title: ADEpedia: a scalable and standardized knowledge base of Adverse Drug Events using semantic web technology.
abstract: A source of semantically coded Adverse Drug Event (ADE) data can be useful for identifying common phenotypes related to ADEs. We proposed a comprehensive framework for building a standardized ADE knowledge base (called ADEpedia) through combining ontology-based approach with semantic web technology. The framework comprises four primary modules: 1) an XML2RDF transformation module; 2) a data normalization module based on NCBO Open Biomedical Annotator; 3) a RDF store based persistence module; and 4) a front-end module based on a Semantic Wiki for the review and curation. A prototype is successfully implemented to demonstrate the capability of the system to integrate multiple drug data and ontology resources and open web services for the ADE data standardization. A preliminary evaluation is performed to demonstrate the usefulness of the system, including the performance of the NCBO annotator. In conclusion, the semantic web technology provides a highly scalable framework for ADE data source integration and standard query service.
authors.affiliation: Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street, SW, Rochester, MN, USA.
authors.forename: Guoqian
authors.initials: G
authors.lastname: Jiang
authors.forename: Harold R
authors.initials: HR
authors.lastname: Solbrig
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Chute
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D000465:Algorithms; D064420:Drug-Related Side Effects and Adverse Reactions; D057208:Health Level Seven; D020407:Internet; D051188:Knowledge Bases; D012660:Semantics; D018875:Vocabulary, Controlled