Towards Formal Computable Representation of Clinical Trial Eligibility Criteria for Alzheimer's Disease

Ambiguity and misunderstanding of free-text clinical trial eligibility can affect the accuracy of translating trial investigators' mental model of the study population to the correct cohort identification queries. In this pilot study, to eliminate the ambiguity when parsing eligibility criteria, we built ontology-based representations to standardize clinical trial eligibility criteria. We analyzed 10 Alzheimer's disease (AD) trials' eligibility criteria and categorized them into general query patterns using an annotation schema borrowed from the literature on constructing knowledge graphs. Then, for each pattern, we built the corresponding ontological representations, linked them to real-word electronic health record (EHR) data, and constructed cohort identification queries using the neo4j graph database. Our evaluation results of these cohort queries verified the accuracy of our ontology representation; and interestingly, we found that graph-queries achieved better runtime performance for complex study traits. These results indicated that our approach is feasible and potentially beneficial; nevertheless, more systematic and comprehensive investigations are warranted.