BioData World Congress Americas Day 1



Robert C Green

The MedSeq and BabySeq Projects: Randomized Trials in Genomic Medicine

  • The MedSeq Project seeks to develop a process to integrate genome sequencing into the clinical practice of general and disease-specific medicine and explore the impact of doing so.
  • The BabySeq Project seeks to examine how best to use genomics in clinical pediatric medicine for both healthy newborns and newborns in the NICU.
Kathy Hudson

An update on the Precision Medicine & BRAIN Initiative

Robert Plenge

Human genetics and drug discovery

Therapeutic interventions that improve the lives of patients are essential in our modern health care system. Unfortunately, too many drugs fail in late stage clinical trials, which drive up the cost of R&D and create conservative cultures in many biopharmaceutical companies. Further, for the drugs that show success in late stage trials, too many are insufficiently differentiated from standard of care treatment to bend the trajectory of health care for suffering patients.  Human genetics provides an approach that overcomes many of the key challenges of drug R&D.  This presentation will address: (1) fundamental challenges of drug R&D; (2) the role of human genetics in improving the novelty, efficiency and productivity of drug R&D; and (3) emerging opportunities that capitalize on advances in new technology and large genotype-phenotype resources.
David Hunter

Standards of evidence for decision making in personalized medicine

  • How do we balance individual versus group average data in PM
  • What is an “n-of-1” study?
  • How can we communicate –omic scale personalized test results?

Morning coffee and Poster Viewing

Professor Louis Fiore

The Department of Veterans Precision Oncology Program: The Crossroads of Clinical Care and Research

  • Description of the VA National Precision Oncology Program
  • Use of EHR to create a Learning Healthcare System environment 
  • Re-use of EHR data for research purposes
Dr Sandro Galea

The personalized medicine chimera

  • Population health is produced through a combination of genetic, social, environmental factors
  • A focus only on one dimension of the causal cascade dooms us to failure
  • We need a recalibration of our emphasis to include focus on multiple determinants of population health


round tables


1. Big Data Genomics and Drug Development
  • Justin H. Johnson, Associate Director and Principal Translational Genomic Scientist, AstraZeneca
  • Joshua McElwee, Group Lead - Immunogenetics, Genetics and Pharmacogenomics, Merck
  • Christopher Sprengle, Director of Human Genetics Information Technology, Regeneron Pharmaceuticals

2. Cloud Computing and Precision FDA
  • Denis Dean, Senior Scientist, Seven Bridges Genomics
  • Rachel Goldfedder, Partner, Precision FDA Community
  • Peter Tonnelato, Senior Research Scientist and Director, Harvard Medical School
  • Monica Wang, Principal Bioinformatics Architect, Project and Program Manager Global Research Systems, Takeda Oncology
  • David Bernick, Director of Technology Operations - Data Sciences, Broad Institute
3. IT Infrastructure and HPC in Genomics
  • James Lowey, CIO, T-Gen
  • Rikki R. Godshall,  Technical Director of HPC, Perelman School of Medicine, University of Pennsylvania
  • Chris Dwan, Director, Research Computing, Broad Institute of MIT and Harvard
  • Yirong Wang, Director of Production Bioinformatics, Mount Sinai Genetic Testing Laboratory, 
  • Icahn Institute for Genomics and Multiscale Biology
  • Jeffrey Bond, Lead Bioinformatician, NMTRC, Spectrum Health System
4. Translation of NGS Into the Clinic
  • Catherine Brownstein, Director, Molecular Genomics Core Facility , Boston Children's Hospital
  • Yiu-Lian Fong, Senior Director, Global Diagnostic Innovation, Johnson and Johnson
  • Sandy Aronson, Executive Director of Information Technology, Partners HealthCare Personalized Medicine
  • Leah Voigt, Director of Research & Chief Privacy Officer, Spectrum Health System
  • Patrick Lacey, President,  BeatNB Foundation
  • Giselle Sholler, Chair, NMTRC
  • Mark Rubin, Founding Director, Englander Institute for Precision Medicine
  • Leah Voigt, Chief Privacy & Research Integrity Officer,Spectrum Health System
  • Big Data Genomics and Drug Development
  • Mr John Cai

    Mr John Cai, Director, Medical Informatics, Celgene

  • IT Infrastructure and HPC in Genomics
  • Jeffrey Bond

    Jeffrey Bond, Lead Bioinformatician, NMTRC, Spectrum Health System

    Transfering the power of HPC and genomics into the clinic

    Big Data: Challenges in Precision medicine

    Big Data: HPC and analysis of genomic data

    Integrating E-Health Records and Genomic Data

    • Understand why using the narrative text of the record is more leveraged than using codified data for genomic studies.
    • Understand how a “deep-phenotype-first” study design can increase the power of such studies.
    • Understand how SMART/FHIR can hasten the integration of genomics into clinical practice.
    Big Data: Challenges in Precision medicine

