Bio IT World Expo 2016  
Bio IT World Expo 2016
Archived Content

Systems and Multiscale Biology 

Final Agenda


7:00 am Workshop Registration and Morning Coffee

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

*Separate Registration Required

2:00 - 7:00 pm Main Conference Registration

4:00 Event Chairperson's Opening Remarks

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

4:05 Keynote Introduction

Sanjay Joshi, Solutions Architect, Life Sciences, EMC Isilon Storage Division



Martin LeachMartin Leach, Ph.D., CIO, Broad Institute of MIT and Harvard


Jill MesirovJill P. Mesirov, Ph.D., Associate Director and Chief Informatics Officer; Director, Computational Biology and Bioinformatics, Broad Institute of MIT and Harvard


Hitachi Data Systems5:00 - 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2 iPod touches® or 1 of 2 Xbox 360s®*!

*Apple® is not a sponsor or participant in this program




7:00 am Registration and Morning Coffee

7:55 Chairperson's Opening Remarks

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

8:00 Keynote Introduction

Bas Burger, President, Global Commerce, BT Global Services



Eric PerakslisEric D. Perakslis, Ph.D., CIO and Chief Scientist of Informatics, U.S. Food and Drug Administration


8:45 Benjamin Franklin Award & Laureate Presentation

9:10 Best Practices Award Program

Cycle Computing small9:45 Coffee Break in the Exhibit Hall with Poster Viewing


Exploring Datasets and Biological Systems 

10:50 Chairperson's Remarks

Mary Ann Brown, Executive Director, Conferences, Cambridge Healthtech Institute

11:00 Featured Speaker
Moving Beyond the Mean: The Role of Variation in Determining Phenotype

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

New datasets have allowed us to explore other properties of biological systems, to embrace natural variation and stochastic effects, and to explore the way in which variation defines phenotypes and the transitions between them. Our work suggests an equally valid and potentially informative question may be: Given two phenotypes, is there a significant difference in the group variance independent of their means.

11:30 From Gene to Function: Understanding Human Variability Using Mechanistic Disease Modeling and Imaginomics in CNS

Hugo Geerts, Ph.D., CSO, Computational Neuropharmacology, In Silico Biosciences

Computer-based mechanistic modeling based upon the physiology of brain networks and the pharmacology of drug-receptor interaction, parametrized with clinical and human imaging data could be a powerful tool to support a variety of decision processes in pre-clinical and clinical CNS R&D. We illustrate an early-stage version of this approach with Alzheimer's disease and schizophrenia that modulate human patient variability in clinical trials and are beyond pre-clinical understanding.

12:00 pm Sponsored Presentation (Opportunity Available)

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

1:40 Chairperson's Remarks

Pek Yee Lum, Ph.D., Vice President, Life Sciences, Ayasdi, Inc.

1:45 Chemical-Protein Interactome and its Application in Personalized Medicine and Drug Repositioning

Lun Yang, Ph.D., Principal Investigator, Quantitative Sciences, GlaxoSmithKline

Chemical-Protein Interactome is a computational methodology with a focus on characterizing differential drug efficacy and side effects through the combined analysis of genetic polymorphisms and their impact on chemical-protein interactions and gene expression perturbations. The methodology opens opportunities for developing patient-specific medication in terms of decreasing adverse drug reactions and broadening new uses for old drugs.

2:15 Data Sciences: An Approach to Drug Discovery

Stephen Cleaver, Ph.D., Head, Quantitative Biology, Novartis Institutes for BioMedical Research

The increasing complexity of hypotheses demands not only in depth analysis for each dataset, but also integrative analysis across projects, and groups to realize their full potential for drug discovery. We are developing a multidisciplinary Data Sciences approach by bringing together systems and people of diverse backgrounds to meet the multi-scale and systems challenges.

Ayasdi 2:45 Topology as a Novel Approach to Detect Patterns in Complex Data SetsPek Yee Lum, Ph.D., Vice President, Life Sciences, Ayasdi, Inc.We introduce a novel computational platform based on Topological Data Analysis for understanding large and complex biological datasets. Further, we show how key ideas of topology are uniquely suited to address complex problems for the drug development pipeline. Finally, we demonstrate an application to patient stratification where we identified a new patient subset for breast cancer and the corresponding biomarkers.

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



Systems Views of the Molecular Basis of Human Disease 

3:45 Featured Speaker
Tying Individual Molecules to Phenotype

Andrew Kasarskis, Ph.D., Vice Chairman, Department of Genetics and Genomic Sciences; Co-Director, Institute for Genomics and Multiscale Biology, Mount Sinai School of Medicine

Technological innovations now allow us to monitor many thousands of individual molecules and their interactions. With this new precision, it is possible to identify distinct sub-populations of molecules in many situations where we could not previously observe them, and we are beginning to probe the relationship between these individual molecular populations and phenotype at both cellular and organismal scales. Progress in both cancer and infectious disease suggests broad and compelling applications for these approaches going forward.

4:15 A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

Thomas Eissing, Ph.D., Head, Systems Biology, Bayer Technology Services GmbH

Diseases are generally a consequence of the dysregulation or malfunction of biological processes on the molecular level. These processes are not isolated, but influence and are influenced by physiology up to whole-body scale. We introduce concepts and show by examples how multiscale models can help to better understand diseases and their progression, as well as potential therapeutic approaches including treatment optimization by a rigorous integration of knowledge, assumptions, and experimental data. Such an approach can also contribute to the personalization of medicine, and is beginning to be applied during drug research and development to rationalize decision making along the development process in the pharmaceutical industry ranging from early target identification to late phase clinical studies.

