Authors:
Sergio Paraiso-Medina
1
;
David Perez-Rey
1
;
Raúl Alonso-Calvo
1
;
Brecht Claerhout
2
;
Kristof de Schepper
2
;
Philippe Hennebert
3
;
Jérôme Lhaut
3
;
Jasper Van Leeuwen
4
and
Anca Bucur
4
Affiliations:
1
Facultad de Informática and Universidad Politécnica de Madrid, Spain
;
2
Custodix NV, Belgium
;
3
Institut Jules Bordet, Belgium
;
4
Phillips Research and Healthcare Information Management, Netherlands
Keyword(s):
Semantic Interoperability, Clinical Trials, SNOMED, HL7, INTEGRATE Project, Breast Cancer.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Clinical Problems and Applications
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Health Information Systems
;
Integration/Interoperability
;
Interoperability
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Semantic Interoperability
;
Sensor Networks
;
Simulation and Modeling
;
Software Agents and Internet Computing
;
Software and Architectures
;
Symbolic Systems
Abstract:
The introduction of –omic information within current clinical treatment is one of the main challenges to transfer the huge amount of genomic-based results. The number of potential translational clinical trials is therefore experiencing a dramatic increase, with the corresponding increment on patient variability. Such scenario requires a larger population to recruit a minimum set of patients that may involve multi-centric trials, with associated challenges on heterogeneous data integration. To ensure sustainability on clinical trial management, semantic interoperability is one of the main goals addressed by international initiatives such as the EU funded INTEGRATE project: “Driving Excellence in Integrative Cancer Research”. This paper describes the approach adopted within an international research initiative, providing a homogeneous platform to manage clinical information from patients on breast cancer clinical trials. Following the project “leitmotif” of reusing standards supported
by a large community, we have developed a solution providing a common data model (i.e. HL7 RIM-based), a biomedical domain vocabulary (i.e. SNOMED) as core dataset and resources from the semantic web community adapted for the biomedical domain. After one year and a half of collaboration, the INTEGRATE consortium has been able to develop a solution providing the reasoning capabilities required to solve clinical trial patient recruitment. The next challenge will be to extend the current solution to support a cohort selection tool allowing prospective analysis and predictive modeling.
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