Development of description framework of pharmacodynamics ontology and its application to possible drug-drug interaction reasoning.
Prediction of synergistic or antagonistic effects of drug-drug interaction (DDI) in vivo has been of considerable interest over the years. Formal representation of pharmacological knowledge such as ontology is indispensable for machine reasoning of possible DDIs. However, current pharmacology knowledge bases are not sufficient to provide formal representation of DDI information. With this background, this paper presents: (1) a description framework of pharmacodynamics ontology; and (2) a methodology to utilize pharmacodynamics ontology to detect different types of possible DDI pairs with supporting information such as underlying pharmacodynamics mechanisms. We also evaluated our methodology in the field of drugs related to noradrenaline signal transduction process and 11 different types of possible DDI pairs were detected. The main features of our methodology are the explanation capability of the reason for possible DDIs and the distinguishability of different types of DDIs. These features will not only be useful for providing supporting information to prescribers, but also for large-scale monitoring of drug safety.
Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, The University of Tokyo, Japan.
Takeshi
T
Imai
Masayo
M
Hayakawa
Kazuhiko
K
Ohe
D016907:Adverse Drug Reaction Reporting Systems; D001185:Artificial Intelligence; D064229:Biological Ontologies; D062313:Databases, Pharmaceutical; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions / Q000145:classification*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods; D010599:Pharmacokinetics