Central Hub for Kidney Precision Medicine - Data Coordinating Center

摘要 迫切需要帮助定义CKD和AKI疾病亚组并识别关键细胞， 新疗法的途径和靶点。此Central Hub应用程序的首要目标是 KPMP的目标是创造一个促进科学严谨性、患者安全和 成功的跨学科团队科学是导致肾脏疾病重大进展所必需的 research.为了实现这一目标，我们组建了一个拥有数据专业知识的团队 协调中心管理、规划、生物统计学、生物医学信息学，以及 流行病学，拥有超过25年的经验，协调非常成功的大规模 纵向研究。KPMP中心枢纽的首要目标是创建 一个促进科学严谨性，患者安全和成功的跨学科团队的环境 科学必要的结果在肾脏疾病研究的重大进展。其中一个关键组成部分是 模型是KPMP数据和生物样本协调中心（DCC），该中心将主要负责 负责规划、促进、监测和跟踪数据和标本采集 招聘网站。DCC必须在以下方面提供组织、统计和方案编制方面的专门知识： 多中心研究，包括但不限于：（1）研究设计和方案制定;（2） 研究实施和执行;（3）数据和样本传输;（4）质量控制;（5）数据 和标本跟踪;（6）分析多个来源的数据;（7）促进沟通。在 为了实现这一目标，我们组建了一个具有数据协调中心专业知识的DCC团队 管理，编程，生物统计学，生物医学信息学和流行病学，超过25 多年的经验，协调非常成功的大型纵向研究。 数据通信中心将作为KPMP中央枢纽的核心组成部分，并将提供数据接口 提交和样品跟踪。所有活动都将利用我们支持和管理的信息学工具。 一系列挑战，包括我们的UW REDCap实例，该实例在 一个可扩展和安全的计算环境，用于自定义电子数据采集。我们还将 利用我们在临床数据集去识别化方面的丰富经验和能力， 非结构化文本标注的命名实体识别算法。将提供数据 通过自助服务网络连接到数据可视化核心（DVC）和管理核心（AC） 接口、应用程序编程接口（API）和关系数据库。我们将与 这两个核心，以确保最高的数据质量和及时交付数据集， KPMP组织图谱和可视化工具。

ABSTRACT There is a critical need to help define CKD and AKI disease subgroups and identify critical cells, pathways and targets for novel therapies. The overarching objective of this Central Hub application for the KPMP is to create an environment to promote scientific rigor, patient safety, and the successful interdisciplinary team science necessary to result in major advances in kidney disease research. In order to accomplish this, we have assembled a team with expertise in data coordinating center management, programming, biostatistics, biomedical informatics, and epidemiology, with over 25 years of experience coordinating highly successful large-scale longitudinal research studies. The overarching objective of the Central Hub of the KPMP is to create an environment to promote scientific rigor, patient safety, and the successful interdisciplinary team science necessary to result in major advances in kidney disease research. A key component of this model is the KPMP Data and biosample Coordinating Center (DCC), which will have primary responsibility for planning, facilitating, monitoring, and tracking data and specimen collection at the recruitment sites. The DCC must provide organizational, statistical, and programming expertise in multi-center studies including, but not limited to: (1) study design and protocol development; (2) study implementation and execution; (3) data and sample transmission; (4) quality control; (5) data and specimen tracking; (6) analysis of data from multiple sources; (7) communication facilitation. In order to accomplish this, we have assembled a DCC team with expertise in data coordinating center management, programming, biostatistics, biomedical informatics, and epidemiology, with over 25 years of experience coordinating highly successful large-scale longitudinal research studies. The DCC will act as a core component of the KPMP Central Hub and will provide interfaces for data submission and sample tracking. All activities will utilize informatics tools we support and govern for a wide array of challenges, include our UW REDCap instance that hosts more than 3,000 projects in a scalable and secure computing environment for custom electronic data capture. We will also leverage our deep experience and capacity in de-identification of clinical datasets and our use of named-entity recognition algorithms for annotation of unstructured text. Data will be made available to the Data Visualization Core (DVC) and the Administrative Core (AC) through self-service web interfaces, application program interfaces (APIs) and relational databases. We will work closely with both cores to ensure the highest data quality and timely delivery of datasets for deployment into the KPMP Tissue Atlas and visualization tools.