title: Semantic categories and relations for modelling adverse drug reactions towards a categorial structure for pharmacovigilance.
abstract: WHO-ART and MedDRA are the terminologies used in pharmacovigilance for coding of adverse drug reactions and statistical analysis. In previous work we showed that tools for automated signal detection and access to pharmacovigilance databases would benefit from terminological reasoning in order to provide improved groupings of terms describing the same medical condition. Such reasoning depends on formal definitions that are absent in both terminologies. A Categorial structure is defined as a minimal set of health care domain constraints which represents a biomedical terminology in a precise healthcare domain. Here we present a draft for a lite ontological model consisting in 19 semantic categories and 16 relations for the representation of adverse drug reactions. From this model we selected 8 semantic categories for the categorial structure. This study was restricted to WHO-ART and additional research is required in order to provide complete coverage of MedDRA.
authors.affiliation: University of Saint Etienne, Department of Public Health and Medical Informatics,St Etienne; INSERM UMR_S 872, Eq 20, Paris, France.
authors.forename: Cédric
authors.initials: C
authors.lastname: Bousquet
authors.forename: Béatrice
authors.initials: B
authors.lastname: Trombert
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Rodrigues
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D004014:Dictionaries as Topic; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification*; D005568:Forms and Records Control; D009323:Natural Language Processing; D012660:Semantics; D009626:Terminology as Topic; D014481:United States