    From data sets to data assets: A probabilistic framework for bridging petabytes of genomics data to large scale analysis

    • More than just an analogy or a metaphor, data are assets that have value. But unlike most physical assets, the value of digital assets resides in their usage and context.
    • Shifting the perspective from data sets to data assets; similarities and differences with asset management
    • Introduction to the principles of the value of data and information
    • Using data valuation for driving and optimising data management lifecycle, leading to effective decision support and data exploitation
    Big Data: Challenges in Precision medicine

    Using gene-disease association big data to improve drug development

    • There are substantial opportunities for genetics to help improve drug discovery
    • In spite of the flood of genetic association data available, there are many limitations to find and apply that knowledge
    • We share our efforts to address those limitations in our discovery research and discuss future needs
    Big Data: HPC and analysis of genomic data

    The future of large-scale clinical genomics through databases and HPC

    • Rapid generation of genomic data provides a wealth of opportunities
    • How can laboratories and health systems harness this data to improve clinical genomics
    • Lessons learned and insights gained from setting up infrastructure to support this
    Big Data: Challenges in Precision medicine

    Medbook for Cancer

    • Building Platforms to integrate private and public data
    • Generating apps for 3rd party use

    Afternoon Refreshments


    Speed Networking

    Genomics and Health: Data Security and Management, IT Infrastructure and data storage

    Big Data: Challenges in Precision medicine

    Genomics and Health: Data Security and Management, IT Infrastructure and data storage

    Application of cloud computing and local HPC to NGS data analysis

    • Challenges on large-scale WGS and RNA-Seq data analysis
    • Cloud-based Rainbow/Stormbow and local HPC-based QuickRNASeq for large-scale NGS data analysis 
    • Lessons we learned on big data analysis in Amazon cloud
    Big Data: Challenges in Precision medicine

    What it takes to do precision medicine at the million person scale

    • Researchers around the world are working on building population-scale genome-phenome datasets to accelerate precision medicine. The scale of these datasets is exploding, which presents unique opportunities and challenges. We will discuss this in the context of one of the largest projects in the world - the U.S. Department of Veterans Affairs Million Veteran Program.
    • Exploring solutions for the  bioinformatics and infrastructure challenges in massive-scale genomics
    • Graph methods to develop new tools for precision medicine
    Big Data: Challenges in Precision medicine

    Integration of genetic medicine into healthcare

    • What data can we generate from a genome, how well can we interpret it, and what does it cost?
    • What genomic information do patients want?
    • What genomic information do doctors want and how do they use it?
    Genomics and Health: Data Security and Management, IT Infrastructure and data storage

    PrecisionFDA: Objective, Scope and Progress to date

    • Review the PrecisionFDA objective
    • Collaborations and progress to date
    • Future plans for engaging with the broader community and accelerate the translation of whole-omic sequencing into best practice precision medicine
    Big Data: Challenges in Precision medicine

    Integration of genetic, and biomarker data to identify, and personalize treatment for individuals at high-risk of developing MS or cognitive decline

    Lori Chibnik, Associate Professor, Broad Institute of MIT & Harvard
    Genomics and Health: Data Security and Management, IT Infrastructure and data storage

    Build out of a highly secured yet flexible cloud infrastructure by the Regeneron Genetics Center to support very large scale genomics data management

    • The Regeneron Genetics Center (RGC) has generated and analyzed whole exomes (WES) at significant scale and at an ever increasing pace, requiring flexible and scalable cloud-based infrastructure that must be well secured.  A cloud security scheme has been developed with genomics analysis and technology partners that provides “better than LAN” security features due to cloud based account separation and abstractions.
    • Genomics data analysis and delivery benefits from the adaptation of genomics software tools with data warehouses and callable web APIs for improved data management.  Delivery of large data freezes to collaborators from the cloud is a significantly improved method over traditional extranet- or DMZ-based solutions, improving the provider’s security posture.
    • RGC has efforts underway to evaluate and improve data analysis and management at ever-greater scale, as WES sequencing goals continue to be raised due to successes to date.  Software-defined infrastructure allows systems development to keep pace with laboratory advances to meet the new goals.
    Big Data: Challenges in Precision medicine

    Real-world treatment pathways tied into the delivery of precision medicine

    • Real-world treatment pathways vs. treatment guidelines – what’s the difference?
    • Real-world treatment pathways vs. payer/providers pathways – what’s the difference?
    • Real-world treatment pathways at the point of care for precision medicine – what’s their use?
    Bob Terbrueggen

    High Frequency Transcriptomics: Direct-to-Patient Clinical Studies Power Advances in Monitoring Disease Activity and Therapy Response

    • The value of disease activity monitoring and therapy monitoring using blood-based transcriptomics
    • Challenges to making immune transcriptomics feasible
    • Using Direct-to-Patient sampling to drive larger cohorts of subjects
    • Key technologies to enable High-Frequency Transcriptomics

    Evening Party

    last published: 14/Sep/16 11:05 GMT