Final Agenda:

Track 6 provides in-depth modeling approaches from in silico to in vivo with an emphasis on drug discovery, ADME predictions, and systems medicine leading to effective translation into the clinic.

TUESDAY, APRIL 12

7:00 am Workshop Registration and Morning Coffee

8:00 - 4:00 pm Pre-Conference Workshops*

*Separate Registration Required.

2:00 - 6:00 Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge Healthtech Institute

Sponsored by
4:05 Keynote Introduction
Chris Blessington, Life Sciences Solutions Architect, Isilon

Plenary Keynote
4:15 Making the World’s Knowledge Computable

Stephen Wolfram, Ph.D., CEO, Wolfram Research; Creator of Wolfram|Alpha

Sponsored by
5:00 Welcome Reception in the Exhibit Hall and Poster Viewing

WEDNESDAY, APRIL 13

7:00 am Registration and Morning Coffee

8:00 Event Chairperson’s Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

Sponsored by
 8:05 Keynote Introduction 
Grant Stephen, CEO, Tessella, Inc.

Plenary Keynote
8:15 Interacting with Complex Information Landscapes: Integration and Next Generation User Interfaces

Bryn Roberts, Ph.D., Global Head, Informatics, Pharma Research and Early Development, F. Hoffmann-La Roche Ltd.

8:45 Benjamin Franklin Award/Presentation: Jonathan Eisen, Ph.D., Professor, Genome Center, University of California, Davis

9:10 Best Practices Awards Program

Sponsored by
9:45 Coffee Break in the Exhibit Hall and Poster Viewing

Systems Medicine

10:50 Chairperson’s Remarks
Mary Ann Brown, Executive Director, Conferences, Cambridge Healthtech Institute

11:00 Featured Presentation
Systems Medicine - Where East Meets West: The Future of Personalized Health

V.A. Shiva Ayyadurai, Ph.D., Fulbright Scholar & Faculty Lecturer, Department of Biological Engineering, Massachusetts Institute of Technology

Modern medicine has provided great discoveries and tools for humanity over the past several decades, particular in the biomolecular sciences. Traditional and ancient systems of medicine, developed over 5,000 years, offer an interconnected approach to understanding the whole human physiome and its interrelationships to the ecosystem. Systems Medicine provides an integrative platform, for bridging ancient and modern, East and West, science and tradition to deliver a personalized health, as never before, to each one of us.

11:30 Bridging the Gap between Systems Biology and Medicine

Gilles Clermont, Department of Critical Care Medicine, University of Pittsburgh School of Medicine

12:00 pm Linking Disease Genetics to Future Therapeutics through Disease Allele/Drug Interaction Screens
Stanley Y. Shaw, M.D., Ph.D., Co-Director, Chemical Biology, Center for Systems Biology, Massachusetts General Hospital; Assistant Professor, Medicine, Harvard Medical School
Translating discoveries in disease genetics into functional insights and therapies has proven challenging.  We performed a synthetic interaction screen in human patient-derived cells, and identified genes and small molecules that interact with a monogenic diabetes mutation. This approach applies the logic of model organism genetic interaction screens to study pathway interactions in patient cells, and may help assign function to disease mutations of unclear mechanism, and suggest novel therapeutic approaches.

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

Data Generation

1:40 Chairperson’s Remarks

V.A. Shiva Ayyadurai, Ph.D., Fulbright Scholar & Faculty Lecturer, Department of Biological Engineering, Massachusetts Institute of Technology

1:45 Featured Presentation
The Role of Variation in Cell Fate Determination - Click here for Podcast 

John Quackenbush, Ph.D., Professor, Biostatistics and Computational Biology, Cancer Biology Center for Cancer Computational Biology, Dana-Farber Cancer Institute

The history of biomedical research has been driven by one basic and extraordinarily successful question: Given a measurement for an experimental and a control group, is the average difference between groups large relative to the variance? While this has allowed us to discover elements that are activated or deactivated during development, disease progression, and in different tissues and organs, it fails to capture the entire spectrum of changes that occur as cells change from one state to another. There is a second, equally important question one might ask: For a biologically relevant pathway or mechanism, is there a large difference in the variance exhibited by different phenotypic groups?

