Original Agenda
We are actively working with our speakers to confirm their availability for our new dates. Initial response from our speakers has been very positive, and we are optimistic we will have the new programs ready to share here soon.

Open Access and Collaborations

The Open Access and Collaborations track presents case studies on collaborative technologies and methodologies used to aggregate and harmonize data from heterogeneous sources to accelerate translational and clinical research. Speakers will show novel approaches of key drivers, technology innovations, collaboration platforms, open-source frameworks, legal considerations, and other factors that are managing data and empowering transformative changes through translation. Additional themes that will be covered include: emerging security; analytic, semantic capabilities; FAIR data practices and applications; data commons; implications of Europe's Plan S on publishing in the United States; and large collaborative datasets.

Final Agenda

Monday, April 20

9:00 am - 5:00 pm Hackathon*

*Pre-registration required.

Tuesday, April 21

7:30 am Workshop Registration Open and Morning Coffee

8:30 am - 3:30 pm Hackathon*

*Pre-registration required.


8:30 - 11:30 am Recommended Morning Pre-Conference Workshops*

W4. Beyond Process and Technology – The Human Side of Collaboration

Celeste Blackman, Co-Founder, Green Zone Culture Group

Ian Fore, PhD, Senior Biomedical Informatics Program Manager, Center for Biomedical Informatics and Information Technology, National Cancer Institute

Melissa Nisonger, Analyst, NetImpact Strategies, Inc.

12:30 - 3:30 pm Recommended Afternoon Pre-Conference Workshops*

W11. AI-Celerating R&D: Foundational Approaches to How Emerging Technologies Can Generate Value

Brian Martin, Head of AI in R&D Information Research, Senior Principal Data Scientist, AbbVie

*Separate registration required.

2:00 - 6:30 Main Conference Registration Open

PLENARY KEYNOTE SESSION

4:00 Welcome Remarks

Cindy Crowninshield, RDN, LDN, Executive Event Director, Cambridge Healthtech Institute

 

 

 

4:05 Keynote Introduction

4:15 PLENARY KEYNOTE PRESENTATION: NIH’s Strategic Vision for Data Science

Susan K. Gregurick, PhD, Associate Director, Data Science (ADDS) and Director, Office of Data Science Strategy (ODSS), National Institutes of Health

 

 

 

 

Rebecca Baker, PhD, Director, HEAL (Helping to End Addiction Long-term) Initiative, Office of the Director, National Institutes of Health

 

 

 

 

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

 

 

Wednesday, April 22

7:30 am Registration Open and Morning Coffee

PLENARY KEYNOTE SESSION

8:00 Welcome Remarks

Allison Proffitt, Editorial Director, Bio-IT World

 

 

 

8:05 Keynote Introduction

8:15 Toward Preventive Genomics: Lessons from MedSeq and BabySeq

Robert Green, MD, MPH, Professor of Medicine (Genetics) and Director, G2P Research Program/Preventive Genomics Clinic, Brigham & Women’s Hospital, Broad Institute, and Harvard Medical School

 

 

 

8:45 PANEL DISCUSSION: Game On: How AI, Citizen Science, and Human Computation Are Facilitating the Next Leap Forward

Seth CooperSeth Cooper, PhD, Assistant Professor, Khoury College of Computer Sciences, Northeastern University

 

 

 

 

 

Lancashire_LeeLee Lancashire, PhD, Chief Information Officer, Cohen Veterans Bioscience

 

 

 

 

 

Pietro Michelucci, PhD, Director, Human Computation Institute

 

 

 

 

 

Jérôme WaldispühlJérôme Waldispühl, PhD, Associate Professor, School of Computer Science, McGill University

 

 

 

 

 

While the precision medicine movement augurs for better outcomes through targeted prevention and intervention, those ambitions entail a bold new set of data challenges. Various panomic and traditional data streams must be integrated if we are to develop a comprehensive basis for individualized care. However, deriving actionable information requires complex predictive models that depend on the acquisition and integration of patient data on a massive scale. This picture is further complicated by new data streams emerging from quantified self-tracking and health social networks, both of which are driven by experimentation-feedback loops. Tackling these issues may seem insurmountable, but recent advancements in human/AI partnerships and crowdsourcing science adds a new set of capabilities to our analytic toolkit. This talk describes recent work in online collective systems that combine human and machine-based information processing to solve biomedical data problems that have been otherwise intractable, and an information processing ecosystem emerging from this work that could transform the landscape of precision medicine for all stakeholders.

