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

> **NIH NIH K01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $174,971

## Abstract

PROJECT SUMMARY/ABSTRACT
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
genet...

## Key facts

- **NIH application ID:** 10112945
- **Project number:** 5K01HG010496-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Kayte Kelleher Spector-Bagdady
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $174,971
- **Award type:** 5
- **Project period:** 2019-05-01 → 2024-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10112945

## Citation

> US National Institutes of Health, RePORTER application 10112945, Genetic data partnerships: Enabling equitable access within academic/private data sharing agreements (5K01HG010496-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10112945. Licensed CC0.

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