4:00pm Event Chairperson’s Opening Remarks
Cindy Crowninshield, Conference Director, Cambridge Healthtech Institute

4:15 Informatics: Integration & Convergence
John Reynders, Ph.D.,Vice President & Chief Information Officer,Johnson & Johnson, Pharma R&D

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!

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7:30 am Registration and Morning Coffee

8:15 Event Chairperson’s Opening Remarks
Phillips Kuhl, Co-founder and President, Cambridge Healthtech Institute 

8:20 Drug Development: Evolving Challenges and Opportunities 
Joshua Boger, Ph.D., President & Chief Executive Officer, Vertex Pharmaceuticals, Inc.

9:00 Keynote Presentation & 2008 Benjamin Franklin Award
Robert Gentleman, Ph.D., Head of Program in Computational Biology, Fred Hutchinson Cancer Research Center

9:30 Coffee Break, Exhibit and Poster Viewing in the Exhibit Hall

10:50 Track Chairperson’s Remarks
John Russell, Executive Editor, Bio-IT World

11:00 Model-Simulated Design of Cancer Therapies
Computational biology is improving our understanding of complex biological systems. Using very large biological datasets of cell signaling, we have constructed detailed, mechanistic models. These may be used to predict net-work responses to targeted therapeutics such as monoclonal antibodies and small molecule inhibitors. Using growth factor signaling as an example, we will present how computational modeling can be used to simulate the best therapy with single agents or combinations of targeted inhibitors.
Ulrik Nielsen, Ph.D., Vice President, Research, Merrimack Pharmaceuticals, Inc.

11:30  Pushing Data-driven Models Beyond Their Breaking Point
Kevin A. Janes, Ph.D., Department of Cell Biology, Harvard Medical School
The earliest and most-immediate goal of many modeling efforts is a model that is validated and predictive, but what can be done afterwards? In this talk, I will present a new approach that we have developed, called “model-breakpoint analysis”, which involves forcing a model to the point of failure and then analyzing the failure mechanisms to propose new biological hypotheses. Using a data-driven model of cytokine-induced apoptosis, model-breakpoint analysis correctly identified context-specific cellular responses to combinations of small-molecule inhibitors and receptor antagonists. The analysis further helped to explain phenotypes from genetic perturbations that would otherwise appear counterintuitive. Our work illustrates how one can learn as much from the failures of a model as from its successes.

12:00 pm The Future of Systems Biology in Drug Discovery 
The molecular characterization of pathological pathways requires a combination of computational biology and in-teraction discovery techniques. Future discoveries will emerge from computational modeling of pathological pathways using a variety of information sources relevant to human pathophysiology, from protein interactions to small metabolites. This seed model will be extended by including information from other organisms and deter-mining missing data. The final step will be to perturb the system to confirm that it behaves as predicted by the model. This will revolutionize drug discovery, along with other applications such as prediction of adverse events and new indications for existing drugs. This talk will present the most recent examples and solutions regarding target discovery, adverse event prediction, and repurposing of existing drugs. 
Jordi Naval, CEO, Anaxomics Biotech

12:30 Luncheon Workshop (Sponsorship Available) or Lunch on Your Own

1:45 Systems Approach to Drug Development: Bio-Simulation and Bio-Mathematics Drug development needs to find innovative ways to increase the probability of success. Disease modeling using bio-simulation and bio-mathematics is a promising approach, however succeeding in this area requires an inter-disciplinary effort involving biologists, chemists, mathematicians and engineers. This session will discuss the use of mathematical and/or statistical models for diseases, and for variations amongst individual patients, that would greatly facilitate the task of predicting how a particular drug would interact with a patient population. Moderator: M. Vidyasagar, Ph.D., Executive Vice President, Tata Consultant Services Panelists:  Zvia Agur, Ph.D., President, Institute for Medical BioMathematics (IMBM); Chairperson and CSO, Optimata David de Graaf, Ph.D., Head, Systems Biology, Pfizer Inc. Vikram Sinha, Ph.D., Head, Global PK/PD & TS - U.S. , Lilly

3:15 Refreshment Break, Exhibit and Dedicated Poster Viewing

5:15-6:15 2008 Best of Show Awards/Reception in the Exhibit Hall

6:15 Exhibit Hall Closes 

7:00 2008 Bio-IT World’s Best Practices Awards/Dinner

7:30 am Registration and Morning Coffee

8:00 Event Chairperson’s Opening Remarks
Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World 

Keynote Introduction: 
Ron Ranauro, President and CEO, GenomeQuest, Inc. 

8:05 Personalized Genetics: Advancements & Driving Change
Linda Avey, co-Founder, 23andMe, Inc..

8:45 The Future of Personal Genomics George Church, Ph.D., Professor of Genetics and Director of the Center for Computational Genetics, Harvard Medical School Dietrich Stephan, Ph.D., Co-founder and Chief Science Officer, Navigenics, Inc. Jeffrey M. Drazen, M.D., Editor-in-Chief, New England Journal of Medicine; Distinguished Parker B. Francis Professor of Medicine, Harvard Medical School Fred D. Ledley, MD, Professor and Chair, Bentley College; Founder and Chairman, My Genome John Halamka, MD, MS, CIO, Harvard Medical School Linda Avey, co-Founder, 23andMe, Inc.