Vast_Data

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

BUILDING AND SUSTAINING SUCCESSFUL SCIENTIFIC COLLABORATION TEAMS AND DATA MODELS

10:50 Organizer’s Welcome Remarks

Cambridge Healthtech Institute

10:55 Chairperson’s Remarks

11:00 Building Interdisciplinary Research Teams: Opportunities and Challenges

Bennett_MichelleL. Michelle Bennett, PhD, Director, Center for Research Strategy, National Cancer Institute

Biomedical research over the last decade has become increasingly complex. The field recognizes the need to bring different disciplinary experts together to solve challenging scientific questions. No longer is a single disciplinary perspective enough for truly breakthrough research advances. It is the science and the possibility of making a major advance that brings people together to form a research team. Once the team has been assembled, it becomes critical for the leader(s) of the team to recognize that there is much more than the science to tend to.

11:30 A Common Data Model Proposal to Facilitate and Encourage Data Sharing and Reuse

Reinold_KathyKathy Reinold, Principal Data Modeler, Broad Institute of Harvard and MIT

Biomedical researchers have access to many data sources, but finding data with specific characteristics remains a challenge. Datasets have different metadata, format, and structure. At the Broad Institute, we envision a simpler and more comprehensive search capability to allow researchers to find and reuse data across many datasets. We propose a cross-domain data model built specifically to facilitate search and reuse. We share our methods, lessons learned, and status.

12:00 pm Sponsored Presentation (Opportunity Available)

12:30 Session Break

12:40 Luncheon Presentation (Sponsorship Opportunity Available)

1:40 Session Break

BUILDING DATA PLATFORMS TO ACHIEVE PATIENT CENTRICITY

1:50 Chairperson’s Remarks

Alexander Sherman, Director, Center for Innovation and Bioinformatics, Massachusetts General Hospital

1:55 Enabling the Connection between Preclinical and Clinical Dat

Lange_MichaelMichael Lange, ML/AI Lead, R&D Informatics, Small Molecule Discovery Informatics, Roche

Preclinical Project Data Hub is going clinical. Over the past years, it was established in Small Molecule Discovery and recently expanded into Large Molecule Research. Next stop: Clinical Data. We plan to provide our users with an application that allows the connection between preclinical and clinical metadata.

2:15 A Comprehensive Platform for Innovation with Data

Shah_AjayAjay Shah, PhD, MBA, Executive Director & Head of IT for Translational Medicine, Bristol-Myers Squibb

Sage is a comprehensive platform that enables FAIR data, for data ranging from discovery, clinical research, and real-world. This talk will focus on the overview of Sage and solutions developed in Sage ecosystem for biomarker analytics, including an overview of essential components of the platform, such as uniform high-quality data ingestion, data lake enhancement with semantic integration conformance of data, and a reproducible research framework.

2:35 Maximizing Real-World Assets through a Comprehensive Patient Data Platform

Wang_AlbertAlbert Wang, MS, Director, IT for Translational Research & Technologies, Bristol-Myers Squibb

Sage ecosystem is a cross-functional cohesive platform for finding, accessing, integrating, and analyzing patient-centric data. This talk will focus on real-world data (RWD). It will highlight how Sage catalogs, models, integrates, conforms, and presents patient-level metadata across all RWD assets to facilitate downstream cross-dataset analysis within an integrated managed analytics environment. This talk will touch on the business drivers for this initiative, our current progress, as well as some lessons learned.