2:15 Single Molecules Meet Systems Biology - Quantifying the E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells

Yuichi Taniguchi, Ph.D., Postdoctoral Fellow, Chemistry and Chemical Biology, Harvard University

System-wide measurements of protein and mRNA copy numbers with single molecule sensitivity in single cells are carried out for the model organism of Escherichia coli. The results provide a comprehensive and quantitative description of stochastic gene expression, and of cell-to-cell variation in protein and mRNA production in isogenic bacterial populations.

2:45 Screening for Novel Chemical and Genetics Regulators of the Wnt/Wingless Signaling Pathway
Ramanuj DasGupta, Ph.D., Assistant Professor, Pharmacology, Director, RNAi-Screening Facility, NYU School of Medicine/Cancer Institute
We have designed an RNAi-based chemical genetic screen to identify novel small molecule modulators of the Wnt signaling pathway. Our screen has identified 3 compounds, that we call “inhibitors of ß-catenin-responsive transcription” or iCRTs, that specifically and potently inhibit the activity of the Wnt pathway in a variety of Wnt-responsive and disease relevant cell lines. Importantly, these novel Wnt inhibitors are specifically cytotoxic to human colon tumor biopsy cultures as well as colon cancer cell lines that exhibit deregulated Wnt signaling.

3:15 Refreshment Break in the Exhibit Hall and Poster Viewing

Data Integration

3:45 Mechanistic Modeling of Clinical Laboratory Data for Earlier and More Accurate Diagnosis of Anemia
John Higgins, M.D., Assistant Professor of Systems Biology, Harvard Medical School; Assistant Pathologist, Massachusetts General Hospital
Biomarkers grounded in an understanding of pathogenic mechanisms yield optimal diagnostic sensitivity and specificity.  We inferred a mechanistic model for the population dynamics of circulating human red blood cells by combining high-resolution data from the hospital clinical laboratory with theory and methods from statistical physics.  The model suggests new aspects of human physiology and motivates novel statistical biomarkers of red blood cell pathophysiology.  These biomarkers can predict which patients will become anemic up to 3 months ahead of time and distinguish anemias with different underlying etiology more accurately than common existing methods.

4:15 Discovering Copy Number Variations in Cancer Genomes by Data Integration

Peter J. Park, Ph.D., Assistant Professor, Harvard Medical School Center for Biomedical Informatics

We have collected and analyzed thousands of DNA copy number profiles of tumor genomes from public databases. Our analysis reveals a spectrum of common and tissue type-specific aberrations, correlations among the observed aberrations, and potential molecular mechanisms. I will also describe some of our efforts in using next-generation sequencing to better characterize structural variations in cancer genomes.

4:45 Selected Poster Presentation: Intelligent Decision Support System-Based Biomarker Discovery
Nabil Belacel, Ph.D., Senior Research Officer, National Research Council of Canada

5:15 Best of Show Awards in the Exhibit Hall

6:15 Exhibit Hall Closes

Thursday, April 14

8:45 am Event Chairperson’s Opening Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:30 Coffee Break in the Exhibit Hall with Poster Competition

Data Modeling for Drug Development

10:55 Chairperson’s Remarks

Zhaohui Cai, M.D., Ph.D., Director, Biomedical Informatics, AstraZeneca

11:00 Computational Models for Human Drug Induced Liver Injury

Sean Ekins, Ph.D., D.Sc., Senior Consultant, Collaborations in Chemistry

Drug-induced liver injury (DILI) is one of the most important reasons for drug development failure at both pre-approval and post-approval stages. I will describe machine learning models for DILI and their large scale validation. These computational models may represent a cost effective selection criteria prior to in vitro or in vivo experimental studies.

