Issue No. 01 - January/February (2006 vol. 21)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2006.2
Matthew Quinlan , Cerebra
Susie Stephens , Oracle
Alfredo Morales , Cerebra
Identifying signals of events that lead to undesirable outcomes is historically one of the most challenging aspects of determining drug safety, both during the drug discovery and development process and once a drug is released to the market. The information required to identify signals resides in disparate and distributed data repositories located in different functional groups and even separate organizations. The Semantic Web provides new capabilities for data integration that exploits explicit semantics and well-defined ontologies. These technologies promise to simplify heterogeneous data integration and allow logic to infer additional insights from the data. The Oracle RDF Data Model integrated with Cerebra Server is a composite solution that addresses the complexities of mediating information in drug safety. A use case illustrates the situation and how the composite solution might help.
Semantic Web, drug safety, RDF data model
Matthew Quinlan, Susie Stephens, Alfredo Morales, "Applying Semantic Web Technologies to Drug Safety Determination", IEEE Intelligent Systems, vol. 21, no. , pp. 82-86, January/February 2006, doi:10.1109/MIS.2006.2