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

RADx-Rad 发现

基本信息

批准号：
10321007
负责人：
Eliah S Aronoff-Spencer
金额：
$ 584.89万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-12-21 至 2022-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10321007
关键词：
Agreement Antibodies Area Award Back 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 Data Data Collection Data Coordinating Center 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 Informatics Internet 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 SARS-CoV-2 infection Sampling Science Secure Security Semantics Signal Transduction Specialist Specimen Standardization Structure Technology Terminology Testing Texas Time United States National Institutes of Health Universities Update Validation Viral Viral Load result Virus Work base dashboard data access data centers data exchange data management data modeling data reuse data sharing data standards design 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 user centered design user-friendly virology

项目摘要

ABSTRACT 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.

文摘