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Reuse of EUCAIM Ontology for Prescreening Use Case
Morgan Vaterkowski1,2, Mirna El Ghosh1, Nadir Ammour2
1Sorbonne Université, INSERM, Université Sorbonne Paris-Nord, Laboratoire d'informatique médicale et d'ingénierie des connaissances en e-santé, LIMICS, 75006 Paris, France.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
Standardizing clinical trial eligibility criteria (EC) using an ontology-based data dictionary improves patient-trial matching. This approach enhances the computable data elements for prescreening, making it more efficient and scalable.
Area of Science:
- Medical Informatics
- Clinical Trial Management
- Ontology Engineering
Background:
- Manual processing of clinical trial eligibility criteria (EC) is time-consuming.
- Standardizing EC is crucial for efficient patient-trial matching using Electronic Health Records (EHR).
Purpose of the Study:
- To design an ontology-based data dictionary for standardizing EC.
- To support patient eligibility determination in clinical trials.
Main Methods:
- Decomposed free-text EC from 51 clinical trials into data elements for prescreening.
- Built the PENELOPE data dictionary and aligned it with the EUCAIM common data model and ontology.
- Enriched the PENELOPE dictionary with EUCAIM ontology concepts relevant for prescreening.
Main Results:
- Aligned 100 data elements, identifying direct, partial, and unique matches between PENELOPE and EUCAIM.
- Revised the PENELOPE data dictionary structure and enriched its semantic content.
- Demonstrated the scalability of the PENELOPE prescreening use case.
Conclusions:
- Ontology-based enrichment of the PENELOPE data dictionary standardizes prescreening-oriented EC.
- This standardization facilitates efficient and scalable patient eligibility determination in clinical trials.
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