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

遗传数据伙伴关系：在学术/私人数据共享协议中实现公平访问

• 批准号: 10341151
• 负责人: Kayte Kelleher Spector-Bagdady
• 金额: $ 17.5万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10341151
• 关键词: Agreement; Automobile Driving; Clinical; Communities; Data; Data Analyses; Data Set; Development; Development Plans; Diagnosis; Ensure; Ethicists; Ethics; Evaluation; Failure; Federal Government; Foundations; Future; Genetic; Genetic Databases; Genetic Research; Goals; Government; Grant; Health Services; Human; Incentives; Individual; Industry; Interview; Knowledge; Lawyers; Legal; Legal patent; Measures; Medical; Mentors; Mentorship; Methods; Modeling; Participant; Patient-Focused Outcomes; Patients; Policies; Prevalence; Privatization; Questionnaire Designs; Regulation; Research; Research Design; Research Methodology; Research Personnel; Resources; Sampling; Science of genetics; Scientist; Social Welfare; Source; Specimen; Structure; System; Testing; Training; Translations; Work; base; career; career development; clinical care; cost; court; data access; data repository; data resource; data sharing; demographics; design; ethical legal social implication; experience; genetic testing; genomic data; health data; improved; instrument; longitudinal analysis; malignant breast neoplasm; meetings; phenotypic data; precision medicine; recruit; research and development; skills

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 genetic data-sharing governance system to improve both research and clinical care for future patients.

项目总结/摘要 候选人：Kayte Spector-Bagdady，JD，MBE，是一名专注于治理的律师和医学伦理学家 利用人类标本和基因数据进行二次研究。她的长期职业目标是成为一名 独立调查员领导的发展，行为，和翻译的混合方法道德，法律的， 和社会影响研究，以改善遗传数据共享治理。研究背景： "精准医学"和遗传研究的其他进展为改善诊断和治疗提供了机会。 治疗数百万患者。他们还需要获得大量的遗传和相关的健康 数据联邦政府目前正在建立一个大型的、多样化的公共数据库，以实现这一工作， 但目前最大的基因数据集都是私人拥有的--而且规模和价值都在以一定的速度增长， 超越了公共对手。我们需要设计有效的基因数据治理结构， 调整激励和监管结构，以保护而不是扼杀基因数据共享。为此，我们 需要对推动基因数据伙伴关系（GDP）市场的因素进行经验评估，首先是 最大的消费者：学者。研究目的：本研究的总体目标是表征和 评估影响学术GDP的因素，将其与当前现有的治理结构进行比较， 为今后的最佳实践提供了一个模式。本研究的具体目标是：（1）描述私人- 通过探索研究人员目前使用的资源，激励或 不鼓励使用公共数据和私人数据，以及这些选择的后果; 2）开发和验证 衡量这些因素的工具，以确定它们在选择数据集时的重要性， 私人数据与公共数据的优缺点，以及国内生产总值协定的内容; 3）评估 现有的治理结构和驱动私人学术GDP市场的因素。研究计划：教授 Spector将使用定性、定量和混合方法分析。在这个项目结束时，她 将产生一系列影响私营-公共GDP市场的因素，开发和验证一个 工具来衡量这些因素，评估了这些因素的流行率和跨 学术遗传学研究人员，对目前私人学术GDP治理的差距进行了分析， 并制定了一套最佳实践建议。职业发展计划：Spector教授将发展 遗传科学的专门知识、问卷设计和抽样以及混合方法。她的训练将是 由经验丰富和跨学科的导师支持;先进的课程;和参与研究 和职业发展会议和研讨会在一个强大的社区科学家，临床医生和健康 服务研究人员。这个项目将使教授斯佩克特成为思想领袖，在建立一个公平的 遗传数据共享治理系统，以改善未来患者的研究和临床护理。