Leaders in Pharmaceutical Business Intelligence (LPBI) Group

 

Reporter: Aviva Lev-Ari, PhD, RN

 

Systems Pharmacology: Pathways to Patient Response @ BioIT World, Boston, MA World Trade Center, April 9-11, 2013

Conference Tracks:

IT Infrastructure – Hardware

Software Development

Cloud Computing

Bioinformatics

Next-Gen Sequencing Informatics

Systems Pharmacology

eClinical Trials Solutions

Data Visualization NEW!

Drug Discovery Informatics

Clinical Omics NEW!

Collaborations and Open

Access Innovations

Cancer Informatics

 

Track 6 focuses on how compounds (drugs) work in the body. How are they influenced by various ‘omics’? How do they vary by tissue? The practical implications of such a compound-centric approach are exciting: new targets, new screens, new markers, new understanding of drug failure mechanisms. The systems computational tool sets including multi-scale modeling, simulation, web-based platforms, etc. will be emphasized.

Final Agenda

 

Download Brochure | Pre-Conference Workshops

 

TUESDAY, APRIL 9

7:00 am Workshop Registration and Morning Coffee

8:00 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

Speaker to be Announced, Hitachi Data Systems

 

 

5:00 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 iPads® or 1 of 2 Kindle Fires®!*

*Apple ® and Amazon are not sponsors or participants in this program

 

WEDNESDAY, APRIL 10

7:00 am Registration and Morning Coffee

8:00 Chairperson’s Opening Remarks

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

8:05 Keynote Introduction

Sanjay Joshi, CTO, Life Sciences, EMC Isilon

 

 

8:55 Benjamin Franklin Award & Laureate Presentation

9:15 Best Practices Award Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

 

PHARMACODYNAMIC MODELS

10:50 Chairperson’s Remarks

» Featured Speaker

11:00 Systems Pharmacology in a Post-Genomic Era

Peter Sorger, Ph.D., Professor, Systems Biology, Harvard Medical School; Co-Chair, Harvard Initiative in Systems Pharmacology

I will describe the emergence of “systems pharmacology” as a means to guide the creation of new molecular matter, study cellular networks and their perturbation by drugs, understand pharmaco-kinetics and pharmaco-dynamics in mouse and man and design and analyze clinical trial data. The approach combines mathematical modeling with empirical measurement as a means to tackle basic and clinical problems in pharmacology. Ultimately we aim for models that describe drug responses at multiple temporal and physical scales from molecular mechanism to whole-organism physiology.

11:30 Using Quantitative Systems Pharmacology for De-Risking Projects in CNS R&D

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

Quantitative Systems Pharmacology is a computer based mechanistic modeling approach combining physiology, the functional imaging of genetics with the pharmacology of drug-receptor interaction and parameterized with clinical data and is a possible powerful tool for improving the success rate of CNS R&D projects. The presentation will include failure analyses of unsuccessful clinical trials, correct prospective identification of clinical problems that halted clinical development and estimation of genotype effects on the pharmacodynamics of candidate drugs.

12:00 pm Systems Pharmacology Approaches to Drug Repositioning

Svetlana Bureeva, Ph.D., Director, Professional Services, Thomson Reuters, IP & Science

Drug repositioning requires advanced computational approaches and comprehensive knowledgebase information to reach success. Thomson Reuters will present on recent advances in drug repositioning approaches, their validation and performance, best practices in using systems biology content, and successful case studies.

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

 

HIGH CONTENT ANALYSIS: CANCER CELL LINES

1:40 Chairperson’s Remarks

1:45 Systems Pharmacology Using CellMiner and the NCI-60 Cancerous Cell Lines

William Reinhold, Manager, Genomics and Bioinformatics Group, Laboratory of Molecular Pharmacology (LMP), National Cancer Institute (NCI)

CellMiner is a web-based application that allows rapid access to and comparison between 20,503 compound activities and the expression levels of 26,065 genes and 360 microRNAs. Included are 102 FDA-approved drugs as well as 53 in clinical trials. The tool is designed for the non-informatisist, and allows the user wide latitude in defining the question of interest. This opens the door to systems pharmacological studies for physicians, molecular biologists and others without bioinformatics expertise.

2:15 Oncology Drug Combinations at Novartis

Joseph Lehár, Ph.D., Associate Director, Bioinformatics, Oncology Translational Research, Novartis; Adjunct Assistant Professor, Bioinformatics, Boston University

Novartis is undertaking a large-scale effort to comprehensively describe cancer through the lens of cell cultures and tissue samples.  In collaboration with academic and industrial partners, we have generated mutation status, gene copy number, and gene expression data for a library of 1,000 cancer cell lines, representing most cancer lineages and common genetic backgrounds.  Most of these cell lines have been tested for chemosensitivity against ~1,200 cancer-relevant compounds, and we are systematically exploring drug combinations for synergy against ~100 prioritized CCLE lines.  We expect this large-scale campaign to enable efficient patient selection for clinical trials on existing cancer drugs, reveal many therapeutically promising drug synergies or anti-resistance combinations, and provide unprecedented detail on functional interactions between cancer signaling pathways.   I will discuss early highlights of this work and describe our plans to make use of this resource.

2:45 Sponsored Presentations (Opportunities Available)

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

 

PHARMACODYNAMIC MODELS FOR ONCOLOGY

3:45 Systems Biology in Cancer Immunotherapy: Applications in the Understanding of Mechanism of Action and Therapeutic Response

Debraj Guha Thakurta, Ph.D., Senior Scientist II & Group Leader, Systems Biology, Dendreon Corporation

We are using high-content platforms (DNA and protein microarrays, RNA-seq) in various stages of the development of cellular immunotherapies for cancer. We will provide examples of genomic applications that can aid in the mechanistic understanding and the discovery of molecular markers associated with the efficacy of a cancer immunotherapy..

