Cloud-Based Biomedical Data Storage and Analysis: Implications for Trustworthy Governance

基于云的生物医学数据存储和分析：对可信治理的影响

• 批准号: 10320454
• 负责人: Stephanie Malia Fullerton
• 金额: $ 19.44万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-18 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10320454
• 关键词: All of Us Research Program; Biomedical Research; Clinical; Clinical Data; Collaborations; Communities; Cost utility; Data; Data Analyses; Data Storage and Retrieval; Data Store; Decision Making; Development; Ensure; Equilibrium; Feedback; Genomic Data Commons; Genomic medicine; Genomics; Goals; Health; Human; Individual; Informatics; Informed Consent; Interview; Investigation; Link; Logistics; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; Outcome; Participant; Phenotype; Policies; Policy Analysis; Procedures; Recommendation; Research; Research Personnel; Role; Sampling; Structure; Time; Trans-Omics for Precision Medicine; Visualization; base; catalyst; cloud based; computerized data processing; data access; data sharing; database of Genotypes and Phenotypes; design; genomics cloud; informant; interest; novel; novel strategies; phenotypic data; precision medicine; public trust; tool; translational genomics; trustworthiness

PROJECT SUMMARY The storage, sharing, and analysis of individual-level genomic, environmental, and linked phenotypic and/or health outcome data poses profound technical and logistical challenges for precision medicine research. Accordingly, new cloud-based computing and storage platforms are being developed to support facile data processing and cloud-based analysis commons. However, the implications for responsible data governance of these mechanisms are currently unexamined. To promote responsible and trustworthy data governance (i.e. decision-making about how biomedical data are stored, accessed, and used by researchers, as well as communicated to research participants), we will conduct an in-depth qualitative analysis of the policies, practices, and procedures associated with three emerging cloud-based precision medicine platforms: the BioData Catalyst or BDCatalyst (NHLBI), the Analysis, Visualization, and Informatics Lab-space or AnVIL (NHGRI), and the Research Hub (All of Us Research Program). The immediate goal of this exploratory investigation will be to examine how the control and management of genomic and linked clinical data stored on these platforms differs from earlier data sharing efforts. We will also explore what research stakeholders, including platform developers; investigators (data contributors as well as data users); institutional officials; and funders regard as the most relevant governance tradeoffs associated with the new approaches. In particular, we will solicit views on mechanisms employed to protect participant data, ensure that research uses are aligned with informed consent, and make well-validated results available to interested participants. Draft recommendations based in these observations will be shared with the research community and form the basis for subsequent research, which will introduce these new platforms and the research practices they enable to diverse research participants for feedback and critical reflection. To achieve these research objectives, we will pursue the following Aims: (1) Characterize current approaches to the storage, sharing, and analysis of largescale genomic and linked data enabled by emerging cloud-based analysis platforms; (2) Explore stakeholder views on current and proposed approaches to the governance of genomic cloud-based analysis platforms; and (3) Propose and vet recommendations for the trustworthy governance of genomic and linked environmental and phenotypic data in the context of cloud-based platforms. The proposed investigation will generate novel, timely, and detailed information about the storage, access, and intended use of large-scale genomic and linked clinical data held in emerging cloud-based data storage and analysis platforms. These data will provide a robust basis from which to identify best practices for trustworthy data governance and provide enhanced transparency about a key precision medicine research tool.

项目摘要 个体水平的基因组、环境和连锁表型和/或基因组的存储、共享和分析， 健康结果数据对精准医学研究提出了深刻的技术和后勤挑战。 因此，正在开发新的基于云的计算和存储平台，以支持简易数据 处理和基于云的分析的共同点。然而，负责任的数据治理的影响， 这些机制目前尚未得到审查。促进负责任和值得信赖的数据治理（即 关于研究人员如何存储、访问和使用生物医学数据的决策，以及 与研究参与者沟通），我们将对政策进行深入的定性分析， 与三个新兴的基于云的精准医学平台相关的实践和程序： 生物数据催化剂或BDCatalyst（NHLBI），分析，可视化和信息学实验室空间或AnVIL （NHGRI）和研究中心（我们所有的研究计划）。这次探索性的直接目标是 研究将检查如何控制和管理存储在 这些平台不同于早期的数据共享工作。我们还将探讨哪些研究利益相关者， 包括平台开发人员;调查人员（数据贡献者和数据使用者）;机构官员;以及 供资者认为与新方法相关的最相关的治理权衡。特别是，委员会认为， 我们将就保护参与者数据的机制征求意见，确保研究用途 与知情同意一致，并向感兴趣的参与者提供经过充分验证的结果。草案 基于这些观察的建议将与研究界分享，并形成基础 为后续研究，这将介绍这些新的平台和研究实践，他们使， 不同的研究参与者的反馈和批判性反思。为达致这些研究目标，我们会 追求以下目标：（1）描述当前存储，共享和分析的方法 通过新兴的基于云的分析平台实现大规模基因组和关联数据;（2）探索 利益相关者对基因组云分析治理的当前和拟议方法的看法 平台;以及（3）提出并审查基因组和相关基因的可靠治理建议 环境和表型数据在基于云的平台的背景下。拟议的调查将 生成有关大规模存储、访问和预期使用的新颖、及时和详细的信息， 在新兴的基于云的数据存储和分析平台中保存的基因组和相关临床数据。这些 数据将提供一个坚实的基础，从中确定值得信赖的数据治理的最佳做法， 提供有关一个关键的精准医学研究工具的更高透明度。

项目成果

Cloud-based biomedical data storage and analysis for genomic research: Landscape analysis of data governance in emerging NIH-supported platforms.

• DOI: 10.1016/j.xhgg.2023.100196
• 发表时间: 2023-07-13
• 期刊: HUMAN GENETICS AND GENOMICS ADVANCES
• 作者: Dahlquist, Jacklyn M.;Nelson, Sarah C.;Fullerton, Stephanie M.
• 通讯作者: Fullerton, Stephanie M.