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Genomic data sharing : case studies, challenges, and opportunities for precision medicine /

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

Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: McCormick, Jennifer B., Pathak, Jyotishman
Format: eBook
Language:English
Published: London, UK : Academic Press, 2023.
Subjects:
Genomics > Data processing.
Genomes > Data processing.
Precision medicine > Data processing.
Genomics.
Genomics
Information Dissemination
Precision Medicine
Génomique > Informatique.
Génomes > Informatique.
Médecine de précision > Informatique.
Génomique.
Genomes > Data processing
Genomics > Data processing
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front cover
  • Half title
  • Title
  • Copyright
  • Contents
  • Contributors
  • 1 Introduction to the volume
  • Acknowledgments
  • References
  • 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
  • Ethical/moral
  • Scientific/practical
  • 2.3.1 Research using model organisms
  • 2.3.2 Research using human data
  • 2.3.3 Technical analysis development
  • 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
  • 3 Biobank case example: Marshfield clinic
  • 3.1 Stakeholder engagement
  • 3.1.1 External stakeholders
  • 3.1.2 Internal stakeholders
  • 3.2 Technical procedures to facilitate genomic data sharing with collaborators
  • 3.3 Phase 1-Sample identification, phenotyping, and quality controls
  • 3.3.1 Phenotype data quality controls
  • 3.3.2 Sample data quality controls
  • 3.4 Phase 2-Data integration and sample return
  • 3.5 Phase 3-Finalizing datasets
  • 3.6 Phase 4-Data access
  • 3.6.1 Pilot genomic data sharing projects with participants
  • 3.7 Summary
  • References
  • 4 Multidirectional genetic and genomic data sharing in the All of Us research program
  • 4.1 Introduction
  • 4.2 Sharing data with researchers
  • 4.2.1 Relevant considerations
  • 4.2.2 Guiding concepts for sharing data with researchers
  • 4.2.3 Implementation
  • 4.2.4 Lessons learned and future directions
  • 4.3 Returning genetic and genomic results to participants
  • 4.3.1 Relevant considerations
  • 4.3.2 Guiding concepts for the return of genetic and genomic results.
  • 4.3.3 Implementation
  • 4.3.4 Lessons learned and future directions
  • 4.4 Concluding remarks
  • References
  • 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)
  • 5.5.1 Technical alignment
  • 5.5.2 Implementation support
  • 5.5.3 Clinical engagement
  • 5.6 Beyond GA4GH connect (2021 and beyond)
  • 5.7 A novel approach to funding and support
  • 5.8 Three recommendations
  • 5.8.1 Community needs should drive development
  • 5.8.2 Create global equity and opportunity to ensure fit-for-purpose development
  • 5.8.3 Strive for consensus and intentional decision-making
  • 5.9 Conclusion
  • Acknowledgments
  • References
  • 6 Clinical genomic data on FHIR®: Case studies in the development and adoption of the Genomics Reporting Implementation Guide
  • 6.1 Background
  • 6.1.1 Health Level 7 (HL7)
  • 6.1.2 HL7 Clinical Genomics
  • 6.2 Case studies: implementation of HL7 FHIR
  • 6.2.1 Exchanging HLA data for histocompatibility and immunogenetics
  • 6.2.2 Electronic medical records and genomics (eMERGE) network
  • 6.2.3 Minimum common oncology data elements (mCODE)
  • 6.3 Conclusion
  • Acknowledgments
  • References
  • 7 Genomics data sharing
  • 7.1 Introduction
  • 7.2 Current practices
  • 7.3 Case study: H3Africa model
  • 7.3.1 Data archive
  • 7.3.2 Data sharing, access and release policy
  • 7.3.3 Data access committee
  • 7.3.4 H3Africa catalog
  • 7.4 Beacons
  • 7.5 Data commons model
  • 7.5.1 Data commons in Africa
  • 7.6 Common challenges in genomic data sharing and managing risks
  • 7.6.1 ELSI
  • 7.6.2 Motivational challenges
  • 7.6.3 Technical challenges
  • 7.6.4 Infrastructure challenges.
  • 7.6.5 Economic and political challenges
  • 7.6.6 Intellectual property rights
  • 7.7 Executive summary
  • References
  • 8 Data standardization in the omics field
  • 8.1 Introduction
  • 8.1.1 Defining standardization
  • 8.2 Omics data standardization
  • 8.2.1 Existing standards and resources
  • 8.2.2 Data standardization and FAIR data
  • 8.3 Challenges to data standardization
  • 8.3.1 Adoption challenges
  • 8.3.2 Policy challenges
  • 8.4 Executive summary
  • Acknowledgments
  • Conflict of Interest
  • References
  • 9 Data sharing: The public's perspective
  • 9.1 Public willing to participate?
  • 9.2 Concerns unique to genomic data?
  • 9.2.1 Data concerns
  • 9.2.2 Matters of trust
  • 9.3 Support for broad data sharing
  • 9.4 A question of context
  • 9.5 Policy for the people
  • 9.6 Further research
  • References
  • 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
  • 10.4.1 (Informed) consent for genetic data sharing: two distinct requirements arising from regulatory and ethics frameworks
  • 10.4.2 What type of consent is considered valid under the GDPR?
  • 10.5 Alternative legal bases for genetic data sharing: shifting attention away from consent
  • 10.6 Concluding remarks
  • References
  • 11 Genomic data sharing and intellectual property
  • 11.1 Forms of intellectual property protection for genomic data
  • 11.1.1 Copyright
  • 11.2 Databases, data protection, and terms of use
  • 11.3 Patents
  • 11.3.1 Early biotech patents
  • 11.3.2 Genetic patents and utility
  • 11.3.3 Bermuda and official patent deterrence
  • 11.3.4 The Ft. Lauderdale principles
  • 11.3.5 NIH's evolving policy toward patenting.
  • 11.3.6 Patent deterrence outside the United States
  • 11.3.7 Nongovernmental limitations on patenting genomic data
  • 11.3.8 The SNP consortium and defensive patenting
  • 11.3.9 Genetic sequence patents under Myriad11Detailed accounts of the gene patenting litigation involving Myriad Genetics can be found in Refs. [50] and [54].
  • 11.3.10 Diagnostic patents under Mayo
  • 11.3.11 Licensing of genomic inventions
  • 11.4 Conclusion
  • References
  • 12 Data governance
  • 12.1 Background: precision medicine genomics and governance
  • 12.2 How data governance shapes precision medicine
  • 12.2.1 Retrospective data integration
  • 12.2.2 Prospective data collection
  • 12.2.3 Data access
  • 12.3 The road ahead: how data governance should shape the future of precision medicine
  • References
  • Index
  • Back cover.