Leaders in Pharmaceutical Business Intelligence (LPBI) Group

 

Track 4 explores technologies and tools that bring together relevant -omic data from multiple physical locations for analysis. Case studies and results will be presented to illustrate how virtual data integration across multiple research initiatives can be applied to any disease. Other topics covered include collaboration tools, biomarker research, imaging, computational models, clinically actionable variants, and gene mapping and expression.

Final Agenda

 

Download Brochure | Pre-Conference Workshops

 

TUESDAY, APRIL 29

 

 

2:00 – 7:00 pm Main Conference Registration

4:00 Event Chairperson’s Opening Remarks

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

 

 

5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing

iPad® mini & Bose® QuietComfort 15 Noise Cancelling Headphones Raffle! Drawing held at 6:30pm!*

 

*Apple® & Bose® are not sponsors or participants in this program.

 

WEDNESDAY, APRIL 30

7:00 am Registration Open and Morning Coffee

8:00 Chairperson’s Opening Remarks

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

 

 

9:00 Benjamin Franklin Award & Laureate Presentation

9:30 Best Practices Awards Program

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

 

BIOINFORMATICS FOR BIG DATA

10:50 Chairperson’s Remarks

11:00 Data Management Best Practices for Genomics Service Providers

Vas Vasiliadis, Director, Products, Computation Institute, University of Chicago and Argonne National Laboratory

Genomics research teams in academia and industry are increasingly limited at all stages of their work by large and unwieldy datasets, poor integration between the computing facilities they use for analysis, and difficulty in sharing analysis results with their customers and collaborators. We will discuss issues with current approaches and describe emerging best practices for managing genomics data through its lifecycle.

11:30 NGS Analysis to Drug Discovery: Impact of High-Performance Computing in Life Sciences

Bhanu Rekepalli, Ph.D., Assistant Professor and Research Scientist, Joint Institute for Computational Sciences, The University of Tennessee, Oak Ridge National Laboratory

We are working with small-cluster-based applications most widely used by the scientific community on the world’s premier supercomputers. We incorporated these parallel applications into science gateways with user-friendly, web-based portals. Learn how the research at UTK-ORNL will help to bridge the gap between the rate of big data generation in life sciences and the speed and ease at which biologists and pharmacists can study this data.

12:00 pm The Future of Biobank Informatics

Bruce Pharr, Vice President, Product Marketing, Laboratory Systems, Remedy Informatics

As biobanks become increasingly essential to basic, translational, and clinical research for genetic studies and personalized medicine, biobank informatics must address areas from biospecimen tracking, privacy protection, and quality management to pre-analytical and clinical collection/identification of study data elements. This presentation will examine specific requirements for third-generation biobanks and how biobank informatics will meet those requirements.

12:15 Learn How YarcData’s High Performance Hadoop and Graph Analytics Appliances Make It Easy to Use Big Data in Life Sciences

Ted Slater, Senior Solutions Architect, Life Sciences, YarcData, a division of Cray

YarcData, a division of Cray, offers high performance solutions for big data using Hadoop and graph analytics at scale, finally giving researchers the power to leverage all the data they need to stratify patients, discover new drug targets, accelerate NGS analysis, predict biomarkers, and better understand diseases and their treatments.

12:30 Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own

1:50 Chairperson’s Remarks

1:55 Integration of Multi-Omic Data Using Linked Data Technologies

Aleksandar Milosavljevic, Ph.D., Professor, Human Genetics; Co-Director, Program in Structural & Computational Biology and Molecular Biophysics; Co-Director, Computational and Integrative Biomedical Research Center, Baylor College of Medicine

By virtue of programmatic interoperability (uniform REST APIs), Genboree servers enable virtual integration of multi-omic data that is distributed across multiple physical locations. Linked Data technologies of the Semantic Web provide an additional “logical” layer of integration by enabling distributed queries across the distributed data and by bringing multi-omic data into the context of pathways and other background knowledge required for data interpretation.

2:25 Building Open Source Semantic Web-Based Biomedical Content Repositories to Facilitate and Speed Up Discovery and Research

Bhanu Bahl, Ph.D., Director, Clinical and Translational Science Centre, Harvard Medical School

Douglas MacFadden, CIO, Harvard Catalyst at Harvard Medical School

Eagle-i open source network at Harvard provides a state-of-the-art informatics platform to support the quality control and annotation of resources establishing a sound foundation for a well-curated resource collection in accordance with Semantic Web and Linked Open Data principles. Learn how this ontology-centric architecture is used to efficiently store, create, and search data.

2:55 Data Experts: Improving Translational Drug-Development Efficiency

Jamie MacPherson, Ph.D., Consultant, Tessella

We report on a novel approach to translational informatics support: embedding ‘Data Experts’ within drug-project teams. Data experts combine first-line informatics support and Business Analysis. They help teams exploit data sources that are diverse in type, scale and quality; analyse user-requirements and prototype potential software solutions. We then explore scaling this approach from a specific drug development team to all.

