Robert H Dolin, Waddah Arafat, Bret S E Heale, Edna Shenvi, Srikar Chamala
{"title":"Molecularly-Guided Cancer Clinical Trial Matching using FHIR and HL7 Clinical Quality Language: A Proof of Concept.","authors":"Robert H Dolin, Waddah Arafat, Bret S E Heale, Edna Shenvi, Srikar Chamala","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p><b>Introduction</b>: Clinical trials play a crucial role in precision cancer care. Patients generally learn of trials from their physician, and physician recognition of potential matches can be enhanced through decision support tools. But automated trial matching remains challenging, particularly for molecular eligibility criteria. <b>Objective</b>: We assessed the feasibility of FHIR Genomics plus CQL to enable trial matching, particularly for molecular criteria. <b>Methods</b>: We developed a prototype that included (1) encoded trial criteria in CQL; (2) synthetic patient clinical and genomic data; (3) trial eligibility computation. <b>Results</b>: We found that even complex molecular eligibility criteria can be represented in CQL given that the semantics of a criterion are formalized in base FHIR specifications. The proof of concept \"CQL for Clinical Trials Matching\" is available at [https://elimu.io/downloads/]. <b>Discussion and Conclusions</b>: Proof of concept work suggests FHIR and CQL as viable options for enhancing clinical trial matching.</p>","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"359-367"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099354/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AMIA ... Annual Symposium proceedings. AMIA Symposium","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Clinical trials play a crucial role in precision cancer care. Patients generally learn of trials from their physician, and physician recognition of potential matches can be enhanced through decision support tools. But automated trial matching remains challenging, particularly for molecular eligibility criteria. Objective: We assessed the feasibility of FHIR Genomics plus CQL to enable trial matching, particularly for molecular criteria. Methods: We developed a prototype that included (1) encoded trial criteria in CQL; (2) synthetic patient clinical and genomic data; (3) trial eligibility computation. Results: We found that even complex molecular eligibility criteria can be represented in CQL given that the semantics of a criterion are formalized in base FHIR specifications. The proof of concept "CQL for Clinical Trials Matching" is available at [https://elimu.io/downloads/]. Discussion and Conclusions: Proof of concept work suggests FHIR and CQL as viable options for enhancing clinical trial matching.