Atorvastatin and amlodipine are commonly prescribed for the treatment of cardiovascular diseases, which often necessitate a polypharmacy approach due to long-term and combined medication use, thus increasing the potential for drug-drug interactions (DDIs). In this study, we developed physiologically-based pharmacokinetic (PBPK) models for atorvastatin and amlodipine, and simulated the potentials of DDIs using known strong index perpetrators of metabolic enzymes, including itraconazole, clarithromycin, and rifampicin. These PBPK models were developed using PK-Sim^® and a virtual Asian Population was developed based on Asian Individuals within PK-Sim^® without modification. Model validation was achieved by comparing simulated exposures to observed data, and all input parameters underwent local sensitivity analysis. We simulated the pharmacokinetic profiles of atorvastatin and amlodipine both with and without the presence of itraconazole, clarithromycin, and rifampicin, and investigated the geometric mean ratios (GMRs) of AUC_inf and C_max for each drug. The GMRs of AUC_inf for atorvastatin were 2.64, 2.37, and 0.43 with itraconazole, clarithromycin, and rifampicin, respectively; for amlodipine, the GMRs of AUC_inf were 2.06, 1.69, and 0.27, respectively. These results demonstrate that our models can be effectively used to explore further the potential DDIs of atorvastatin and amlodipine with various comedications.

Keywordsphysiologically-based pharmacokinetic modeling, atorvastatin, amlodipine, drug-drug interactions