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: 10112945
• 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/10112945
• 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.

项目摘要/摘要 候选人：Kayte Spector-Bagdady，JD，MBE，是专注于治理的律师和医学伦理学家 人类标本和遗传数据的二级研究使用。她的长期职业目标是成为一个 独立研究者领导混合方法的发展，行为和翻译道德，法律，法律， 以及对改善遗传数据共享治理的社会影响。研究背景： “精确医学”和遗传研究的其他进步为改善诊断和 数百万患者的治疗。他们还需要获得大量遗传和相关健康 数据。联邦政府目前正在建立一个大型，潜水和公共数据库，以实现此类工作， 但是最大的遗传数据集目前是私人所有的，并以速度增长的尺寸和价值 超越公共对方。我们需要设计有效的遗传数据治理结构，以使我们能够 校准激励和调节结构，以保护（但不扼杀）基因数据共享。为此，我们 需要经验评估推动遗传数据伙伴关系（GDP）市场的因素，从一个开始 最大的消费者：学者。研究目的：这项研究的总体目标是表征和 评估因素影响学术GDP，将其与当前现有治理结构进行比较，并 为未来的最佳实践提供模型。该研究的具体目的是：1）表征私人 - 通过探索研究人员当前正在使用的资源，动机或 阻止使用公共数据与私人数据的使用以及这些选择的后果； 2）发展和验证 一种衡量这些因素的工具，以确定它们在选择数据集中的重要性 私人数据与公共数据的优势/劣势以及GDP协议的内容； 3）评估差距 现有的治理结构和因素推动了私人学术GDP市场。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 将产生一系列因素，影响私人公共GDP市场，开发和验证 衡量这些因素的工具，评估这些因素的患病率以及各个方面的关注 学术遗传研究人员对私立学校GDP治理的当前差距进行了分析， 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，问卷设计和抽样以及混合方法方面的专业知识。她的训练将是 在经验丰富和跨学科的导师的支持下；高级课程工作；并参与研究 以及一个科学家，临床医生和健康社区中的职业发展会议和半少数 服务研究人员。该项目将使Spector教授成为建立公平的思想领导者 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。