Genomic Data Sharing

Case Studies, Challenges, and Opportunities for Precision Medicine

1st Edition - November 29, 2022
Imprint: Academic Press
Editors: Jennifer B. Mccormick, Jyotishman Pathak
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 1 9 8 0 3 - 2
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 1 9 8 0 4 - 9

Genomic Data Sharing: Case Studies, Challenges, and Opportunities for Precision Medicine provides a comprehensive overview of current and emerging issues in genomic data sharin… Read more

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Genomic Data Sharing: Case Studies, Challenges, and Opportunities for Precision Medicine provides a comprehensive overview of current and emerging issues in genomic data sharing. In this book, international leaders in genomic data examine these issues in-depth, offering practical case studies that highlight key successes, challenges and opportunities. Sections discuss the eMERGE Network, Undiagnosed Disease Network, Vanderbilt Biobank, Marshfield Clinic Biobank, Minnesota Authorization, Rochester Epidemiology Project, NIH sponsored biobanks, GINA, and Global Alliance for Genomics and Health (GA4GH). In addition to these perspectives from the frontlines, the book also provides succinct overviews of ethical, legal, social and IT challenges.

Clinician investigators, clinicians affiliated with academic medical centers, policymakers and regulators will also gain insights that will allow them to navigate the increasingly complex ethical, social and clinical landscape of genomic data sharing.

Cover Image
Title Page
Copyright
Table of Contents
Contributors
Chapter 1 Introduction to the volume
Acknowledgments
Reference
Chapter 2 From public resources to improving health: How genomic data sharing empowers science and medicine
2.1 Introduction
2.2 The Human Genome Project set the paradigm for genomic data sharing
2.3 Genomic data sharing enables multiple areas of research
2.4 Putting data sharing into practice
2.5 Data sharing will propel precision medicine
2.6 Learning healthcare systems and data sharing
2.7 Need for responsible data stewardship
2.8 Barriers to genomic data sharing
2.9 Conclusion
References
Chapter 3 Biobank case example: Marshfield clinic
3.1 Stakeholder engagement
3.2 Technical procedures to facilitate genomic data sharing with collaborators
3.3 Phase 1—Sample identification, phenotyping, and quality controls
3.4 Phase 2—Data integration and sample return
3.5 Phase 3—Finalizing datasets
3.6 Phase 4—Data access
3.7 Summary
References
Chapter 4 Multidirectional genetic and genomic data sharing in the All of Us research program
4.1 Introduction
4.2 Sharing data with researchers
4.3 Returning genetic and genomic results to participants
4.4 Concluding remarks
References
Chapter 5 A community approach to standards development: The Global Alliance for Genomics and Health (GA4GH)
5.1 Introduction
5.2 The rationale for and promise of an international alliance (2012–2014)
5.3 Convening the community (2014–2017)
5.4 GA4GH connect (2017–2019)
5.5 Gap analysis (2019–2021)
5.6 Beyond GA4GH connect (2021 and beyond)
5.7 A novel approach to funding and support
5.8 Three recommendations
5.9 Conclusion
Acknowledgments
References
Chapter 6 Clinical genomic data on FHIR®: Case studies in the development and adoption of the Genomics Reporting Implementation Guide
6.1 Background
6.2 Case studies: implementation of HL7 FHIR
6.3 Conclusion
Acknowledgments
Bibliography
Chapter 7 Genomics data sharing
7.1 Introduction
7.2 Current practices
7.3 Case study: H3Africa model
7.4 Beacons
7.5 Data commons model
7.6 Common challenges in genomic data sharing and managing risks
7.7 Executive summary
References
Chapter 8 Data standardization in the omics field
8.1 Introduction
8.2 Omics data standardization
8.3 Challenges to data standardization
8.4 Executive summary
Acknowledgments
Conflict of Interest
References
Chapter 9 Data sharing: The public's perspective
9.1 Public willing to participate?
9.2 Concerns unique to genomic data?
9.3 Support for broad data sharing
9.4 A question of context
9.5 Policy for the people
9.6 Further research
References
Chapter 10 Genetic data sharing in the view of the EU general data protection regulation (GDPR)
10.1 Introduction
10.2 The special status of genetic/genomic data
10.3 The GDPR framework for scientific research
10.4 Consent for genetic data sharing under EU law
10.5 Alternative legal bases for genetic data sharing: shifting attention away from consent
10.6 Concluding remarks
References
Chapter 11 Genomic data sharing and intellectual property
11.1 Forms of intellectual property protection for genomic data
11.2 Databases, data protection, and terms of use
11.3 Patents
11.4 Conclusion
References
Chapter 12 Data governance
12.1 Background: precision medicine genomics and governance
12.2 How data governance shapes precision medicine
12.3 The road ahead: how data governance should shape the future of precision medicine
References
Index

Jennifer B. Mccormick

Dr. McCormick is an interdisciplinary academic having completed a doctorate degree in molecular and cellular biology, postdoctoral fellowship in biological chemistry, masters’ degree in public policy, and NIH Center of Excellence in ELSI Research fellowship. She conducts empirical studies examining the policy implications and ethical challenges of translating research into clinical care and public health. Much of her work focuses on the ethical, legal, political, and social implications of medical record and genomic data sharing, the challenges to protecting participants’ privacy and confidentiality in the era of ‘big data’, and the ethical complexities presented by translating genomic research findings into clinical and public health domains. She has also been involved in initiatives aimed at enhancing human participation in research and promoting professionalism and social responsibility in biomedical research. She lectures frequently on topics related to research and translational research ethics, translational genomics, and social responsibility and policy. She has published on topics related to research ethics consultation, genetic and genomic research and biobanking, human research participant engagement and protection, and challenges in translational research. Beyond Sputnik: US Science Policy in the 21st Century (Neal, Smith, and McCormick) is considered one of the first general textbooks on national science policy and is used in science policy training and fellowship programs.

Affiliations and expertise

Associate Professor, Department of Humanities, Penn State College of Medicine, Hershey, PA, USA

Jyotishman Pathak

Dr. Pathak is the Frances & John L. Loeb Professor of Medical Informatics and the Chief of Division of Health Informatics at Weill Cornell Medicine, Cornell University, New York. Prior to joining Weill Cornell, he was the Professor of Biomedical Informatics at Mayo Clinic in Rochester, Minnesota (2007-2015) where he led two major NIH/HHS funded initiatives—the Electronic Medical Records and Genomics (eMERGE) and Strategic Health IT Research Project (SHARP) projects—which have pioneered techniques for high-throughput phenotyping from the electronic medical record. His research interests and expertise lie in developing and applying informatics methods for data mining and phenotype extraction from electronic medical records (EMRs), and their applications in pharmacogenomics, comparative effectiveness research, and population health research, particularly focusing on mental health disorders. Throughout his career, he has led and collaborated across multiple investigators in several NIH/DHHS consortiums, including, most recently at Mayo, as the Co-PI of eMERGE and PI of PCORI Learning Health Systems Clinical Data Research Network, and currently at Weill Cornell, as the Co-PI for the PCORI New York City Clinical Data Research Network (NYC-CDRN) and the PI for NIH Big Data to Knowledge (BD2K) R25 Training and Education Program on Biomedical Informatics (BD2BMI).

Affiliations and expertise

Frances and John L. Loeb Professor of Medical Informatics and Chief, Division of Health Informatics, Weill Cornell Medicine, Cornell University, NY, USA

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