Genomic Data Sharing. Case Studies, Challenges, and Opportunities for Precision Medicine

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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 developmentand adoption of the GenomicsReporting 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