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Use of model-simulated therapeutics, in silico tools, drug discovery and development, and predictive bio-simulations & models to explore and understand chemical and biological systems Monday, April 27 4:00 pm Event Chairperson’s Opening Remarks Cindy Crowninshield, Conference Director, Cambridge
Healthtech Institute 4:15 Plenary
Keynote
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 iPods ®!
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
in silico Modeling and Simulation Tools 10:50 Track Chairperson’s Remarks John Russell, Executive Editor, Bio-IT World 11:00 Drug Salvaging with Optimata Virtual Patient Mark Tepper, Ph.D., Chief Executive Officer, Optimata We have developed in silico models of drug-patient dynamic interactions to optimize the clinical development of oncology compounds. Using the Optimata Virtual Patient (OVP) technology, we have been able to accurately predict the optimal match between clinical indication, patient sub-population and drug schedule for a previously discontinued oncology compound. We will present a case study in which the OVP technology successfully salvaged a previously discontinued prostate cancer drug by identifying a new dosing regimen and drug combination. This new drug treatment protocol is predicted to extend the survival of prostate cancer patients by over 3 fold over five years. 11:30 Utilizing Virtual Populations to Reduce Risk in Clinical Studies Alex L. Bangs, Co-Founder & CTO, Entelos, Inc. New methods and technologies have been developed to analyze existing clinical data sets and create virtual populations - large sets of individual mechanistically simulated virtual patients that statistically mirror clinical populations. These virtual populations have been used to simulate clinical trials on novel therapeutics and analyze simulated trial results for potential biomarkers. The methods and technology will be discussed as well as specific examples from completed research projects. 12:00 in silico Modeling and Simulation Using Automated Fitting Algorithms to Optimize Antibody Study Design Serge Guzy, Ph.D., Principal Scientist, Business Development, XOMA Few companies use automated processes to optimize trial
design. In addition, non optimal algorithms are used for that purpose. The main
objective of our work is to provide the optimal trial design for future
oncology experiments by running one series of simple scripts that would
generate automatically output files with the optimal information for decision
making. This talk will discuss the special tools developed that address
statistical optimization challenges, save time and money, increases the
probability of detecting true positives, and affords improved decision making. 12:30 Luncheon Presentation (Sponsorship Opportunity Available)
in silico Modeling and Simulation Tools (continued) 1:40 Chairperson’s Remarks John Russell, Executive Editor, Bio-IT World 1:45 Modeling and Simulation: Taking the Clinic into the Lab and Back Again Michael N. Liebman, PhD, Managing Director, Strategic Medicine, Inc There is a significant opportunity to apply modeling and simulation into clinical application which goes beyond its use in biomedical/translational research. We have focused on identifying critical clinical issues that directly impact patient treatment, i.e. clinical decision support, and have developed and applied these modeling methods in the diagnosis and treatment of breast cancer, coagulation disorders and cardiac transplant matching, utilizing pathway-based approaches and both neural networks and Bayesian analysis to analyze pathology data as well as SNP's, all integrated with clinical data and outcomes and will present several case studies. 2:15 Talk X: Computational Architecture for Modeling the Cell Shiva Ayyadurai, Ph.D., Fulbright Scholar & Faculty Lecturer, M.I.T.; Executive Director, International Center for Integrative Systems Research A grand challenge of predictive and in silico Medicine is to create a model of the whole cell. Over the past decade, the description of biomolecular pathways is rapidly moving from simple diagrammatic representations to detailed mathematical models. This trend provides the opportunity to create a model of the cell by integrating the individual biological pathway models. Current approaches to modeling the whole cell are not scalable to integrate the large number of pathway models, each of which may be in different formats and under constant change. In this talk, we present CytoSolve a new approach that provides a scalable computational platform for integrating multiple biological pathway models. 2:45 Virtual Screening for R-Groups
Sponsored by
Richard Cramer, Ph.D., Senior Vice President, Science & Chief Scientific Officer, Tripos 3:15 Refreshment Break, Exhibits and Poster Viewing in the Exhibit Hall
