8:50 Statistical and Computational Pharmacogenetics: Detecting Genes for Drug Response
Ronging
Wu, Ph.D., Professor, University of Florida
Research Foundation Professor, Statistics,
University of Florida
I will present a conceptual framework for computing genes and genome for drug response by integrating mathematical and chemical aspects of drug reactions in the body. With this framework, specific DNA sequence variants can be identified on the basis of the test of a few parameters that define the shape and pattern of drug responses, which thus enhances the precision of parameter estimation as well as biological and clinical relevance in pharmacogenetic and pharmacogenomic research.
9:20 Clotting, Cascades, and Computers - Systems Biology in Personalized Medicine
Michael Roehrl, M.D., Ph.D., Pathology and Laboratory Medicine, Massachusetts General Hospital
The human blood clotting system is a complex and highly regulated network of biomolecular interactions. We demonstrate in this talk how data from careful biochemical measurements can be integrated into quantitative and predictive computational models of blood coagulation. Pharmacological manipulation of blood clotting has tremendous medical and pharmaceutical ramifications. Millions of patients receive the oral anticoagulant Coumadin to prevent fatal thromboembolic events. Yet personalized Coumadin dosing is both cumbersome and expensive (requiring frequent blood draws and lab testing) and potentially dangerous. Coumadin is among the top 10 drugs with the largest number of serious adverse event reports submitted to the FDA. We show how a novel Systems Biological approach can be used in the clinical setting to personalize Coumadin dosing and to achieve safe therapeutic goals. Additional specific examples of optimized clinical management using Systems Biology in clinical medicine will be discussed, including both bleeding disorders (hemophilias) and clotting disorders (e.g., Factor V Leiden and protein C or S deficiencies).
9:50 Networking Coffee Break, Poster and Exhibit Viewing
10:45 Identify Pathway Specific Gene Signatures for
Cancer Prognosis Using Gene Expression
Profiling Data
Dan Li, Ph.D., Principle Research Scientist, Informatics, Integrative Biology, Eli Lilly and Company
Neoplastic transformation and progression is driven by deregulated cellular pathways that control cell fate, growth, differentiation and survival. Although significant progress has been made to identify and characterize oncogenes, tumor suppressors and the molecular pathways that they
regulate, it remains largely unclear what pathways play a critical role in the development of different tumor types. Post-genomic era technology in gene expression profiling has provided a powerful tool to study gene regulations in cancers at the molecular level. In this study, we developed and applied a novel approach to derive gene signatures for cancer prognosis in the context of known biological pathways.
11:15 Genome-Wide Transcriptional Fingerprinting of Hepatotoxicity Regulatory Networks Using
Multiplex Parallel High-Throughput ChIP-on-Chip Assays
Jeff Falk, Ph.D., Director, Technology Applications, Molecular Biology, Aviva Systems Biology
A genome-wide transcription factor mapping consortium is currently being assembled to facilitate the dissection of key disease and toxicology-related regulatory networks. The consortium will facilitate global identification of key toxicity and disease-related networks and biomarkers by providing reference fingerprints of transcription factor-mediated pathway modulations in key tissues that can then be compared with similar profiles derived from disease-related or therapeutic compound treated samples. We will describe the initial phase of experiments utilizing our next generation ChIP-on-chip technology for mapping of transcriptional networks that pinpoint critical pathways and biomarkers associated with hepatotoxicity. These studies were performed utilizing Affymetrix high density tiling arrays that have been incorporated into an automated high throughput multiplex parallel ChIP-on-Chip system used in conjunction with our internal antibody collection covering all human transcription factors and co-factors. In these initial studies, hepatotoxicity fingerprints were generated by transcriptional mapping of pathways mediated by 50 transcription factors in liver. The results demonstrate the utility of these transcriptional mapping studies in elucidating key pathways, regulatory networks, and biomarkers that have implications in predicting the hepatotoxicity of potential therapeutic drugs.
11:45 Systems Biology of Melanoma
William Kaufmann, Ph.D., Professor, Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill
I propose to describe a model of human carcinogenesis that is based upon the interaction of an external stress (sunlight) with mutations in the MAPK signaling pathway in melanocytes to cause deletions in the CDKN2A tumor suppressor locus that encodes p16INK4A and ARF. Systems biology approaches to the model include generation of genetic and physical interaction networks to model the DNA damage response, global analysis of gene expression to identify melanoma subtypes, and mathematical models of nucleotide excision repair and G2 DNA damage checkpoint responses.
12:15 pm Close of Morning Session
12:30 Luncheon Technology Workshops
(Sponsorships Available) or Lunch on Your Own
1:45 Chairperson’s Remarks
1:50 Speaker TBA
2:20
Validation
of Physiologic Models and Analysis of Uncertainty
Richard Ho, Ph.D., Principal, Rosa &
Co.
2:50 Human Cell Systems Biology: A Practical
Approach for Drug Discovery
Ellen Berg, Ph.D., Chief Scientific Officer, Research, BioSeek, Inc.
The goal of systems biology in drug discovery is to predict drug or target efficacy, safety and pharmacology prior to clinical testing, reducing the cost and time of drug development. Assay systems that model human disease biology more effectively and also meet the throughput needs of drug discovery research can help achieve this goal. Biologically Multiplexed Activity Profiling (BioMAP®) involves the statistical analysis of disease biomarker endpoints generated from primary human cell-based disease models, BioMAP systems, for drug selection and characterization. BioMAP systems have been developed for a broad range of human disease and tissue biology including inflammatory, autoimmune, cardiovascular, respiratory and cancer biology. Applications for 1) target prioritization; 2) screening hit and phenotypic hit prioritization; 3) lead optimization and candidate selection; and 4) drug repositioning will be presented.
3:20 Networking Refreshment Break, Last Chance for Poster and Exhibit Viewing
4:00 Poster Awards in the Exhibit Hall
