Kelsey R Mayo, Melissa A Basford, Robert J Carroll, Moira Dillon, Heather Fullen, Jesse Leung, Hiral Master, Shimon Rura, Lina Sulieman, Nan Kennedy, Eric Banks, David Bernick, Asmita Gauchan, Lee Lichtenstein, Brandy M Mapes, Kayla Marginean, Steve L Nyemba, Andrea Ramirez, Charissa Rotundo, Keri Wolfe, Weiyi Xia, Romuladus E Azuine, Robert M Cronin, Joshua C Denny, Abel Kho, Christopher Lunt, Bradley Malin, Karthik Natarajan, Consuelo H Wilkins, Hua Xu, George Hripcsak, Dan M Roden, Anthony A Philippakis, David Glazer, Paul A Harris
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引用次数: 0
摘要
我们所有人研究计划的数据和研究中心(DRC)成立的目的是帮助获取、策划和访问世界上最大、最多样化的精准医学研究数据集之一。已经有超过50万名参与者参加了All of Us,其中80%在生物医学研究中的代表性不足,2300多名研究人员正在分析数据。DRC通过与参与者、创新项目合作伙伴和有能力的研究人员合作,创建了这个蓬勃发展的数据生态系统。在这篇综述中,我们首先描述了刚果民主共和国是如何组织起来以满足这一广泛利益相关者群体的需求的。然后,我们概述了用于构建All of Us数据生态系统的指导原则、共同挑战和创新方法。最后,我们分享经验教训,帮助其他人在构建现代生物医学数据平台时做出重要决策和权衡。
The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research.
The All of Us Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in All of Us, 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers. In this review, we first describe how the DRC is organized to meet the needs of this broad group of stakeholders. We then outline guiding principles, common challenges, and innovative approaches used to build the All of Us data ecosystem. Finally, we share lessons learned to help others navigate important decisions and trade-offs in building a modern biomedical data platform.
期刊介绍:
The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.