9:45 Coffee Break, Exhibit Viewing, Vendor Theater Presentations, and Poster Competition in the Exhibit Hall

10:45 Track Chairperson’s Remarks
M. Vidyasagar, Ph.D., Executive Vice President, Tata Consultancy Services

11:00 An Integrated Framework for Multiple Myeloma Research Joint with Track 2
The Computational Biology and Functional Genomics Laboratory at the Dana Farber Cancer Institute, in collabo-ration with InforSense, is developing a novel web-based application to support Multiple Myeloma research. The application provides research scientists an integrated view of clinical and laboratory data that allows them to better understand the relationships that exist. Scientists can identify the mechanisms that can be linked to poor response to chemotherapy and use that information to develop new therapeutics. This application supports a range of research activities performed by various users, including study designers, biologists, statisticians and software developers. Its functionality allows researchers to utilize features that support their specific needs: Study designers can check participant metrics and sample availability, biologists can access statistician data and link to public-domain data sources, statisticians can export formatted data sets, and developers can rapidly de-velop and deploy new applications to accommodate evolving research needs. In this talk, we will cover the spe-cifics of the application, as well as the ROI that has been achieved in terms of both cost and science. 
John Quackenbush, Ph.D., Professor of Biostatistics and Computational Biology, Dana-Farber Cancer Institute

11:30 Immunogenicity Assessment of Protein Therapeutics 
With over 50 therapeutic proteins on the market, and several hundred in clinical trials, the biotherapeutics are currently the largest growing drug segment. Over the past years, the challenges related to protein drugs become more obvious, and predictive methods to assess immunogenicity have become of age. This presentation will dis-cuss strategies for pre-clinical prediction of immunogenicity with in silico tools, and evaluate how in silico tools can be used to optimize the protein engineering and lead selection process.
Qingyu Cao, Ph.D., Business Development, AlgoNomics NV

12:00 pm Innovations in Small Molecule Selection and in the Preclinical Pipeline: the PREDICT Methodology
The application of structure-based in silico methods to drug discovery is still considered a major challenge, particularly when the x-ray structure of the target protein is unknown. At Epix we have successfully overcome this dearth of structural information of certain membrane embedded drug targets by developing a novel modeling methodologies as well as in silico screening and optimization algorithms that are uniquely suited to membrane embedded drug targets. This talk will review The PREDICT™ program and describe Epix’s approach for lead optimization using a suite of algorithms to navigate the chemistry in a multitude of possible pathways throughout the optimization process.
Sharon Shacham, Ph.D., MBA, Senior Vice President, Drug Development, Epix Pharmaceuticals, Inc.

12:30 Luncheon in the Exhibit Hall

2:00 Exhibit Hall Closes

2:00 Integrating Phospho Proteomic Data into Causal Models of Cancer Drug Mechanisms 
The development of targeted cancer therapies has focused largely on the identification of antagonists for protein kinases and phosphatases that regulate networks and pathways leading to cell proliferation and apoptosis. The development of large-scale phospho proteomic measurements using mass spectrometry presents a valuable re-source for reconstructing the altered signaling networks that result from drug treatment. This talk will present the integration of these large-scale measurements into causal models of cell proliferation, to elucidate network changes that result in sensitivity (and resistance) to targeted cancer therapeutics.
Christian Reich, Vice President, Scientific Research, Research, Genstruct, Inc.

2:30 Developing Genomic Predictive Models for Common Diseases
Genetic prediction is at the heart of personalized medicine. The promise of new tailored medicines rests on our ability to forecast disease risk and treatment response based on a patient’s genetic makeup. However, common diseases are likely to be caused by the interaction of multiple genetic factors. While current SNP microarrays can query virtually all of the variations in the human genome, current methods tend to focus on one SNP at a time. This talk will show how to identify the multigenic profiles underpinning complex traits and to develop prognostic models to predict individual risk based on genetic variations. We will describe the use of Bayesian networks for developing models and introduce a novel set of techniques and search algorithms specifically tailored to the analysis of genome-wide association studies. Applications to the identification of genomic predictive models to common diseases, such as stroke, asthma and nicotine dependence, will be described.
Marco Ramoni, Ph.D., Assistant Professor, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School

3:00 GenoCAD: Computer-Assisted Design and Fabrication of Synthetic Genetic Systems 
A gap exists between the few academic groups who have the capability of running small-scale, proof-of-concept projects in synthetic biology and the people who could identify and benefit from biomedical and industrial appli-cations of this technology. We are creating the infrastructure for non-specialists to design large-scale genetic systems that could be used in basic biological research or product development programs. We are adapting the workflow developed by the electronics industry to automate the design and fabrication of electronic circuits, to the design and assembly of Very Large Scale Integrated genetic systems. This talk will describe the molecular tools, algorithms, and software applications in development that will make the computer assisted design and fab-rication of genetic systems a reality within five years.
Jean Peccoud, Ph.D., Associate Professor, Virginia Bioinformatics Institute, Virginia Tech

4:00 Conference Adjourns