiling of Kinase Inhibitors on Substrate Microarrays
Dr. Jos Joore, VP Array Technologies, Peptide Microarrays, Pepscan Systems
We have developed a method to study the kinome of cells and tissues, meaning a fingerprint of kinase activity. This technology is studied for its usefulness in compound characterization by comparing activity profiles of different kinase inhibitors in a variety of cells and tissues. This method gives a far better insight in the complex interactions that influence the effects of signal transduction modulating compounds, as compared to classical kinase assays on panels of purified kinases.

3:05-3:55 Exhibit Hall Opening, Refreshment Break with Poster and Exhibit Viewing

3:55-4:35 Expression Profiling Revealed Novel Activities of Compounds
Dr. Yan Luo, Senior Group Leader, Cancer Research, Abbott Laboratories
Conventional assessment of compound selectivity is often limited to classes of closely related proteins. Even for the panel of selected proteins that we are able to test in vitro, these proteins may not be in the same physiological state as in cells. All of these factors could result in an inaccurate assessment of compound selectivity. In contrast, gene expression profile analysis could provide a physiological, as well as a thorough and unbiased snapshot of the gene expression changes resulting from compound treatment, and thus, a more accurate assessment of a compound selectivity in cells.

4:35-5:15 Panel Discussion with the Speakers

5:15-6:30 Reception in the Exhibit Hall

For more information please contact: 
Julia Boguslavsky, Conference Director, Cambridge Healthtech Institute
Phone: 781-972-5482 or E-mail: juliab@healthtech.com

For sponsorship information please contact:
Arnie Wolfson at 781-972-5431 or awolfson@healthtech.com.