Development and validation of a computable knowledge framework for genomic medicine

基因组医学可计算知识框架的开发和验证

• 批准号: 10293672
• 负责人: Alex Handler Wagner
• 金额: $ 42.06万
• 依托单位: RESEARCH INST NATIONWIDE CHILDREN'S HOSP
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-08 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10293672
• 关键词: Clinical; Collection; Consumption; Data; Data Sources; Decision Making; Development; Diagnosis; Discipline; Education; Evaluation; Genome; Genomic medicine; Genomics; Growth; Health; Individual; Intuition; Knowledge; Left; Literature; Malignant Neoplasms; Modernization; Patients; Privatization; Prognosis; Reporting; Research; Research Activity; Resources; Risk; Role; Services; Standardization; System; Therapeutic; Time; Validation; Variant; Work; clinical care; clinical decision support; clinically relevant; clinically significant; combinatorial; cost; data ecosystem; data harmonization; design; genetic variant; genomic data; improved; innovation; interoperability; knowledge base; novel; research clinical testing; support tools; tool; tool development

Project Summary/Abstract Genomic medicine is the discipline of interpreting genomic information about an individual as part of their clinical care, for diagnosis, prognosis, or therapeutic decision-making. Integral to the practice of genome interpretation is the collection of multiple lines of evidence from knowledgebases to support or refute the clinical significance of evaluated variants. Modern clinical variant knowledgebases maintain literature and variant coverage that is mostly non-overlapping. This diversity of content causes a known problem in genome interpretation: analysts tasked with assembling a clinical variant report choose to spend considerable time navigating multiple resources and collating evidence, or risk missing critical information by selectively evaluating fewer resources. The resulting effort needed for an analyst to clinically interpret a variant list is known as the interpretation bottleneck, for its rate-limiting role in the clinical evaluation of patient genomes. Data integrators from public and private genomic medicine organizations work to alleviate this bottleneck by developing integrative clinical interpretation applications for use by genome analysts. As new knowledgebases are created, each of these public and private data integrators is left with the task of designing and maintaining another interface for each new resource, leading to combinatorial growth of data harmonization effort across the entire system. This approach is not scalable. This project will enable a transition to a scalable, interoperable, and federated genomic data ecosystem from the data integrators and knowledgebases already in existence today. To build an interoperable network of knowledgebases will require development and validation of a computable knowledge framework for genomic medicine. The framework will require the drafting of modern genomic knowledge standards, and development of the tools and services needed to support the implementation of those standards. These objectives will be carried out through coordination of several research activities with the Variant Interpretation for Cancer Consortium, ClinGen, and the Global Alliance for Genomics and Health. Research will involve conceptualization of genomic knowledge as precise computable concepts, designing schema for those concepts, developing framework support tools, and building intuitive user applications to leverage these advances. As a result of this research, new knowledgebases implementing this framework become immediately accessible to existing applications, while new applications and workflows implementing this framework are immediately able to leverage a wide breadth of data sources. In addition to these immediate benefits, the creation of a standardized, federated knowledge network reduces barriers for developing new products, spurring innovation towards novel applications for research, education, and clinical decision support tools.

项目总结/文摘