Literature Based Drug Interaction Prediction with Clinical Assessment Using Electronic Medical Records: Novel Myopathy Associated Drug Interactions

Drug-drug interactions (DDIs) are a common cause of adverse drug events. In this paper, we combined a literature discovery approach with analysis of a large electronic medical record database method to predict and evaluate novel DDIs. We predicted an initial set of 13197 potential DDIs based on substrates and inhibitors of cytochrome P450 (CYP) metabolism enzymes identified from published in vitro pharmacology experiments. Using a clinical repository of over 800,000 patients, we narrowed this theoretical set of DDIs to 3670 drug pairs actually taken by patients. Finally, we sought to identify novel combinations that synergistically increased the risk of myopathy. Five pairs were identified with their p-values less than 1E-06: loratadine and simvastatin (relative risk or RR = 1.69); loratadine and alprazolam (RR = 1.86); loratadine and duloxetine (RR = 1.94); loratadine and ropinirole (RR = 3.21); and promethazine and tegaserod (RR = 3.00). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Based on additional literature data on in vitro drug metabolism and inhibition potency, loratadine and simvastatin and tegaserod and promethazine were predicted to have a strong DDI through the CYP3A4 and CYP2D6 enzymes, respectively. This new translational biomedical informatics approach supports not only detection of new clinically significant DDI signals, but also evaluation of their potential molecular mechanisms. Drug-drug interactions are a common cause of adverse drug events. In this paper, we developed an automated search algorithm which can predict new drug interactions based on published literature. Using a large electronic medical record database, we then analyzed the correlation between concurrent use of these potentially interacting drugs and the incidence of myopathy as an adverse drug event. Myopathy comprises a range of musculoskeletal conditions including muscle pain, weakness, and tissue breakdown (rhabdomyolysis). Our statistical analysis identified 5 drug interaction pairs: (loratadine, simvastatin), (loratadine, alprazolam), (loratadine, duloxetine), (loratadine, ropinirole), and (promethazine, tegaserod). When taken together, each drug pair showed a significantly increased risk of myopathy when compared to the expected additive myopathy risk from taking either of the drugs alone. Further investigation suggests that two major drug metabolism proteins, CYP2D6 and CYP3A4, are involved with these five drug pairs' interactions. Overall, our method is robust in that it can incorporate all published literature, all FDA approved drugs, and very large clinical datasets to generate predictions of clinically significant interactions. The interactions can then be further validated in future cell-based experiments and/or clinical studies.