Central Hub for Kidney Precision Medicine - Data Coordinating Center

肾脏精准医学中心中心 - 数据协调中心

• 批准号: 10002339
• 负责人: Robyn Leagh McClelland
• 金额: $ 69.45万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10002339
• 关键词: Acute Renal Failure with Renal Papillary Necrosis; Algorithms; Atlases; Biometry; Cells; Chronic Kidney Failure; Clinical; Clinical Research; Cohort Studies; Communication; Consult; Custom; Data; Data Analyses; Data Collection; Data Coordinating Center; Data Set; Databases; Ensure; Environment; Epidemiology; Ethics; Funding; Health; Informatics; Institutes; Kidney; Kidney Diseases; Knowledge; Leadership; Medical Education; Methodology; Michigan; Modeling; Monitor; Multicenter Studies; Names; Pathway interactions; Patients; Quality Control; Reporting; Research; Research Design; Research Institute; Research Personnel; Safety; Sample Size; Sampling; Science; Secure; Security; Site; Specimen; Standardization; Text; Time; Tissues; Training; Universities; Visualization software; Washington; Work; application programming interface; base; biomedical informatics; clinical care; data quality; data resource; data submission; data visualization; design; disorder subtype; electronic data; experience; informatics tool; innovation; interest; kidney biopsy; longitudinal analysis; multiple data sources; new therapeutic target; patient safety; precision medicine; protocol development; recruit; relational database; repository; research study; sample collection; sound; success; support tools; translational health science; transmission process; web interface; web services

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.

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应用程序的总体目标 为KPMP创造一个环境，以促进科学严谨性、患者安全和 成功的跨学科团队科学是在肾脏疾病方面取得重大进展所必需的 研究。为了实现这一目标，我们组建了一支在数据方面拥有专业知识的团队 协调中心管理、规划、生物统计、生物医学信息学和 流行病学，有超过25年的经验协调非常成功的大规模 纵向研究。KPMP中央枢纽的总体目标是创建 促进科学严谨、患者安全和成功的跨学科团队的环境 在肾脏疾病研究方面取得重大进展所必需的科学。这其中的一个关键组成部分 模式是KPMP数据和生物样本协调中心(DCC)，它将有主要的 负责规划、促进、监测和跟踪数据和样本收集 招聘网站。DCC必须在以下方面提供组织、统计和编程方面的专业知识 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 和标本追踪；(6)多来源数据的分析；(7)沟通便利。在……里面 为了实现这一目标，我们组建了一支在数据协调中心拥有专业知识的DCC团队 管理、规划、生物统计、生物医学信息学和流行病学，超过25名 多年协调非常成功的大型纵向研究的经验。 DCC将作为KPMP中央枢纽的核心组成部分，并将为数据提供接口 提交和样品跟踪。所有活动都将使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，该实例托管了3,000多个项目 用于定制电子数据捕获的可扩展且安全的计算环境。我们还将 利用我们在去识别临床数据集和使用我们的 非结构化文本标注的命名实体识别算法。数据将可用 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、应用程序接口(API)和关系数据库。我们将与 两个核心，以确保最高的数据质量和及时交付数据集，以便部署到 KPMP组织图谱和可视化工具。