4:15 Use of Systems Pharmacology to Aid Cancer Clinical Development

Anna Georgieva Kondic, Ph.D., MBA, Senior Principal Scientist, Modeling and Simulation, Merck Research Labs

The last few years have seen an increased use of physiologically-based pharmacokinetics and pharmacodynamics models in Oncology drug development. This is partially due to an improved mechanistic understanding of disease drivers and the collection of better patient-level quantitative data that lends itself to modeling. In this talk, a suite of studies where systems modeling was successfully used to inform either preclinical to clinical transition or clinical study design will be presented. The talk will complete with a potential systems pharmacology framework that can be used systematically in drug development.

4:45 Sponsored Presentations (Opportunities Available)

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

6:15 Exhibit Hall Closes

 

Thursday, April 11

7:00 am Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

 

MODELING AND MINING TARGETS

8:45 Chairperson’s Opening Remarks

8:50 Systems Biology Approach for Identification of New Targets and Biomarkers

I-Ming Wang, Ph.D., Associate Scientific Director, Research Solutions and Bioinformatics, Informatics and Analysis, Merck Research Laboratory

A representative gene signature was identified by an integrated analysis of expression data in twelve rodent inflammatory models/tissues. This “inflammatome” signature is highly enriched in known drug target genes and is significantly overlapped with macrophage-enriched metabolic networks (MEMN) reported previously. A large proportion of genes in this signature are tightly connected in several tissue-specific Bayesian networks built from multiple mouse F2 crosses and human tissue cohorts; furthermore, these tissue networks are very significantly overlapped. This indicates that variable expression in this set of co-regulated genes is the main driver of many disease states. Disease-specific gene sets with the potential of being utilized as biomarkers were also identified with the approach we applied. The identification of this “inflammatome” gene signature extends the coverage of MEMN beyond adipose and liver in the metabolic disease to multiple diseases involving various affected tissues.

9:20 Optimizing Therapeutic Index (TI) by Exploring Co-Dependencies of Target and Therapeutic Properties

Madhu Natarajan, Ph.D., Associate Director, Computational Biology, Discovery Research, Shire HGT

Conventional drug-discovery informatics workflows employ combinations of mechanistic/probabilistic in-silico methods to rank lists of targets; therapeutics are then developed for “optimal” targets. I describe a systems pharmacology approach that instead integrates systematic in-silico therapeutic perturbation with models of target/disease biology to identify conditions for optimal TI; non-intuitively optimal TI is sometimes achieved by pairing sub-optimal targets with therapeutics having appropriate properties.

9:50 Sponsored Presentations (Opportunities Available)

10:20 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

10:45 Plenary Keynote Panel Chairperson’s Remarks

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

10:50 Plenary Keynote Panel Introduction

Yury Rozenman, Head of BT for Life Sciences, BT Global Services

 

 

12:15 pm Luncheon in the Exhibit Hall with Poster Viewing

 

MODELING MOLECULAR AND PATHOPHYSIOLOGICAL DATA

1:55 Chairperson’s Remarks

2:00 Predicting Adverse Side Effects of Drugs Using Systems Pharmacology

Jake Chen, Ph.D., Associate Professor, Indiana University School of Informatics & Purdue University Department of Computer Science; Director, Indiana Center for Systems Biology and Personalized Medicine

A new way of studying drug toxicity is to incorporate biomolecular annotation and network data with clinical observations of drug targets upon drug perturbations. I will describe the development of a novel computational modeling framework, with which we demonstrated the highest drug toxicity prediction accuracies ever reported by far. Adoption of this framework may have profound practical drug discovery implications.

2:30 Holistic Integration of Molecular and Physiological Data and Its Application in Personalized Healthcare

David de Graaf, Ph.D. President and CEO, Selventa

There are multiple industry-wide challenges in aggregating molecular and pathophysiological data for systems pharmacology to transform the process of drug discovery and development. One of the ways to address these challenges is to utilize a common computable biological expression language (BEL) that can provide a comprehensive knowledge network for new discoveries. An application of BEL and its use in identifying clinically relevant predictive biomarkers for patient stratification will be presented.

3:00 The Role of Informatics in ADME Pharmacogenetics

Boyd Steere, Ph.D., Senior Research Scientist, Lilly Research Laboraories, IT Research Informatics, Eli Lilly

The leveraging of pharmacogenetics to support decisions in early-phase clinical trial design requires informatics methods to integrate, visualize, and analyze heterogeneous data sets from many different discovery platforms.  This presentation describes challenges and solutions in making sense of diverse sets of genetic, protein, and metabolic data in support of ADME pharmacology projects.

3:30 A Systems Pharmacology Approach to Understand and Optimize Functional Selectivity for Non-Selective Drugs

Joshua Apgar, Principal Scientist, Systems Biology, Dept. of Immunology & Inflammation, Boehringer Ingelheim Pharmaceuticals, Inc.

Most commonly the selectivity of a compound is defined in an in vitro or cellular assay, and it is thought of as principally a function of the binding energy of the drug to its on-target and off-target proteins; however, in vivo functional selectivity is much more complicated, and is affected by systems level effects such as multiple feedback processes within and between the various on- and off-target pathways. These systems level processes are often impossible to reconstruct in vitro as they involve many cell types, tissues, and organs systems throughout the body. We show here that through mathematical modeling we were able to identify, in silico, molecular properties that are critical to driving functional selectivity. The models, although simple, capture the key systems pharmacology needed to understand the on- an off- target effects. Surprisingly, in this case, the key driver of functional selectivity is not the affinity of the drugs but rather the pharmacokinetics, with drugs having a short half-life predicted to be the most functionally selective.