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: 10218146
• 负责人: Robyn Leagh McClelland
• 金额: $ 85.31万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2022-09-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10218146
• 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.

抽象的 有帮助定义CKD和AKI疾病亚组并识别关键细胞的迫切需要 新疗法的途径和靶标。此中央集线器应用的总体目标 毕马威（KPMP）是创造一个环境，以促进科学严谨，患者安全和 成功的跨学科团队科学必不可少的导致肾脏疾病的重大进展 研究。为了实现这一目标，我们组建了一个具有数据专业知识的团队 协调中心管理，编程，生物统计学，生物医学信息学和 流行病学，拥有超过25年的经验，可以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 导致肾脏疾病研究的重大进展所必需的科学。一个关键组成部分 模型是KPMP数据和生物样品协调中心（DCC），它将具有主要 在计划，促进，监视和跟踪数据和标本收集的责任 招聘站点。 DCC必须提供组织，统计和编程专业知识 多中心研究包括但不限于：（1）研究设计和协议开发； （2） 研究实施和执行； （3）数据和样品传输； （4）质量控制； （5）数据 和标本跟踪； （6）分析来自多个来源的数据； （7）沟通便利。在 为了实现这一目标，我们已经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 多年的经验协调了非常成功的大规模纵向研究。 DCC将充当KPMP中央集线器的核心组成部分，并将为数据提供接口 提交和样本跟踪。所有活动都将利用我们支持并管理的信息学工具 各种各样的挑战包括我们的UW REDCAP实例，该实例托管了3,000多个项目 定制电子数据捕获的可扩展且安全的计算环境。我们也会 利用我们在临床数据集取消识别的深刻经验和能力 非结构化文本注释的命名实体识别算法。数据将可用 通过自助服务网络到数据可视化核心（DVC）和管理核心（AC） 接口，应用程序界面（API）和关系数据库。我们将与 两种核心，以确保数据质量最高和及时交付数据集以部署到 KPMP组织地图集和可视化工具。