Informa_PharmaIntelligence_NEW

2:55 Optimizing Site Feasibility using AI and Predictive Insights

Nicola Marlin, Chief Product Office, Pharma Intelligence

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

DATA COMMONS IN PRACTICE

4:00 Chairperson’s Remarks

William Van Etten, PhD, Senior Scientific Consultant & Founding Partner, BioTeam

4:05 Building Patient Platforms with Gen3 for Research and Real-World Data

Grossman_RobertRobert Grossman, PhD, Frederick H. Rawson Distinguished Service Professor in Medicine and Computer Science; The Jim and Karen Frank Director, Center for Translational Data Science, University of Chicago


4:15 Facilitating Cooperative Data Science in the Cloud with the Gen3 Platform for Creating Data Commons

Meyer_ChristopherChristopher Meyer, PhD, Scientific Support Analyst, Center for Translational Data Science (CTDS), University of Chicago

There is growing appreciation in the scientific community for the value of making data from exploratory pilot projects and published studies available for reuse. With the aim of accelerating new discoveries through the sharing and collaborative re-analysis of data, the University of Chicago has created open source software called “Gen3” for building data commons, which are cloud-based platforms for harmonizing, sharing, and analyzing large datasets contributed by multiple groups or organizations. Background and overview of the Gen3 software architecture and how it is being used will be presented.

4:30 Gabriella Miller Kids First Data Resource Center: Collaborative Platforms for Accelerating Cross-Disease Pediatric Research across Development and Cancer

Heath_AllisonAllison Heath, PhD, Director, Data Technology and Innovation, Center for Data-Driven Discovery in Biomedicine (D3b), Children’s Hospital of Philadelphia

Since launching in October 2018, the Gabriella Miller Kids First (Kids First) Data Resource Center (DRC), has made an increasing number of pediatric genomic studies available to the research community. A “best-of-breed” approach has been taken by our multi-institutional team to develop a platform comprising of reusable technology stack components enabling search and query capabilities coupled with secure workspaces for data analysis. Additionally, the DRC services strive towards a foundation for interoperability with other large-scale data sources, both nationally and globally.

4:45 Our Experience as the First External Organization to Build a Gen3 Data Commons

Van_Etten_WilliamWilliam Van Etten, PhD, Senior Scientific Consultant & Founding Partner, BioTeam

BMS asked BioTeam to build a Data Commons to share FAIR scientific data across their organization. Through work at NCI, BioTeam became acquainted with the open-source Gen3 Data Commons framework developed by the University of Chicago and we chose to leverage Gen3 for this BMS Cloud platform. In this talk, we will describe our experience as the first organization outside of U. Chicago to build a Gen3 Data Commons.

5:00 Silo Breaking with Gen3: Improving the Culture of Data Sharing by Leveraging a Data Commons Approach within a Global Pharmaceutical Company

Daniel Huston, Lead IT Business Partner, Translational Bioinformatics IT for Translational Medicine, Bristol-Myers Squibb

Sharing genomics datasets for collaborative analyses poses critical challenges for pharmaceutical organizations with diverse R&D needs. In 2019, IT for Translational Medicine created “SiloBreaker”; a cross-functional program with the mission to break down the barriers that exist between genomics data and scientists. The team implemented the Gen3 Data Commons framework as its key platform solution. This talk will discuss the significant improvement in the culture of genomics data sharing at BMS achieved through the SiloBreaker program.

