Enabling semantic interoperability in multi-centric clinical trials on breast cancer.

Background And Objectives: Post-genomic clinical trials require the participation of multiple institutions, and collecting data from several hospitals, laboratories and research facilities. This paper presents a standard-based solution to provide a uniform access endpoint to patient data involved in current clinical research.

Methods: The proposed approach exploits well-established standards such as HL7 v3 or SPARQL and medical vocabularies such as SNOMED CT, LOINC and HGNC. A novel mechanism to exploit semantic normalization among HL7-based data models and biomedical ontologies has been created by using Semantic Web technologies.

Results: Different types of queries have been used for testing the semantic interoperability solution described in this paper. The execution times obtained in the tests enable the development of end user tools within a framework that requires efficient retrieval of integrated data.

Conclusions: The proposed approach has been successfully tested by applications within the INTEGRATE and EURECA EU projects. These applications have been deployed and tested for: (i) patient screening, (ii) trial recruitment, and (iii) retrospective analysis; exploiting semantically interoperable access to clinical patient data from heterogeneous data sources.