Prediction of Adverse Drug Reactions due to Drug-Drug Interactions using Probability Analysis

Abstract

An adverse drug reaction (ADR) is an expression that describes harm associated with the use of given medications at a normal dosage during normal use. ADRs may occur following a single dose or prolonged administration of a drug or result from the combination of two or more drugs. The data on Adverse Drug Reactions are abundant, incomplete and consumes huge space to store. No quantitative conclusions can be drawn from the reported data in regard to mortality, or the underlying causes of ADRs. Hence two drugs namely vioxx and warfarin taken to show that different reactions are caused when the drug is taken in single and in combinations. Association rules are used to find the association between drug and adverse event. Here association rules are generated using probability analysis method .In this method the 2*2 contingency table is constructed for the drugs and the adverse event and the chi-square statistics is found out based on the goodness of fit. With the chi-square test, it is possible to determine only the relative strength of association, not to distinguish the interaction relationships between the drugs. For that Probabilistic model is constructed and based on that adverse event is found out whether due to single drug or drug in combination. Then patient’s demographic information such as gender, age are taken and drug route is also considered to find out if symptom due to drug and with these additional conditions. They are analyzed using ID3 algorithm.