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.

Data Security and Compliance

Data security is defined by the processes and mechanisms in place that prevent data misuse and identify threat risks. However, many biopharmaceutical research data sources, from IP to genomic to mobile, require different levels of security. The reality is that it matters not where your data exist, but the ways in which data are accessed. Are you doing enough for information security? How do you demonstrate that you are compliant? The Data Security and Compliance track presents in-depth case studies from leading life science organizations who are implementing solutions to address these data security and compliance problems and challenges. Presentations will also address security services from private to cloud-based systems for academic, government, clinical, biomedical, and pharmaceutical networks. Learn how to adopt a data-centric approach to help you reduce costs, mitigate risk, and meet compliance. Data standards for compliance and security need to deal with global communities, and where guidelines and requirements may differ, e.g., GDPR. How do you incorporate this especially when considering the use of real-world data?

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*

W5. Giving the Personalized Digital Health Ecosystem a FAIRshake

Amir Lahav, ScD, Digital Health Innovation Consultant

Avi Ma’ayan, PhD, Professor, Department of Pharmacological Sciences; Director, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai

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

W15. Digital Health Startups Panel and Pitch – Securing Funding and Collaboration

Debbie Lin, PhD MPP, MSc Eng, Executive Director, Boehringer Ingelheim Venture Fund USA, Inc.

Sean Cheng, PhD, Investment Manager, Philips Ventures

Millie Liu, MFin, Founder, Managing Partner, First Star Ventures

Additional Instructors to be Announced

*Separate registration required.

2:00 - 6:30 Main Conference Registration Open


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


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.


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


10:50 Organizer’s Welcome Remarks

Cambridge Healthtech Institute

10:55 Chairperson’s Remarks

11:00 KEYNOTE PRESENTATION: The Road from Data Commons to Data Ecosystems: Challenges, Opportunities, and Emerging Best Practices

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

There are now several large-scale data commons supporting the biomedical research community and the beginnings of data ecosystems. In this talk, we discuss some of the emerging best practices around data ecosystems, as well as some of the challenges and opportunities. We also discuss some case studies of data commons and data ecosystems developing using the open source Gen3 data platform.

11:30 Harnessing Cloud for Mega-Biobanks: Efficient Computing with Sensible Data Governance

Pyarajan_SaijuSaiju Pyarajan, PhD, Director, Center for Data and Computational Sciences, VA Boston Healthcare System; Faculty, Harvard Medical School

Multiple initiatives are currently underway for setting up large biobanks with associated clinical and molecular data. With more than 800,000 samples already collected and genotyped, the Million Veteran Program (MVP), promises a unique opportunity to perform genomic analysis at-scale for meaningful interpretation of results with better confidence. This talk will discuss the infrastructure that facilitates genomic research in MVP as well as the challenges in scaling data, analytics, security and data governance.

12:00 pm Presentation to be Announced


12:15 Presentation to be Announced

12:30 Session Break

12:40 Luncheon Presentation I to be Announced


1:10 LUNCHEON PRESENTATION II: Bioinformatics Pipelines in Azure

Jer-Ming Chia, Principal Program Manager, Microsoft

Scott Jeschonek, Principal Program Manager, Azure, Microsoft

The lunch session will describe how to apply a typical bioinformatics pipeline on Microsoft Azure. Topics will include common workflow frameworks like Cromwell and Nextflow in Azure, data storage and access considerations, and a discussion about the advantages of leveraging the latest AMD EPYC based virtual machines in these pipeline architectures.

1:40 Session Break


1:50 Chairperson’s Remarks

Brian Bissett, MBA, MSEE, FAC P/PM, IT Specialist, Hardware Engineering, US Government

1:55 Defending Against the Persistence of Inevitability

Bissett_BrianBrian Bissett, MBA, MSEE, FAC P/PM, IT Specialist, Hardware Engineering, US Government

Most data breaches represent a systemic breakdown along multiple lines of both technical and human factors. While many factors can contribute to an unauthorized release, the effort necessary to protect against these factors is not equal. This discussion will be from a holistic viewpoint of many security breaches, the breakdowns in fundamental security concepts which lead to the breaches, and the factors of paramount consideration in protecting an enterprise.

2:15 Data Security and Governance for Biopharma

Gambhir_JyotinJyotin Gambhir, MBA, CISM, Founder, SecureFLO

Governance provides a playbook for a biopharma company to manage security and privacy compliance. Good governance leads to a better managed goal and a focused IT environment. CyberHygiene today is critical for any company developing a drug or researching cures and trying to protect intellectual property, as well as subjects’ personal information. Regulations under FDA and FTC, as well as EU GDPR, can be complicated.

2:35 Dynamic Encryption and Watermarking of Genomic Sequencing Data to Facilitate Privacy-Preserving Ownership-Based Data Governance

Gai_XiaowuXiaowu Gai, PhD, Director, Bioinformatics; Associate Professor, Clinical Pathology, Pathology & Laboratory Medicine, Children’s Hospital of Los Angeles

To facilitate privacy-preserving ownership-based data governance, we developed two novel algorithms which can be used to implement flexible fine-grained protection of genomic data: a) dynamic privacy-preserving encryption of user-specified genomic regions; and b) ownership and utility-preserving watermarking of the sequencing data. This empowers individuals to control when, for how long, and for what purpose any portion of their genomic data is shared, all in an auditable manner.