11:30 Model-Based Drug Development: How in silico Approaches Are Reshaping the Clinical Enterprise

Zhaohui Cai, M.D., Ph.D., Director, Biomedical Informatics, AstraZeneca

This presentation will demonstrate how the application of advanced in-silico methods for predictive modeling look set to change the way that clinical trials are conducted in the future. Specifically, it will cover different applications of predictive modeling in drug development and demonstrate how disciplines like Biomedical and Health Informatics can help address the gaps in drug development through real case scenarios. It will end with a discussion on the successes and challenges surrounding how to implement modeling as a routine way of working in biopharmaceutical drug development.

12:00 pm Understanding the Human Microbiome through Data Integration
Curtis Huttenhower, Ph.D., Assistant Professor, Department of Biostatistics, Harvard School of Public Health
In order to interpret the biological activity of our microbial communities, it is necessary to harness a wide range of experimental results generated by decades of work on model organisms in the laboratory. I will discuss work that my lab has done integrating such data in order to characterize individual microbes and assembling it to better understand microbial communities. I will conclude with an overview of the functional genomics involved in the Human Microbiome Project and their potential for future cohort studies of the microbiota for disease diagnosis and treatment.

12:30 Luncheon in the Exhibit Hall and Poster Viewing

2:00 Exhibit Hall Closes

The 4 D’s: Data, Drug Discovery
& Development

1:55 Chairperson’s Remarks

Bruce Gomes, Ph.D., Head, Mathematical Modeling, Systems Biology, Research Technology Center, Pfizer, Inc.

2:00 Re-Engineering CNS Drug R&D Using Computer-Based Mechanistic Modeling and Simulation

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences; Adjunct Associate Professor, School of Medicine, University of Pennsylvania

A major difference between the pharmaceutical industry and other successful industries is the lack of integrated computer simulation. Computer-based mechanistic modeling based upon the physiology of brain networks and the pharmacology of drug-receptor interaction, based upon pre-clinical and clinical data for schizophrenia and cognitive disorders is a powerful tool to support a variety of decision processes in pre-clinical and clinical CNS R&D, especially when validated by correlations with clinical outcomes.

2:30 Drugable.com -- Drug Discovery in the Systems Biology Era Meets the Web - Click here for Podcast 

James Swetnam, Lead Scientific Programmer, Pharmacology, New York University Langone Medical Center

Drugable.com is an NLM stimulus-funded venture that maintains a comprehensive, clean, and intuitive index of drugable targets, druglike chemistry, experimental activity, crystallographic structures, and in silico docking predictions. This talk will show how drugable.com can be used to diversify lead portfolios, explore off-target activity, and accelerate drug discovery. Broader emerging concepts in drug discovery informatics will also be discussed.

3:00 Practical Applications of Systems Biology in the Pharmaceutical Industry

Bruce Gomes, Ph.D., Head, Mathematical Modeling, Systems Biology, Research Technology Center, Pfizer, Inc.

At one end of the R&D spectrum, modeling and simulation of therapeutics is applied in clinical trial design and patient stratification. At the other end of the discovery pipeline, Systems Biology is used to objectively define therapeutic product profiles. In addition, the combination of text mining and modeling is being effectively deployed for target generation from the combination of disease, therapeutic modality, and pathway modeling. This talk will trace some of the practical applications of Systems Biology that have been used to speed discovery, increase its success rate, improve safety of biotherapeutic drug candidates and deliver these drugs to the correct patient populations.

3:30 A Systems Approach to Drug Discovery

Ulrik Nielsen, Ph.D., Senior Vice President & CSO, Merrimack Pharmaceuticals

Merrimack has built a pharmaceutical organization designed to drive innovation through a systems approach to therapeutic research and development. Insights from multidisciplinary teams working on drug design and diagnostics have led to a pipeline of novel experimental cancer therapies. We will discuss our experience based on several programs that are now in clinical trials.

4:00 Conference Adjourns