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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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... A Trial metadata repository contains protocol definitions ( Figure 1) and the SNAQL engine executes the DSL of the criteria to find patients belonging to the cohort. The SNAQL engine accesses the semantic integration services which provide a query interface [2] with reasoning abilities. Once a clinical protocol has been finalized, the tool is used to find patients eligible for enrollment. ...
... Our data model leverages the HL7-RIM and the HL7 implementation guidelines 6 . The underlying semantic solution is described in [5]. In [6] we estimated the effort required for implementing mappings to the patient information model, the scalability of our solution with the number of trials and its extensibility to other clinical domains. ...
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