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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

基本信息

批准号：
10555193
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
项目类别：
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/10555193
关键词：
Agreement Automobile Driving Calibration Clinical Communities Data Data Analyses Data Set Dedications Development Development Plans Diagnosis Ensure Equity Ethicists Ethics Evaluation Failure Federal Government Future Genetic Genetic Databases Genetic Research Goals Government Grant Health Services Human Incentives Individual Industry Institution Interview Lawyers Legal Legal patent Marketing 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 Specimen Structure System Testing Training Translations Work base career career development clinical care cost court data access data integration data repository data resource data sharing demographics design ethical, legal, and social implication experience genetic testing genomic data health data improved instrument knowledge commons longitudinal analysis malignant breast neoplasm meetings phenotypic data precision medicine recruit research and development skills

项目摘要

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.

项目概要/摘要候选人：Kayte Spector-Bagdady，法学博士，MBE，是一位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次研究使用。她的长期职业目标是成为一名独立调查员领导混合方法的开发、实施和翻译，符合道德、法律、以及改善遗传数据共享治理的社会影响研究。研究背景： “精准医学”和基因研究的其他进展为改善诊断和治疗提供了机会。为数百万患者提供治疗。他们还需要获得大量的遗传和相关健康信息数据。联邦政府目前正在建立一个大型、多样化的公共数据库来支持此类工作，但最大的遗传数据集目前为私人所有，并且其规模和价值正在以惊人的速度增长超越公共同行。我们需要设计有效的遗传数据治理结构，使我们能够调整激励和监管结构以保护（而不是扼杀）遗传数据共享。为此，我们需要对推动基因数据合作伙伴关系 (GDP) 市场的因素进行实证评估，首先从以下之一开始：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，以及提供未来最佳实践的模型。该研究的具体目标是： 1) 描述私人- 通过探索研究人员目前正在使用哪些资源、激励或促进学术 GDP 的因素阻止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以确定它们在选择数据集时的重要性的工具，感知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推动私人学术 GDP 市场的因素。研究计划：Prof. 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人-公共 GDP 市场的因素，开发并验证衡量这些因素的工具，评估这些因素的流行率以及各个方面的担忧学术遗传研究人员对当前私人学术 GDP 治理方面的差距进行了分析，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、问卷设计和抽样以及混合方法方面的专业知识。她的训练将是得到经验丰富的跨学科导师的支持；高级课程作业；和参与研究以及在由科学家、临床医生和健康界组成的强大社区内举办的职业发展会议和研讨会服务研究人员。该项目将使斯佩克特教授成为建立公平的教育体系的思想领袖。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。