RADx-Rad Discoveries & Data: Consortium Coordination Center Program Organization

RADx-Rad 发现

基本信息

批准号：
10745886
负责人：
Eliah S Aronoff-Spencer
金额：
$ 585.3万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-01-01 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10745886
关键词：
Agreement Antibodies Area Award Benchmarking Biological Assay COVID-19 COVID-19 diagnostic COVID-19 pandemic COVID-19 testing Calibration California Clinical Pathology Clinical Research Cloud Computing Cloud Service Collaborations Communicable Diseases Communication Communities Computer software Consultations Creativeness Data Data Collection Data Discovery Data Science Data Scientist Data Sources Development Diagnostic Diagnostic tests Ensure Evaluation FAIR principles FDA approved Funding Goals Gold Health Insurance Portability and Accountability Act Health Sciences Infection Informatics Knowledge Laboratories Logistics Metadata Methods Online Systems Persons Positioning Attribute Preparation Privacy Procedures Process Protocols documentation Quality Control RADx RADx Radical Reporting Research Personnel Resources Risk Role Sampling Science Secure Security Semantics Signal Transduction Specialist Specimen Standardization Structure Technology Terminology Testing Texas United States National Institutes of Health Universities Update Validation Viral Viral Load result Virus Visualization Work coronavirus disease dashboard data access data centers data exchange data management data modeling data reuse data sharing data standards design detection method diagnostic technologies distributed data expectation experience help-seeking behavior indexing innovation meetings member new technology news novel diagnostics programs quality assurance repository search engine syntax testing services tool transmission process usability user centered design user-friendly virology web-based tool

项目摘要

Preparing SARS-CoV-2 testing data for reuse requires making the data syntactically and semantically equivalent. Standardization of terminologies and a common data model accomplish the former, while the latter is accomplished through understanding the data and making it comparable across RADx-rad awardees by benchmarking against known gold standards. The standardization of samples is as important as standardizing the data, particularly in the highly innovative RADx-rad program, where new technologies will be developed or optimized for deployment in various settings. Highly motivated RADx-rad awardees will receive advice on how their diagnostics compare to FDA-approved ones, with each other, how their diagnostic performs in independent testing, as well as how to ensure the tests are usable in real world settings. In collaboration with University of Texas Health Science Center at Houston, University of California San Diego researchers in informatics/data science and infectious diseases with ample experience in leading large consortia have designed a unique RADx-rad Consortium Data and Coordination Center (radCDCC). This center is based on three pillars: (1) effective administration and coordination among awardees, NIH, and other programs;; (2) innovative approaches and tools to collect and standardize data and metadata to promote findability, accessibility, interoperability and reuse (FAIR) for data sharing;; and (3) principled preparation of standardized samples with known quantities of viral loads, and standardized procedures for testing new diagnostics to allow comparison across tests and calibration of new technologies. Backed by sophisticated HIPAA-compliant cloud services, user friendly web-tools, and extensive support from UCSD’s facilities for computation and for clinical research, the radCDCC will interface with other RADx programs and other COVID-19 focused programs at NIH to ensure alignment of awardees, NIH and the public in the pursuit of effective, affordable, and deployable new technologies for testing

准备SARS-COV-2测试数据以进行重复使用，需要以语法和语义等效进行数据。术语的标准化和通用数据模型实现了前者，而后者是通过理解数据并使其在RADX RAD获奖者中可比根据已知的黄金标准进行基准测试。样品的标准化与标准化一样重要数据，特别是在高度创新的RADX RAD计划中，将开发新技术或优化用于在各种设置中部署。高度积极进取的RADX-RAD获奖者将获得有关如何他们的诊断与FDA批准的诊断相比，彼此之间的诊断在独立中的诊断表现测试以及如何确保测试在现实世界中可用。与德克萨斯大学健康科学中心合作，加利福尼亚大学圣地亚哥分校的知识/数据科学和传染病研究人员在领先的大型财团方面具有丰富的经验，设计了一个独特的RADX RAD财团数据和协调中心（RADCDCC）。该中心基于三个支柱：（1）获奖者，NIH和其他计划之间的有效管理和协调；（2）创新方法和工具收集和标准化数据和元数据以促进可发现性，可访问性，互操作性和重复使用（公平）数据共享; （3）具有已知量病毒量的标准样品的主要制备负载和测试新诊断的标准化程序，以允许在测试和校准之间进行比较新技术。以精致的HIPAA兼容云服务，用户友好的网络工具和 UCSD的计算设施和临床研究的广泛支持，RADCDCC将接口 NIH与NIH的其他RADX计划和其他Covid-19以确保获奖者的一致性，NIH 公众追求有效，负担得起和可部署的新技术进行测试