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Apply informatics tools, science and statistics to extract the most knowledge from medical and clinical data for genome analysis, biomarker detection, and target discovery Monday, April 27 4:00 pm Event Chairperson’s Opening Remarks Cindy Crowninshield, Conference Director, Cambridge Healthtech Institute Keynote Introduction: Rudy Potenzone, Ph.D., WW Industry Technology Strategist for Pharmaceuticals, Microsoft Corporation 4:15 Plenary Keynote Research Computing and Infrastructure Technology
5:00 Welcome Reception in the Exhibit Hall Drop off a business card at the CHI Sales booth for a chance to win 1 of 2 iPod® Videos!
7:00 Networking Event hosted by BiotechTuesday
Tuesday, April 28 7:30 am Registration and Morning Coffee 8:15 Event Chairperson’s Opening Remarks Phillips Kuhl, Co-founder and President, Cambridge Healthtech Institute Keynote Introduction: Ken Buetow, Ph.D., Associate Director, Bioinformatics and Information Technology, National Cancer Institute 8:20 Plenary Keynote
9:00 Keynote Presentation & 2009 Benjamin Franklin Award 9:30 Coffee Break, Exhibit and Poster Viewing in the Exhibit Hall
Biological Data: Modeling & Imaging for Gene Expression 10:50 Track Chairperson’s Remarks Colin Williams, Product Manager, Biology & Bioinformatics and Product Management, PharmaChem, Thomson Reuters 11:00 Going Beyond Genome-Wide Association Studies Andrew Kasarskis, Ph.D., Scientific Director, Genetics, Merck Research Laboratories This talk provides an overview of Merck’s current approaches to translating genome-wide association studies (GWAS) into clinical practice. GWAS have provided a robust set of replicated associations between DNA variation and clinical traits. However, understanding the mechanism by which DNA variation affects disease is often not straightforward. Adding genetics of gene expression study results into the interpretation of clinical GWAS provides mechanistic insight that can be interpreted in the context of network models, with the goal of building predictive models of disease processes. These models then form the basis for informed selection of new biomarkers and drug targets. Construction of effective models based on high-dimensional biological data places introduces unique problems in computing that demand innovation in hardware, algorithms, and software development processes. 11:30 BORA: Biologically Oriented Repository Architecture for Genomic Medicine Hugues Sicotte, Ph.D., Assistant Professor of Medical Informatics, Biomedical Statistics and Informatics, Mayo Clinic The Biologically Oriented Repository Architecture (BORA) mines multiple types of genomics data in the context of clinical information and bioinformatics annotation. Unlike other genomics data mart systems, the BORA system allows arbitrary questions to be asked of the data and goes well beyond the “genome browser”-style of integration that is limited to correlating elements at the same genomics position. The BORA system enables a more mechanistic understanding of complex data sets and can enable the study of the relationships between any genomics data elements, clinical variables, and known or predicted biological relationships. 12:00 Assessment of the Function and Potential Clinical Relevance of Gene Variants from Genome Wide Association Studies Using Workflow-Driven Bioinformatics David Ross, Ph.D., Director, Computational Biology, Celera This talk will demonstrate how workflow driven bioinformatics can enhance the relevance of gene variant biomarkers - delivering insights that would otherwise have been missed. Celera is recognized as being at the forefront of this field and have a deep understanding of the opportunities and pitfalls as well as issues around the integration and analysis of this type of complex biological data. This presentation will provide details of the technology used and lessons learned, and cover the scientific findings around the DEAD-box and Kinesin protein families. Sponsored by
 12:30 Luncheon Presentation Making the Most of Your GWAS Data Michael Rosenberg, Ph.D., Senior Director, Professional Services, Rosetta Biosoftware A growing number of comprehensive genome-wide association (GWAS) data sets is being generated by academic and publicly-funded consortia. Notable examples are the Framingham Heart Study and data released by the Wellcome Trust Case Control Consortium. This abundance of data is creating new opportunities for academic researchers,, and pharmaceutical, biotech and emerging direct-to-consumer diagnostics companies to expand the context and increase the power of their own genetics association research efforts. Organizations are tasked with the formidable challenge of how to make the best use of these data sets, implementing approaches to effectively bring them in-house and integrate with proprietary data. We will address the various opportunities and challenges R&D organizations face when working with public GWAS data. We will discuss how existing and emerging commercial software solutions can help eliminate barriers to extracting scientific value from these data sets and provide examples of data mining approaches.
