Detecting DDI Using Ontology: Drug Mechanism of Action

Drug-drug interactions are generally harmful. This is usually manifested when the patient suffers from more than one disease for which drugs are prescribed and/or more than one drug is needed to be prescribed. The problem is made worse by the wide range of available drugs and the complexity which characterizes the variety of possible interactions or adverse effects. Determining potential drug-drug interactions (DDIs) is essential in any drug prescription. However, this process is not easy taking into consideration that medical and clinical data is continually increasing. Formal representation of the underlying knowledge is needed to provide comprehensive study of potential DDI. The ultimate aim of this work is to develop and use ontology for identifying DDI. DDI effects were classified into three types: toxic reaction, reduction effect or synergism effect. In this paper, the mechanism of action of drugs was considered to describe the proven general properties and action of drugs. Three scenarios were created to show the ability of description Logic (DL) reasoner of the proposed ontology to provide a proper classification of the DDI effects. In another words, describing the characteristics of any class will enable the DL reasoner to automatically recognize any individual that is an instance of this class. The study shows an efficient classification based on the defined ontology. The study relies on five dug families: Angiotensin-converting enzyme (ACE) inhibitors, Angiotensin II receptor blockers (ARBs), Beta blockers, Broad-spectrum penicillin's and Nonsteroidal anti-inflammatory drugs (NSAIDs).