4:45 Systems Epigenomic Views of Complex Disease Associations Reveal 1000s of Regulatory SNPs

Manolis Kellis, Ph.D., Associate Professor, MIT Computer Science and Electrical Engineering Department; Head, MIT Computational Biology Group; MIT Computer Science and Artificial Intelligence Laboratory, Broad Institute of MIT and Harvard University

To identify the molecular mechanisms underlying disease-associated variants, we integrate disease studies with large-scale functional genomics studies, including chromatin state maps in multiple human cell types, linking of active enhancers to upstream regulators and downstream targets based on coordinated patterns of activity, and genome-wide brain methylation patterns across hundreds of Alzheimer’s patients and healthy controls. These reveal global associations of thousands of enhancer elements with complex human disease that are chromatin-state-specific and cell type-specific, suggesting that thousands of SNPs contribute to the observed disease phenotype.

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes




Web-Based Platforms for Systems Medicine 

8:40 Chairperson's Opening Remarks

Subha Madhavan, Ph.D., Director, Clinical Research Informatics, Lombardi Comprehensive Cancer Center; Director, Biomedical Informatics, Georgetown-Howard Universities CTSA, Georgetown University Medical Center

8:45 G-DOC: A Systems Medicine Platform for Personalized Oncology

Subha Madhavan, Ph.D., Director, Clinical Research Informatics, Lombardi Comprehensive Cancer Center; Director, Biomedical Informatics, Georgetown-Howard Universities CTSA, Georgetown University Medical Center

The Georgetown Database of Cancer (G-DOC) is a generic and flexible web-based platform that serves to enable basic, translational, and clinical research activities by integrating patient characteristics and clinical outcome data with a variety of high-throughput research data in a unified environment. Through this modular, extensible, and flexible infrastructure, we can quickly and easily assemble new translational web applications with both analytic and generic administrative features.

9:15 Data Integration around Hierarchically and Modularly Organized Protein-Protein Interaction Network

Bing Zhang, Ph.D., Assistant Professor, Department of Biomedical Informatics, Vanderbilt University School of Medicine

Traditional graph-based network visualization techniques quickly become inadequate as network size and data complexity increase. We propose NetGestalt, a novel web-based data integration framework that exploits the inherent hierarchical modular architecture of protein-protein interaction networks to achieve high scalability. Using multidimensional cancer omics, as an example, we show that Netgestalt allows simultaneous presentation of large scale experimental and annotation data from various sources.

9:45 A Systems Approach to Designing Effective Clinical Trials

Vincent Fusaro, Ph.D., Research Associate, Center for Biomedical Informatics, Harvard Medical School

Randomized clinical trials are unsustainable in the era of personalized medicine due to the exponential number of combinations necessary for evaluating personalized treatment options. Computational methods are necessary to predict the likely outcomes and guide clinical trial designs.

10:15 Coffee Break in the Exhibit Hall and Poster Competition

10:45 Plenary Keynote Panel Chairperson's Remarks

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

10:50 Plenary Keynote Panel Introduction

Geoffrey Noer, Senior Director, Product Marketing, Panasas


11:00 Plenary Keynote Panel:
A special plenary session featuring trends and challenges in cancer research:

Julian Adams, Ph.D., President, Research and Development, Infinity Pharmaceuticals, Inc.

Jose Baselga, M.D., Ph.D., Chief and Bruce A. Chabner Chair, Division of Hematology/Oncology, Massachusetts General Hospital; Associate Director, Massachusetts General Hospital Cancer Center; Professor of Medicine, Harvard Medical School

Sir John Burn, MD, FMedSci, Professor of Clinical Genetics, Institute of Genetic Medicine, Newcastle University, UK; Genetics Lead, National Institute of Health Research, UK; Medical Director, QuantuMDx Ltd

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

12:15 Luncheon in the Exhibit Hall with Poster Viewing

Systems Pharmacology

1:55 Chairperson's Remarks

Avi Ma'ayan, Ph.D., Assistant Professor, Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine

2:00 Data Mining Strategies in Systems Pharmacology and Stem Cell Systems Biology

Avi Ma'ayan, Ph.D., Assistant Professor, Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine

Genome-wide experiments collect data across regulatory layers, including gene expression, transcription factor binding to DNA, epigenetic modifications, as well as protein abundance, protein interactions and protein modifications. Integrating these different types of experimental data is a fundamental challenge of computational systems biology. This presentation describes successful applications of data integration in stem cell systems biology and systems pharmacology.

2:30 Systems Pharmacology Modeling in Drug Research and Development

Oleg Demin, Ph.D., CSO, Institute for Systems Biology SPb

Quantitative Systems Pharmacology (QSP) is an emerging modelling technique that combines the flexibility of systems biology and tractability of compartmental pharmacokinetic–pharmacodynamic modelling techniques. In my presentation the impact of QSP within drug discovery and development is considered by discussing several examples illustrating application of the modeling technique to resolve the problems arising in the field of pharmacology.

3:00 Next-Generation Model-Based Drug Discovery and Development: Quantitative and Systems Pharmacology

Sandy Allerheiligen, Ph.D.,Vice President, Modeling and Simulation, Merck & Co., Inc.

3:30 Closing Featured Speaker:
Platform for Clinical Research Networks: Novel Approach towards Discoveries in Rare Diseases

Alex Sherman, Ph.D., Director, Systems, Neurology, Massachusetts General Hospital

This presentation describes a TREAT ALS™ software platform that is currently deployed to support a clinical research network in Lou Gehrig's disease and allows investigators from 100+ academic institutions around the world to collaborate, share data, and biological specimen. This is a unique solution and approach in managing disease-specific research networks and may serve as a model for academic and industry collaboration in finding cures for rare diseases.

4:00 Conference Adjourns


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