Biological Data: Modeling & Imaging for Gene Expression (continued) 1:40 Chairperson’s Remarks Stuart Tugendreich, Director, Product Management New Solutions, Ingenuity Systems 1:45 Cancer Epigenomics: A Systematic Approach to Biomarker Discovery and Computational Optimization Christoph Bock, Department of Computational Biology, Max Planck Institute for Informatics The demand for computational support and bioinformatics tools in cancer epigenetics is rapidly increasing, due to complex experimental methods, increasingly genome-wide analysis and the pressure to translate scientific results into clinical practice. Our goal is to develop bioinformatics methodology for addressing these issues, and to implement a set of web services that make powerful algorithms available to typical bench scientists. Recent work on computational epigenetics (performed in conjunction with The Broad Institute) will be presented, highlighting a systematic workflow for optimizing epigenetic biomarker candidates for clinical applications. 2:15 Computational Approaches in Biological Imaging Jean-Christophe Olivo-Marin, Ph.D., Group Leader, Quantitative Image Computational analysis of images is central to the successful use of multidimensional microscopy in post-genomics biomedicine. Molecular medicine, proteomics and functional genomics rely heavily on imaging to study the complex machinery of cell functions and disease-related dysfunctions by high-throughput screenings and in cellulo assays. We will present the latest innovative tools in computer aided biological imagery and exemplify them on successful projects from different areas of biology like cell biology, infectious diseases, development biology and immunology. Technology Highlights Sponsored by
 2:45 Connecting Public and Internal Data using a Gene- and Sequence-Centric Semantic Integration Framework Ilya Kupershmidt, Co-founder and Vice President Products, NextBio Organizations are increasingly looking for ways to leverage combined public and internal data (legacy, current and future) to improve their basic and clinical research programs. NextBio has developed a scientific platform that brings together and correlates large quantities of data from microarray and next-generation sequencing platforms to enable comprehensive and efficient discovery and testing of new hypotheses. In this session we will describe how a semantic integration framework, public and internal gene- and sequence-centric data and a large number of pre-computations enable real time knowledge discovery within NextBio. Sponsored by
 3:00 Putting It All Together: The Acceleration of Biomarker Qualification in Drug Discovery Jonathan Usuka, Ph.D., M.B.A., Senior Director, Life Sciences, Accelrys, Inc.
3:15 Refreshment Break, Exhibits and Poster Viewing in the Exhibit Hall
Discovery Informatics and Platforms 3:45 You’re Using Your Computer Wrong: Semantics in Pharma R&D Ted Slater, Senior Manager, Pfizer Worldwide Technologies Most informatics efforts are aimed at data integration, but data integration is insufficient to enhance our ability to accurately predict drug efficacy and safety. To reach the next level in R&D, we must move beyond data integration to the point where computers generate hypotheses. This talk will provide a view of a practical, semantics-based solution which provides for automated reasoning over pharmaceutical knowledge bases, and which has useful emergent properties such as streamlined data interoperability and a universal platform for knowledge management. 4:15 CBIP: Successfully Implementing a Large-Scale Automation and Informatics Platform for Academic Probe Discovery David DeCaprio, Associate Platform Director for Chemical Biology and Novel Therapeutics, The Broad Institute Raza Shaikh, Associate Director of Informatics, Chemical Biology Platform, The Broad Institute Over the past two years, The Broad Institute set out to completely rebuild its high throughput screening and probe discovery platform using state of the art automation and informatics tools. The platform uses an electronic notebook as the rich front-end for recording chemical and biological information integrated with a web-based LIMS system. Our innovative approach to engineering the solution included informatics participating in Factory Acceptance Tests (FAT) and building functionality to align with Site Acceptance Tests (SAT). This approach coupled with just-in-time approach to software engineering has allowed us to build a comprehensive platform. Attendees will learn the issues and decisions involved in building an informatics platform that caters to the needs for a diverse set of processes. Sponsored by
 4:45 RISe – Research Informatics System at Elan 5:15 2009 Best of Show Awards in Exhibit Hall 6:15 Exhibit Hall Closes 6:30 2009 Bio-IT World’s Best Practices Awards/Dinner
Wednesday, April 29 7:30 am Registration and Morning Coffee 8:00 Event Chairperson’s Opening Remarks Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World 8:05 Plenary
Keynote
8:45 Keynote Panel
9:45 Coffee Break, Exhibit Viewing, Vendor Theater Presentations, and Poster Competition in the Exhibit Hall
Disease Pathway Solutions 10:55 Track Chairperson’s Remarks Yaron Turpaz, Ph.D., Director of Integrative Computational Sciences, Lilly Singapore Centre for Drug Discovery
