Drug-drug interactions: A Data Mining Approach

Drug–drug interaction is one of the important problems of Adverse Drug Reaction (ADR). This presentation describes a data mining approach to this problem developed at the University of Ballarat. This approach is based on drug–reaction relationships represented in the form of a vector of weights; each vector related to a particular drug can be considered as a pattern in causing adverse drug reactions. Optimal patterns for drugs are determined as a solution to some global optimization problem. Although this approach can be used for solving many ADR problems, we concentrate only on drug–drug interactions. The numerical implementations are carried out on different classes of reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database. The results obtained extend our understanding of the drug–drug interaction from a data mining point of view. Copyright c ©2011, Australian Computer Society, Inc. This paper appeared at the 9th Australasian Data Mining Conference (AusDM 2011), Ballarat, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 121, Peter Vamplew, Andrew Stranieri, Kok–Leong Ong, Peter Christen and Paul Kennedy, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included. Proceedings of the 9-th Australasian Data Mining Conference (AusDM'11), Ballarat, Australia