Biomedical Data Translator Technical Feasibility Assessment and Architecture Design

卡罗莱纳生物医学数据翻译器(CBDT)将解决以下重大挑战 允许临床医生、护士、生物医学研究人员和 临床科学家查询、开发和贡献复杂和高度集中的 具有医学重要性的不同数据。这个数据联邦--一种“准全面”的医疗 联邦-将使审讯者能够提出关于人类健康和疾病的问题 在此之前是无法想象的。我们预计这些分析将在#年增加。 我们对新的治疗方法和治疗靶点的理解， 疾病和疾病传播的机制、环境诱因、药物机会 再利用、候选分子和系统生物学途径。 为了实现这一愿景，我们提出了一条允许实现这样一种 联邦政府。我们打算以适度的方式开始，并使用我们拥有的独特工具制作CBDT的原型 一直在为其他信息学项目构建，然后迭代地改进CBDT 与NCATS合作。最终，CBDT联盟将需要社会化， 被允许和培育，以实现其全部潜力。事实上，我们认为最大的 唯一的挑战将是建立一个治理模式，允许集合 从各个机构和组织中提取的信息。我们在小节中讨论这个问题 2.2.1. CBDT必须为： ·动态：定期更新，以适应新数据和数据源的增加； ·敏捷：可针对原始设计之外的用途进行修改，并可适用于其他数据分析； ·可用：允许不同的访问和访问级别(查看、编辑等)到数据，以及 允许受过适度培训的专家和新用户使用； ·理性：这些数据将在临床和科学上具有相关性，并受到政策的影响 和协议，系统将提供具有上下文元数据的答案；以及 ·有计划的：数据将有相关的来源和质量衡量标准，包括 适当时的统计相关性。 我们设想了一个支持数据摄取和后续操作的动态系统 管理、联邦和剥削(见图)。我们已经组建了一支 拥有跨学科协作和开发开放的记录的团队 源工具。我们提出了一个在两年内可行的示范项目 时间范围内，但演示了最终版本 系统必须具备。

The Carolina Biomedical Data Translator (CBDT) will address the significant challenges in clinical and translational research by permitting clinicians, nurses, biomedical researchers, and clinical scientists to query, exploit, and contribute to a federated collection of complex and highly disparate data with medical importance. This data federation—a “quasi-comprehensive” medical federation—will enable interrogators to pose questions about human health and disease that could not heretofore have been imagined. We anticipate that these analyses will increase, in ways that are paradigm shifting, our understanding of new treatments and treatment targets, mechanisms of disease and disease transmission, environmental triggers, opportunities for drug repurposing, molecular candidates, and systems biology pathways. To realize this vision, we propose a trajectory that permits the realization of such a federation. We intend to start modestly and prototype the CBDT using the unique tools we have been building for other informatics projects, and then iteratively improve the CBDT in collaboration with NCATS. Ultimately, the CBDT federation will need to be socialized, permitted, and nurtured in order to realize its full potential. Indeed, we believe that the biggest single challenge will be establishing a governance model that permits the assembly of information pulled from across institutions and organizations. We discuss this issue in Section 2.2.1. The CBDT must be: • Dynamic: regularly updated to accommodate the addition of new data and data sources; • Agile: modifiable for uses beyond the original design and adaptable for other data analysis; • Usable: permitting differential access and levels of access (view, edit, etc.) to the data, and permitting use by both experts and new users with modest training; • Rational: the data will be clinically and scientifically relevant, as well as informed by policy and protocols, and the system will provide answers with contextual meta-data; and • Curated: the data will have associated provenance and quality measures, including statistical relevance where appropriate. We envision a dynamic system that supports data ingestion and subsequent curation, federation, and exploitation (see figure). We have assembled a team that has a track record of interdisciplinary collaboration and development of open source tools. We propose a demonstration project that is feasible in the 2-year time frame, but demonstrates all of the key functionality that the final system must possess.