Modeling Toxicity Data 3:45 Unlocking Toxicity Data for Structure-Activity Modeling By Semi-Automated Extraction from Study Reports Nigel Greene, Ph.D., Associate Research Fellow & Head of Computational Toxicology, Pfizer David Milward, Ph.D., Chief Technology Officer, Linguamatics Many of the results obtained from toxicity tests are stored in study report documents that cannot be easily interrogated to allow toxicity modeling, such as the creation of structure-activity relationships. Fully manual extraction of structured data, including numerical values, is time consuming and expensive. This collaboration between Pfizer, Linguamatics and Lhasa has resulted in a semi-automated method which involves text mining based on natural language processing (NLP), followed by interactive curation. This talk will provide attendees an understanding of how NLP-based text mining can unlock value in legacy safety studies to support current decision-making. 4:15 Cheminformatics Approaches for Toxicity Predictions in Drug Discovery Florian Nigsch, Ph.D., University of Cambridge and Novartis Institutes for BioMedical Research Our work combines data and methods from different areas—cheminformatics, toxicology, pharmacology—to gain new insights into (un)desired actions of small molecule modulators of biological pathways. Developing models for the prediction of toxicological outcomes is vital due to changing legislation regarding drug safety as well as reduction in the use of laboratory animals. We will show the limitations inherent in such computational approaches and highlight the benefits and relevance to drug discovery projects. Attendees will understand the: development process and what can be learned from target prediction models in a toxicological context, limitations in the underlying data, overview of data integration required in order to build and use such models, presentation of the methodology that was used and how it can be extended. 4:45 Causal Network Modeling in Drug Toxicity: Predicting the Risk of Idiosyncratic DILI and Hemangiosarcoma in Animal Models Keith O. Elliston, Ph.D., Co-Founder, President and Chief Executive Officer, Genstruct, Inc. 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 A special plenary panel discussion featuring:
9:45 Coffee Break, Exhibit Viewing, Vendor Theater Presentations, and Poster Competition in the Exhibit Hall
Systems Biology, Systems Integration & LIMS 10:45 Track Chairperson’s Remarks 11:00 A Chemical Systems Biology to Drug Discovery:
Lei Xie, Ph.D., Principal Scientist, San Diego Supercomputer Center, University of California, San Diego Attendees will learn how our methods will help shift one-drug-one-target drug discovery process to a new paradigm of network pharmacology. We have developed a chemical systems biology approach to reconstructing and simulating protein-ligand interaction networks on a genome scale and applied it to elucidating molecular mechanisms of drug side-effects and repurposing pharmaceuticals to target different pathways. Attendees will learn how systems biology can play key roles in the future of drug discovery, side-effects can be modulated by the fine-tuning of the off-target binding network, and drug repurposing can be explored systematically and efficiently using chemical systems biology approaches. 11:30 Clotting, Cascades, and Computers - Systems Biology in Personalized Medicine Michael H. 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. This talk demonstrates 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 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. 12:30 Luncheon in the Exhibit Hall 2:00 Exhibit Hall Closes
Case Studies and Lessons Learned from Your Peers 1:55 Chairperson’s Remarks Jeremy L. Jenkins, Ph.D., Research Investigator, Lead Discovery Informatics, Novartis Institutes for BioMedical Research 2:00 Power to the People: Integrating Data and Analysis in One Easy Application Derek Debe, Ph.D., Senior Group Leader, Scientific Informatics and Automation, Abbott Laboratories This talk discusses the successful development and deployment of a Drug Discovery data integration and analysis platform at Abbott Laboratories. Specific use case examples will be presented, including functionality useful for Hit-to-Lead analysis and Lead Optimization efforts. 3:00 Predictive In-Silico Science: Shifting the Discovery Paradigm Yossi Cohen, M.D., VP R&D, Compugen We share insights into how new in silico predictive approaches differ from the traditional discovery approaches, and why it has the potential to predict high-quality candidates in a much more efficient and cost-effective manner. Through examples of some of Compugen's successes in drug candidate discoveries, this talk will demonstrate how the predictive in silico approach is steadily revolutionizing the R&D paradigm of the industry. We will highlight the potential of in silico science to increase success rates in the preclinical stages of drug development and how collaborative efforts can help stem clinical stage attrition. 3:30 "Virtual Fragment Linking": An Approach to Identify Potent Binders from Low Affinity Fragment Hits Meir Glick, Ph.D., Research Investigator II, Lead Discovery Informatics, Novartis Institutes for BioMedical Research We explore the possibilities of using fragment-based screening data to prioritize compounds from a full HTS library, a method we call virtual fragment linking (VFL). The ability of VFL to identify compounds of nanomolar potency based on micromolar fragment binding data was tested on 75 target classes from the WOMBAT database and succeeded in 57 cases. Further, the method was demonstrated for seven drug targets from in-house screening programs that performed both FBS of 8800 fragments and screens ofthe full library. VFL captured between 28% and 67% of the hits (IC50 < 10?M) in the top 5% of the ranked library for four of the targets (enrichment between 5-fold and 13-fold). 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.