5:15 Q&A with Session Speakers

 

Stellus_Technologies

 

 

5:35 Best of Show Awards Reception in the Exhibit Hall with Poster Viewing

 

RedRiver

 

 

 


6:45 End of Day

Thursday, April 23

7:30 am Registration Open and Morning Coffee

PLENARY KEYNOTE SESSION & AWARDS PROGRAM

8:00 Organizer’s Remarks

Cindy Crowninshield, RDN, LDN, Executive Event Director, Cambridge Healthtech Institute

 

 

 

 

8:05 Awards Program Introduction

8:10 Benjamin Franklin Award and Laureate Presentation

J.W. Bizzaro, Managing Director, Bioinformatics.org

 

 

 

 

Discngine8:35 Bio-IT World Innovative Practices Awards

Allison Proffitt, Editorial Director, Bio-IT World

 

 

 

 

9:00 AI in Pharma: Where We Are Today and How We Will Succeed in the Future

Natalija Jovanovic, PhD, Chief Digital Officer, Sanofi Pasteur

 

 

 

 

Penguin_Computing_Tagline 9:45 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced at 10:00

 

 

DATA ECOSYSTEM TO ACCELERATE DATA DISCOVERY AND SHARING FOR BIOMEDICAL RESEARCH

10:30 Organizer’s Remarks

Cambridge Healthtech Institute

10:35 Chairperson’s Remarks

10:40 Cascadia Data Discovery Initiative: Accelerating Health Innovation and Cancer Research through Collaboration, Data Sharing, and Data-Driven Research

Trunnell_MatthewMatthew Trunnell, Vice President and Chief Data Officer, Fred Hutchinson Cancer Research Center


11:10 The National Microbiome Data Collaborative: A FAIR Data Resource for Microbiome Research

Fagnan_KjierstenKjiersten Fagnan, PhD, Chief Informatics Officer, Data Science and Informatics Leader, DOE Joint Genome Institute, Lawrence Berkeley National Laboratory

Our multi-lab collaborative partnership will pilot an integrated, community-centric framework within 27 months to fully leverage existing microbiome data science resources and high-performance computing systems available within the DOE complex for data access, integration, and advanced analyses. In this talk, I will cover some of the challenges in microbiome data sciences and how we aim to overcome these by creating a large, open-access repository of FAIR data.

11:40 Sponsored Presentation (Opportunity Available)

12:10 pm Session Break

12:20 Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own

1:20 Dessert Refreshment Break in the Exhibit Hall with Last Chance Poster Viewing

APPLICATION OF TOOLS IN CLINICAL, POPULATION, AND COLLABORATIVE HEALTH SETTINGS

1:55 Chairperson’s Remarks

Chris Anderson, Editor-in-Chief, Clinical OMICs

2:00 Open-AD: A Radically Open Approach to Diversify the AD Drug Portfolio

Mangravite_LaraLara Mangravite, PhD, President, Sage BioNetworks

Here we describe a radically open approach to diversify the AD drug portfolio. Using multi-omic and genetic models of disease built from human brain data, a suite of emerging therapeutic hypotheses are generated that complement the small set already in drug development. To catalyze rapid evaluation of these targets, target enabling packages – containing computational and experimental resources including prototype drug compounds – are developed and openly distributed for use across the research community.

2:30 Development of Risk Prediction Models for Cardiovascular Diseases and Prostate Cancer Using Deep Learning: Case Studies from Ongoing Collaboration between the Department of Veterans Affairs (VA) and the Department of Energy (DOE)

Madduri_RaviRavi Madduri, Scientist, Data Science and Learning, Argonne National Laboratory; Senior Scientist, University of Chicago Consortium for Advanced Science and Engineering (UChicago CASE)


3:00 A Deluge of Data, Wrangling the UK BioBank and Other NGS Data

Sasson_AriellaAriella Sasson, PhD, Senior Research Investigator, Bristol-Myers Squibb

As the amount of NGS data grows, the basic standard manipulations of data (movement, storage, organization) become non-trivial problems (cost, time, space, corruption). These data, which can grow to petabytes in size, not only bring the question of how we handle the data to the forefront but compound the difficult task of making it maximally useful and accessible to enable the science.

3:30 Open Science with OHDSI: From Question to Evidence in 5 Days

Bochove_Kees_vanKees van Bochove, Founder, The Hyve


4:00 Close of Conference



Platinum Sponsors

accenture

BenchlingNEW

Elsevier-square

L7-informatics

linguamatics

Nutanix

PerkinElmer

Weka_Purple