2:55 Presentation to be Announced

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


4:00 Chairperson’s Remarks

Sanjay Joshi, Industry CTO, Healthcare, Dell EMC

4:05 PANEL DISCUSSION: Real-World Evidence (RWE): Data Provenance, Format, Ingest, Quality (Bias), Integration, Visualization, Transformation, Verification & Validation, and Implementation


Joshi_SanjaySanjay Joshi, Industry CTO, Healthcare, Dell EMC


Gamerman_VictoriaVictoria Gamerman, PhD, Head of US Health Informatics and Analytics, Boehringer Ingelheim

Goetz_LauraLaura Goetz, FACS, MD, MPH, Assistant Clinical Professor, Department of Medical Oncology & Therapeutics Research, Division of Clinical Cancer Genomics, City of Hope Comprehensive Cancer Center

Kenna Mills Shaw, PhD, Executive Director, Institute for Personalized Cancer Therapy, MD Anderson Cancer Center

Kelly Zou, PhD, PStat®, ASA Fellow, Vice President, Medical Analytics & Insights (MAI), R&D and Medical, Upjohn Division, Pfizer Inc.

The future of the intersection of healthcare and the life sciences will be data- and process-focused, not application- or software-focused. “Bringing the analytics to Data” is the challenge from an infrastructure and methods perspective. According to the FDA, Real-World Evidence (RWE) is defined as “the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of Real-World Data (RWD): e.g., effectiveness or safety outcomes from an RWD source in randomized clinical trials or in observational studies.” Our topical, honest, and “real-world” panel will discuss the sources of RWD (EHR, Claims & Billing, Registries, Patient Reported Data, etc.) and their process implications for RWE and the future of clinical trials themselves.

5:05 Presentation to be Announced

5:20 Sponsored Presentation (Opportunity Available)





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






6:45 End of Day

Thursday, April 23

7:30 am Registration Open and Morning Coffee


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




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


1:55 Chairperson’s Remarks

Nick Lynch, PhD, Founder and CTO, Curlew Research; External Liaison and Advisor, Pistoia Alliance

2:00 AI & Strategy Development: Collaboration, Externalisation, Data Sharing and Integration

Lynch_NickNick Lynch, PhD, Founder and CTO, Curlew Research; External Liaison and Advisor, Pistoia Alliance

AI is at peak hype at present, but its full potential will not be realised unless a clear and incremental strategy is adopted. In this talk, we will discuss the current state of collaboration and pre-competitive activities within AI in Life Sciences R&D, where this is heading and how we can influence it as a community. We will discuss how data sharing and the use of data standards will need to underpin the future potential of AI and looking ahead to the future approaches.

2:30 Bridging Business and Technical Functions: How to Translate AI between the Two

Allgood_BrandonBrandon Allgood, PhD, Vice President, Head of Technology and Innovation, Integral Health; Co-Founder and Vice Chair, Alliance for Artificial Intelligence in Healthcare (AAIH)

Artificial Intelligence has been studied by computer scientists for more than 70 years. The term ‘Artificial Intelligence’ itself was coined in 1956, but the theory and topics that became known as AI have a much longer history. Even so, it remains one of the most complex and misunderstood topics in computer science because of the vast number of techniques employed and the often nebulous goals being pursued. Add to this the complexities of business and it is no wonder that in most cases, AI is taking a long time to show impact. But. the transformation that AI will bring is worth it. I will discuss how companies can approach and implement AI for success. I will also help to dispel many of the myths and hype surrounding AI, focusing on how companies can quickly get to practical solutions.

3:00 Generating Genomic Variant Data: Solving Both Data Privacy and AI Robustness Problems

neumann_ericEric Neumann, PhD, CEO & Founder, AIDAKA LLC

In Scientific Data Analytics, the utility of data is accompanied by issues around individual privacy guarantees. Many argue that having large sets of detailed data is essential for effective machine learning. Yet the same detail impacts privacy issues via the increased risk of exposure of matched individuals behind such data. We show here that both issues are usually two sides of the same coin and can both be solved together.

3:30 Applications of Groundbreaking AI Technology to Produce Realistic, Fully De-Identified Patient Data to Test and Validate Preclinical Modelling Methods

Robasky_KimberlyKimberly Robasky, PhD, Head, Translational Science, Renaissance Computing Institute (RENCI)

Researchers use biomarker and outcomes data to model and predict adverse events. However, access restrictions to safeguard patient privacy necessarily slow down the rate of discovery and increase research costs via IRB review. For these reasons, synthetic data that preserve patient-variable relationships have been an active area of research. We discuss current advances made by generative models in this area and the breakthrough AI technologies accelerating those advances.

4:00 Close of Conference

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