Semantic Inference for Pharmacokinetic Drug-Drug Interactions

Semantic Computing(2014)

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摘要
Drug-drug interaction (DDI) study is an important aspect of therapy management and drug efficacy. DDI study investigates how drugs interact with each other and determine whether these interactions may lead to dire effects or nullify the therapeutic effects of each other. In this paper we model metabolic pathways of drugs that include the reaction effects between drugs and the related enzymes. By modeling the reaction effects, our model captures the degree of the effects of the interacting drugs. We introduce a novel methodology that combines semantics, ontology to model the concepts and interactions, and Answer Set Programming for temporal reasoning. We illustrate our method by inferring the effects of DDI among three drugs clozapine, olanzapine and fluvoxamine.
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关键词
drug delivery systems,drugs,inference mechanisms,logic programming,medical computing,ontologies (artificial intelligence),semantic networks,DDI,answer set programming,clozapine,drug efficacy,drug metabolic pathways,fluvoxamine,olanzapine,ontology,pharmacokinetic drug-drug interactions,reaction effects,semantic inference,temporal reasoning,therapeutic effect nullification,therapy management,Answer Set Programming,Drug-Drug Interactions,Ontology,Semantics,Temporal Reasoning
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