• NIH May 1, 2019 | K01

    Genetic data partnerships: Enabling equitable access within academic/private data sharing agreements

    Principal Investigator(s): SPECTOR-BAGDADY, KAYTE KELLEHER;

    Institution: UNIVERSITY OF MICHIGAN AT ANN ARBOR

    FOA Number: PA-18-369

    Abstract

    PROJECT NARRATIVE ?Precision medicine? and other advances in genetic research require access to massive amounts of genetic and related health data, but private genetic datasets are growing rapidly in both value and size and pose a challenge to the public genetic data market. This research proposes to characterize and evaluate the factors influencing these genetic data partnerships (beginning with academics), compare market drivers to current existing governance structures, and offer a model for best practices. Findings will inform current academic and governmental genetic data-sharing policy, as well as build a longitudinal analysis and conceptual model to stabilize this market moving forward.

    FUNDING AGENCY:

    Funder:
    NIH

    Institute:
    NATIONAL HUMAN GENOME RESEARCH INSTITUTE

    Funding Type:
    K01

    Project Number:
    K01HG010496

    Start Date:
    May 1, 2019

    End Date:
    Feb 28, 2024

    PROJECT TERMS:

    Agreement, Automobile Driving, base, career, career development, Clinical, clinical care, Communities, cost, court, Data, data access, Data Analyses, data repository, data resource, Data Set, data sharing, demographics, design, Development, Development Plans, Diagnosis, Ensure, ethical legal social implication, Ethicists, Ethics, Evaluation, experience, Failure, Federal Government, Foundations, Future, Genetic, Genetic Databases, Genetic Research, genetic testing, genomic data, Goals, Government, Grant, health data, Health Services, Human, improved, Incentives, Individual, Industry, instrument, Interview, Knowledge, Lawyers, Legal, Legal patent, longitudinal analysis, malignant breast neoplasm, Measures, Medical, meetings, Mentors, Mentorship, Methods, Modeling, Participant, Patient-Focused Outcomes, Patients, phenotypic data, Policies, precision medicine, Prevalence, Privatization, Questionnaire Designs, recruit, Regulation, Research, research and development, Research Design, Research Methodology, Research Personnel, Resources, Sampling, Science of genetics, Scientist, skills, Social Welfare, Source, Specimen, Structure, System, Testing, Training, Translations, Work

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