Ontology-Driven Hypothetic Assertion (OHA) for Drug InteractionPrediction

Abstract

In accordance with the increasing amount of information concerning individual differences in drug response and molecular interaction, the role of in silico prediction of drug interaction on a pathway level is becoming more and more important. However, in view of the interferences for the identification of new drug interactions, most conventional information models of a biological pathway would have limitations. As a reflection of real world biological events triggered by a stimulus, it is important to facilitate the incorporation of known molecular events for inferring (unknown) possible pathways and hypothetic drug interactions. Method: On-stimulus dynamic pathway generation has been adopted to evade dealing with redundant static pathways in exponential numbers. Potential drug-drug interactions are detected from drug metabolic pathways dynamically generated by molecular events triggered after the administration of certain drugs. New hypothetic assertions of potential drug interactions are deduced from the Drug Interaction Ontology (DIO) written in Web Ontology Language (OWL). Results and Conclusion: The concept of Ontology- Driven Hypothetic Assertion (OHA) was demonstrated with known interactions between irinotecan (CPT-11) and ketoconazole. The system automatically detected four drug- drug interactions that involved cytochrome p450 (CYP3A4) and albumin as potential drug interaction genes. Future plans regarding in silico prediction of individual differences in the response to the drug and drug-drug interactions after the administration of multiple drugs are also discussed. Keyword: Biomedical Ontology, Drug Interaction, Metabolic Pathway, Web Ontology Language (OWL), Pharmacokinetics