Sponsored by
 11:00 Use of Pathways Solutions to Gain Extensive Domain Knowledge of Disease Related Pathways and Targets Stuart Tugendreich, Director, Product Management New Solutions, Ingenuity Systems Cellular behavior in health and disease is controlled by the events such as activation, repression and interaction of signal transduction pathways. This presentation will demonstrate how IPA can be used to identify molecular pathways and individual proteins that regulate disease-related processes. 11:30 Applied Diseaseomics: A Generalized Approach for Assembling Gene and Disease-Related Feature Networks to Enable Disease-Specific Inferential Reasoning for Causal Factors and Candidate Therapeutics Bruce Aronow, Ph.D., Professor of Pediatrics; Scientific Director, Center for Computational Medicine, Biomedical Informatics, Cincinnati Children¹s Hospital Medical Center, University of Cincinnati This talk will outline methods for rapid network-based aggregation of current knowledge associated with specific diseases or disease types. By extending connections of known associated genes, phenotypes, or similar diseases, a variety of comparative feature enrichment analyses can be performed that allow connectivity to pathways, etiologies, and therapeutics. Reasoning-based approaches are thereby enabled that can shed light into operative underlying disease processes. These analytical and modeling approaches can then help to suggest candidate modifiers that may be systematically evaluated such as variant genetics, etiologic factors, and novel therapeutic agents. 12:00 Inferring Causal Effects with Targeted Maximum Likelihood Mark van der Laan, Ph.D., Professor of Biostatistics and Statistics, UC Berkeley We present a general targeted maximum likelihood statistical methodology that targets a user supplied variable importance or causal effect of a variable/treatment on an outcome. This method provides an optimal way in extracting the relevant information and dealing with the curse of dimensionality, while preserving the maximum likelihood principle. We illustrate this method for the purpose of assessing the effect of mutations in the HIV virus that cause resistance to a particular drug, and for assessing a causal effect of a treatment in a clinical trial and survival outcome, in the presence of informative censoring. We also apply the targeted maximum likelihood methodology to case control data providing a new way of assessing causal effects of single nucleotide mutations on phenotypes of interest. 12:30 Luncheon in the Exhibit Hall 2:00 Exhibit Hall Closes
Leveraging Data and Standards 1:55 Chairperson’s Remarks 2:00 Pharma’s Role and Possible Approaches to Driving Data Standards for Early Stage Research Martin D. Leach, Ph.D., Executive Director, MRL IT Basic Research & Biomarkers, Merck & Co. An increasing trend across the pharmaceutical and biotechnology industry is an increase in the leverage of external research organizations and integrating these ‘virtual sites’ into the overall research pipelines. To accomplish this, there needs to be a standardization of the methods and data formats for biology and chemistry. There is consensus for the need and development of data standards for early stage research and some specific successes, such as those around the transmission and management of gene expression data. Overall progress, however, has been poor in the development and adoption of additional standards. There are lessons to be gained from the clinical data standard realm and there needs to be a call to arms to apply these lessons to needs of early research. 2:30 The Neurodegeneration Knowledge Sphere: Integrated Software for Preclinical Drug Development Steven Perrin, Ph.D., Chief Scientific Officer, ALS Therapy Development Institute The ALS Therapy Development Institute has created a Neurodegeneration Knowledge Sphere to monitor and track all aspects of the preclinical therapeutic discovery process allowing unprecedented data access to scientists in the user community. Attendees will learn how to design and implement the informatics infrastructure to track all aspects of preclinical drug development from discovery to in vivo testing. Additionally, attendees will learn how data visualization tools can assist scientific groups in the organization to leverage the data for portfolio prioritization and management. 3:00 Scientific Intelligence in R&D - Knowledge Integration across Discovery, Pre-clinical, and Clinical Development (Joint with IT Infrastructure and Operations & Clinical and Medical Informatics Tracks) John Apathy, Assistant Vice President, Business Systems and Processes - Discovery, PreClinical, and Vaccines, Wyeth 3:30 Service Oriented Architecture – A New Data Sharing Architecture (Joint w/IT Infrastructure and Operations, Clinical and Medical Informatics, & eHealth Solutions Tracks) Robert Lundsten, Director of Biorepository, Feinstein Institute for Medical Research 4:00 Conference Adjourns |
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Chris Dagdigian, Founding Partner and Director of Technology, BioTeam,
Inc.
Eric E. Schadt, Ph.D., Executive Scientific Director, Genetics, Rosetta Inpharmatics/Merck Research Labs; Vice President and Chief Scientific Officer, Sage 
Clifford Reid, Ph.D., Chief Executive
Officer, Complete Genomics, Inc.
