Precision Medicine Data Integration Core

核心B精准医疗数据集成 项目概要 风湿性疾病在表型、事件动力学和轨迹方面具有异质性，并且 对治疗的反应。定义相对同质的疾病亚组可以促进识别 具有共同潜在病理生理机制、并发症风险和 对不同治疗策略的反应——从而为发展奠定重要基础 风湿性疾病的精准医学方法。作为利用多种方法 亚组患者的临床和生物学特征可能会提高我们的预测能力 能力，利用允许聚合和协调的工具和技术至关重要 多个流数据。约翰霍普金斯大学医学院建立了一个大数据捕获系统， 聚合和协调。这个工具被称为精准医学分析平台， 捕获高质量的纵向数据，包括护理点更深入的表型数据， 来自诊断系统和医疗保健外部测量的精细结果 环境。在本提案中，我们寻求将这些工具和技术引入我们的风湿病学 狼疮、血管炎、类风湿关节炎、银屑病关节炎、硬皮病、 肌炎、干燥综合征、莱姆病和癌症免疫相关不良事件加速发生 风湿病研究。精准医疗数据整合的具体目标 核心是：1）促进和加速研究实施，同时确保严格的 研究伦理和数据安全实践； 2）转变数据收集方法以利用 机构“大数据”，提高效率并促进远程研究进展。核心由以下人员领导 研究项目建设、研究伦理和数据安全实践以及数据方面的专家 捕获和协调方法。

Core B Precision Medicine Data Integration PROJECT SUMMARY Rheumatic diseases are heterogeneous in phenotypes, kinetics of events and trajectory, and response to therapy. Defining relatively homogenous disease subgroups can foster identification of patients who share underlying pathophysiologic mechanisms, risks of complications and response to distinct therapeutic strategies – thereby laying a critical foundation for developing precision medicine approaches to the rheumatic diseases. As approaches that utilize multiple clinical and biologic characteristics to subgroup patients will likely improve our predictive capability, it is critical to harness tools and technologies that allow aggregation and harmonization of multiple streams data. Johns Hopkins Medicine has built a system for big data capture, aggregation and harmonization. This tool, known as the Precision Medicine Analytics Platform, captures high quality longitudinal data including deeper phenotypic data at the point of care, granular results from diagnostic systems and measurements from outside the health care environment. In this proposal, we seek to bring these tools and technologies to our rheumatology subspecialty centers in Lupus, Vasculitis, Rheumatoid Arthritis, Psoriatic Arthritis, Scleroderma, Myositis, Sjogren’s syndrome, Lyme, and Cancer Immune-Related Adverse Events to accelerate research in the rheumatic diseases. The Specific Aims of the Precision Medicine Data Integration Core are to: 1) facilitate and accelerate research study implementation, while ensuring stringent research ethics and data security practices; and 2) transform data collection methods to harness institutional “big data,” improve efficiency and enable remote study progress. The Core is led by experts in research program building, research ethics and data security practices, and data capture and harmonization methods.