Ontology based Drug-Drug Interaction Model

The rapidly increasing amount of data in pharmacy industry provides new opportunities and challenges for large scale data mining and Semantic Web. To meet challenges, various types of data about drugs, patients, diseases, adverse effects of drugs, drug-drug interaction and so on must be effectively integrated. Ontologies are used to retrieve and manipulate the data and display information in very precise and organized way. There do not exist a system that can identify the advanced drug-drug interaction automatically. In this research paper, we have proposed a system that can provide the advanced level drug-drug interaction. In this research, we have proposed an ontology-driven system that can provide the information about drugs, diseases, advanced drugdrug interaction (DDI), drug types, disease types, ingredient types, mechanism of action type, pharmokinetics type, physiologic effect type and dose form type. We have observed that pharmacist/doctors are also interested in administration methods, adverse effects, DDI mechanism, DDI types, drug reaction frequency, drug ingredient, drug interaction level, reaction duration and side effects. Most of above domain knowledge is missing in existing DDI ontologies. We have developed an ADDI ontology that can capture above mentioned advanced details for drug-drug interaction. SPARQL queries are posed to compute and extract the results. Our proposed ontology based system can facilitate the doctors and pharmacists to identify the adverse effects of different drugs interaction and help the patients as well.