3:25 Refreshment Break in the Exhibit Hall with Poster Viewing

 

BIOLOGICAL NETWORKS

4:00 Network Verification Challenge: A Reputation-Based Crowd-Sourced Peer Review Platform for Network Biology

William Hayes, Ph.D., Senior Vice President, Platform Development, IT/Informatics, Selventa

Anselmo DiFabio, Vice President, Technology, Applied Dynamic Solutions

The Network Verification Challenge proposes a new approach for peer review for Network biology. The use of a reputation-based crowd-sourced platform can make previously overwhelming efforts in capturing large-scale network biology and validating it possible. The same approach for peer review can also be applied inside bioPharma for internal collaboration and validation of network biology in and across therapeutic areas.

4:30 NDEx, the Network Data Exchange: Bridging the Knowledge Gap for Commercial and Academic Collaboration on Biological Networks

Dexter Pratt, Project Director, NDEx, Cytoscape Consortium

NDEx is a public portal for collaboration and publication for scientists and organizations working with biological networks of multiple types and in multiple formats. This talk presents key features of the NDEx portal and the underlying open-source server software. The status of NDEx in collaborations with other organizations and the use (or development) of standards will be summarized.

5:00 Sponsored Presentations (Opportunities Available)

5:30 – 6:30 Best of Show Awards Reception in the Exhibit Hall

THURSDAY, MAY 1

7:15 am Registration Open

7:15 Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

8:30 Chairperson’s Opening Remarks

Kevin Davies, Ph.D., Vice President Business Development & Publisher C&EN, American Chemical Society; Founding Editor, Bio-IT World

 

 

10:00 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

 

BIOINFORMATICS ACROSS MULTIPLE RESEARCH INITIATIVES

10:30 Chairperson’s Opening Remarks

10:35 Analysis of Genomics Data in an Internal Cloud Computing Environment

Philip Groth, Ph.D., IT Business Partner Genomics, R&D IT – Research, Bayer HealthCare

This talk presents the technical set-up of vCloud, an in-house cloud solution, maintenance and running an internal cloud-computing environment, and how this set-up enables fast & secure analysis of large-scale genomics data. Results of analyzing genomic data from over 4,000 cancer patients will be presented.

11:05 Genome-Wide Multi-Omics Profiling of Colorectal Cancer Identifies Immune Determinants Strongly Associated with Relapse

Subha Madhavan, Ph.D., Director, Innovation Center for Biomedical Informatics, Oncology, Georgetown University

This presentation demonstrates the use of novel informatics methods and data integration approaches in identifying prognostic markers of cancer. The use and benefit of adjuvant chemotherapy to treat patients with state II colorectal cancer (CRC) is not well understood since the majority of these patients are cured by surgery alone.

11:35 Sponsored Presentations (Opportunities Available)

12:05 pm Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own

1:15 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing

1:55 Chairperson’s Remarks

2:00 An Algorithm to Access Human Memory Showing Alzheimer Symptoms When Distorted

Simon Berkovich, Ph.D., Professor, Computer Science, The George Washington University

This talk presents a novel theoretical framework for bioinformatics. Access to a holographic model of the brain encounters a particular problem of multiple responses resolution. For the given milieu, we employ a digital-analog adjustment of a streaming algorithm for finding a predominant element. Receptacles deterioration incurs preferential recall of prior life stages akin to Alzheimer’s disease.

 

MACHINE LEARNING MODELS

2:30 Accurate Prediction of Clinical Stroke Scales from Robotic Measurements

Dimitris K. Agrafiotis, Ph.D., FRSC, Vice President and Chief Data Officer, Covance

Here, we describe a novel approach that combines robotic devices and advanced machine learning algorithms to derive predictive models of clinical assessments of motor function following stroke. We show that it is possible to derive sensitive biomarkers of motor impairment using a few easily obtained robotic measurements, which can then be used to improve the efficiency and cost of clinical trials.

3:00 GPS Engineering: Machine Learning Approaches to Biological Engineering

Drew Regitsky, Scientist, Bioengineering, Calysta Energy

This talk presents a potential new approach to computational representations of biological systems and applying multidimensional analysis to predicting the behavior of complex systems. Several case studies will be presented to demonstrate applications of the methods and examples of the output of data analysis.

3:30 A Multiclass Extreme-Learning-Machine Approach to the Discovery of Multiple Cancer Biomarkers: Using Binary Coded Genetic Algorithm and IPA Analysis

Saras Saraswathi, Ph.D., Clinical Instructor, Pediatrics, Ohio State University; Postdoctoral Research Associate, Battelle Center for Mathematical Medicine, Research Institute, Nationwide Children’s Hospital

The neural network-based Extreme Learning Machine is combined with a Binary Coded Genetic Algorithm to select a small set of 92 genes which simultaneously classify 14 different types of cancers simultaneously, to high accuracy. IPA analysis of the selected genes reveals that over 60% of the selected genes are related to many cancers that are being classified.

4:00 Conference Adjourns

SOURCE

http://www.bio-itworldexpo.com/Bioinformatics/