Using Semantic Web Technologies for Clinical Trial Recruitment

Abstract

International audienceClinical trials are fundamental for medical science: they provide the evaluation for new treatments and new diagnostic approaches. One of the most difficult parts of clinical trials is the recruitment of patients: many trials fail due to lack of participants. Recruitment is done by matching the eligibility criteria of trials to patient conditions. This is usually done manually, but both the large number of active trials and the lack of time available for matching keep the recruitment ratio low. In this paper we present a method, entirely based on standard semantic web technologies and tool, that allows the automatic recruitment of a patient to the available clinical trials. We use a domain specific ontology to represent data from patients' health records and we use SWRL to verify the eligibility of patients to clinical trials

Towards the Automated Calculation of Clinical Quality Indicators

“…In the following, we describe two methods for clinical trial recruitment [1], [13] that are based on Semantic Web technologies. Similar to our approach, both methods employ a terminology.…”

“…In contrast to our approach, they rely on SWRL or description logic queries instead of SPARQL. Besana et al [1] showed that the automatic recruitment of patients who meet eligibility criteria of clinical trials is possible based on OWL and SWRL, the Semantic Web Rule Language 6 . They use the NCI ontology to represent both patient data and the eligibility criteria.…”

SemanticCT: A Semantically-Enabled System for Clinical Trials

“…Their approach is based on a SOA-oriented approach combined with the exploitation of ontologies which forms an "intelligence" layer for interpreting and analyzing existing data, which is dispersed, heterogeneous information, which is to a great extend publicly available. In [2] the authors present a method, entirely based on standard semantic web technologies and tool, that allows the automatic recruitment of a patient to the available clinical trials. They use a domain specific ontology to represent data from patients' health records and use SWRL to verify the eligibility of patients to clinical trials.…”

“…SemanticCT is built on the top of LarKC (Large Knowledge Collider), a platform for scalable semantic data processing 2 . With the built-in reasoning support for large-scale RDF/OWL data of LarKC, SemanticCT is able to provide various reasoning and data processing services for clinical trials, which include faster identification of eligible patients for recruitment service and efficient identification of eligible trials for patients.…”

Analysis of the Suitability of Existing Medical Ontologies for Building a Scalable Semantic Interoperability Solution Supporting Multi-site Collaboration in Oncology

“…In this paper we leverage the work in the INTEGRATE project and extend our semantic approach to other clinical domains such as lung cancer, sarcoma and nephroblastoma. In [7] the authors present a method that uses the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL) for automatic recruitment of a patient to available clinical trials. The aim of their work is to show how it is possible to represent eligibility criteria of clinical trials using SWRL on top of a large domain specific ontology: NCI thesaurus.…”