Modeling, building and evaluating an ontology for the automatic characterization of adverse drug effects during pharmacovigilance.
BACKGROUND
The characterization of spontaneous reported cases is fundamental for pharmacovigilance. This task is time consuming and its reproducibility is low.


OBJECTIVE
To develop a system founded on an ontology that automatically instantiates spontaneous reported cases as "known" adverse drug effects (ADE) only if the reported ADEs are described in drug compendia.


METHODS
A simple ontology of drugs and their related adverse effects represented in description logics was developed from a drug database. Manual evaluation was carried out on 378 spontaneous reported cases instantiated as "known ADE of a chemical class". The initial manual characterization was reviewed by a pharmacovigilance expert to validate the generated automatic characterization.


RESULTS
The ontology is composed by 57,04 concepts and 5 relations. It was successfully validated thanks to Pellet reasoner and it contains neither inconsistencies nor cycles. In this validation, 86% of the instantiated spontaneous reported cases effectively concerned notorious ADEs, whereas only 75% were initially identified manually as related to notorious ADEs.


CONCLUSIONS
This system can assist characterization by applying a reasoning process similar to that used by experts in the search for ADEs.
Duclos
Catherine
C
Laboratoire d'Informatique Médicale et Bioinformatique, Université Paris 13, Bobigny, France. catherine.duclos@avc.aphp.fr
Soualmia
Lina F
LF
Krivine
Sonia
S
Jamet
Anne
A
Lillo-Louët
Agnes
A
D016907:Adverse Drug Reaction Reporting Systems; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000139:chemically induced; D006801:Humans