Candidate: Kayte Spector-Bagdady, JD, MBE, is an attorney and medical ethicist focused on the governance of secondary research use of human specimens and genetic data. Her long-term career goal is to become an independent investigator leading the development, conduct, and translation of mixed methods ethical, legal, and social implications research into improved genetic data-sharing governance. Research Context: ?Precision medicine? and other advances in genetic research offer opportunities to improve diagnosis and therapy for millions of patients. They also require access to massive amounts of genetic and related health data. The federal government is currently building a large, diverse, and public databank to enable such work, but the largest genetic datasets are currently privately owned?and growing in size and value at a rate outstripping public counterparts. We need to design effective genetic data governance structures to allow us to calibrate incentivization and regulation structures to protect?but not stifle?genetic data-sharing. To do so, we need empiric evaluation of the factors driving the genetic data partnership (GDP) market, beginning with one of the largest consumers: academics.
Research Aims : The overall goal of this research is to characterize and evaluate factors influencing academic GDPs, compare them to current existing governance structures, and offer a model for best practice going forward. The study's specific aims are to: 1) Characterize private- academic GDPs by exploring what resources researchers are currently using, factors that motivate or discourage the use of public vs. private data, and the consequences of those choices; 2) Develop and validate an instrument to measure these factors to determine their importance in selecting a dataset, perceived strengths/ weaknesses of private vs. public data, and content of GDP agreements; and 3) Assess gaps in existing governance structures and factors driving the private-academic GDP market. Research Plan: Prof. Spector will use qualitative, quantitative, and mixed methods analyses. At the conclusion of this project, she will have generated a set of factors influencing the private-public GDP market, developed and validated an instrument to measure these factors, assessed prevalence rates of these factors and concerns across academic genetic researchers, performed an analysis of current gaps in private-academic GDP governance, and developed a set of best practice proposals. Career Development Plan: Prof. Spector will develop expertise in genetic science, questionnaire design and sampling, and mixed methods. Her training will be supported by experienced and interdisciplinary mentors; advanced coursework; and participation in research and career development meetings and seminars within a robust community of scientist, clinicians, and health service researchers. This project will enable Prof. Spector to become a thought leader in building an equitable genetic data-sharing governance system to improve both research and clinical care for future patients.

Public Health Relevance

?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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01HG010496-02
Application #
9916795
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lockhart, Nicole C
Project Start
2019-05-01
Project End
2024-02-28
Budget Start
2020-03-01
Budget End
2021-02-28
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Obstetrics & Gynecology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109