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Final Agenda 


Developing Scalable IT 

Day 1 | Day 2 | Day 3 | Download Brochure 

Recommended Pre-Conference Short Courses * 

(SC3) Best Practices in Translational & Personalized Medicine 

(SC9) Building an Ontological Framework from Drug Discovery to Clinical Data  


* Separate Registration Required. 



Wednesday, February 23 

7:00 am Registration and Morning Coffee

8:00 Plenary Keynotes - Details 

9:40 Grand Opening Refreshment Break in the Exhibit Hall


Getting More Value and Generating Knowledge from Large Volumes of Data and Studies

11:00 Chairperson’s Opening Remarks

Kevin Davies, Ph.D., Author, The $1,000 Genome; Editor-in-Chief, Bio-IT World

11:10 Generating More Knowledge from Our Data and More Value from Our Studies: The Value of Expert Skills

Anastasia M. Khoury Christianson, Ph.D., Senior Director, Discovery Information, AstraZeneca Pharmaceuticals

A major challenge in translational science is finding the relevant data, information and knowledge to allow meaningful correlation between pre-clinical observations and clinical outcomes. A big factor in this challenge is that the business drivers, processes, approaches, and cultures are very different between early stages of drug discovery and late stages of drug development, which lead to very different approaches to information management systems, data standards and vocabularies.  A simple generalization is that Discovery systems and processes are designed for data exploration, while those in development are designed for regulatory submission, two very different objectives.  This presentation will concentrate on the key success factors for leveraging information, generating new knowledge, and ensuring best informed decisions in our drug projects.

11:40 Burn the Hay or Build a Better Magnet to Find the Needles in our Haystack?

Martin LeachMartin Leach, Ph.D., Executive Director, IT for Discovery & Pre-Clinical Sciences (DPS), Merck

More silos, exponential data growth, it's not going away. Lab technologies are constantly evolving and the volume and granularity of research data is ever-changing—where biological research is a much more diverse space than chemistry. Some predictions estimate that by 2011 the cost of a personal petabyte disk could be less than $1000. That equates to 20 million four-drawer filing cabinets filled with text. The expense and availability of technology enables compulsive hoarding, but at what cost to research? The ability to find things now relies heavily on search technology, data-mining or semantic-mining techniques that require proper classification of the structured and unstructured data, information, and knowledge. Search technology may be able to find things, but how do we effectively manage this information vs. constantly compounding the problem. There are several approaches that are needed in pharmaceutical research for effective information management and access and this presentation will explore some of the lessons learned at Merck and other organizations. 

12:10 pm From Virtual Machine to Virtual Pharmaceutical Organization: Cloud-Based Translational Informatics for European IMI Projects

Eric PerakslisEric Perakslis, Ph.D., Vice President, Research & Development IT, Johnson & Johnson

Anthony Rowe, Ph.D., Department of Computing, Imperial College, London

In this talk, we illustrate the design of the IT infrastructure for collaborative translational research in the UBIOPRED IMI project. The system is based on the Cloud computing infrastructure, with a strong focus on supporting open collaborative research. Through this work, we would like to demonstrate that the convergence of the technical trend in cloud computing and the industry trend in pre-competitive collaboration will realize a powerful new generation of IT infrastructure. Such an infrastructure is essential for the new knowledge-oriented scientific business where ‘proprietary data’ can be made shared to enable the collaboration in generating ‘proprietary knowledge’ for each collaborative partner from the shared data and IT infrastructure.

    Sponsored by
Biofortis smaller
12:40 Luncheon Presentation

Complex Questions Against Complex Data: Challenges in Translational and Clinical Informatics
Jian Wang, Ph.D., CEO, BioFortis, Inc.
There are many unique challenges faced by research informatics groups when dealing with complex clinical and translational data sets. These challenges are exacerbated by the fact that researchers are asking increasingly more dynamic and complex questions against these data sets. Traditional BI (business intelligence) methods have their limitations under these conditions.  In this presentation, we will describe these unique challenges and BioFortis’ innovative approach to help address them, focusing on a repeatable process we developed in data cleaning & standardization, data exploration, and data analysis from working with our partners & clients.


1:10 Luncheon Presentation (Sponsorship Opportunities Available) or Lunch on Your Own

1:45 Dessert in the Exhibit Hall



2:15 Chairperson’s Remarks

Matthew Trunnell, Manager, Research Computing, Broad Institute

2:20 Challenges in Management and Analysis of Sequencing Data at Large Scale

Matthew Trunnell, Manager, Research Computing, Broad Institute

One of the Broad Institute's core missions is to discover, develop and optimize the critical technologies needed to obtain and analyze the massive amounts of genomic data being generated by scientists at the Broad and around the world. Our adoption of second-generation sequencing technologies over the past four years has driven a 40-fold growth in the size of our data repositories. This talk will discuss our ongoing adjustment to data wrangling at this new multi-petabyte scale with particular emphasis on data storage, support for the analysis of multi-terabyte data sets, and new approaches to the management of unstructured research data.

2:50 From Genomic Data to Personalized Medicine

Karen Eilbeck, Ph.D., Assistant Professor, Human Genetics, & Biomedical Informatics, University of Utah School of Medicine

There are many challenges to managing and utilizing personal genomic data. Using ontologies to describe the reference features, the personal changes and the effect of those changes provides the means for a standard format for storage, exchange and analysis of these data.

3:20 Supporting Yet Another New High Throughput Technology: Bring it On!

Anthony Masiello, Senior Group Head, Biomarker Data Systems, Biomarker Development, Novartis Institutes for BioMedical Research

The past two decades have seen a proliferation of increasingly high throughput molecular biology platforms. Technologies from early microarrays, genotyping, SNP arrays, and now NGS data are giving us experience, but what are we learning from it?  We will share case studies covering the evolution of whole genome technologies to highlight the infrastructure and ever changing needs associated with bringing high throughput platforms on-line and making them productive.

Sponsored by
3:50 Sponsored Presentations (Opportunities Available) 

4:05 Sponsored Presentation

To Be Announced

4:20 Reception in the Exhibit Hall(Sponsorship Available) 

5:20 Breakout Discussions in the Exhibit Hall

Concurrent Problem Solving Break-Out Sessions are interactive, problem solving discussions hosted by a moderator to discuss a topic in depth.  The discussions are open to all attendees, sponsors, exhibitors, and speakers and provide a forum for discussing key issues and meeting potential partners. Please pick a topic of your choice and join in.  

Proteomic Data Management

Brian Halligan, Ph.D., Scientist, Bioinformatics Research Center, Medical College of Wisconsin

  • Acquisition of MS Data
  • Analysis of MS Data
  • What data to store and for how long?
  • Data Storage formats
  • Public Deposit of data

Management of Unstructured Data at Large Scale

Matthew Trunnell, Manager, Research Computing, Broad Institute

6:20 Close of Day

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