Physiologically-based pharmacokinetic modeling of enantioselective hydroxychloroquine kinetics and impact of genetic polymorphisms

Hydroxychloroquine (HCQ) is a chiral drug used to treat malaria and inflammatory diseases, available as a racemic mixture of R– and S–HCQ. This work aimed to build physiologically-based pharmacokinetic (PBPK) models to predict the pharmacokinetics (PK) of R– and S–HCQ and assess the impact of major genetic polymorphisms on PK. Whole-body PBPK models accounting for first-order absorption, Rodgers and Rowland distribution method, and enzyme kinetics data were built for R– and S–HCQ. The models were verified by comparing predicted PK parameters with observed ones, with a mean error within the acceptable range (0.5–2 fold). Simulations covered CYP2D6 normal metabolizer (NM), poor metabolizer (PM), and ultra-rapid metabolizer (UM) phenotypes, as well as CYP2C8 NM and PM phenotypes. The results revealed a 1.1-fold increase in area under the curve blood concentration versus time (AUC) for CYP2D6 PM individuals and a 0.9-fold reduction for UM individuals compared to NM individuals. In addition, simulations with CYP2D6 and CYP2C8 PM phenotype individuals combined with the CYP3A4 inhibitor clarithromycin showed increased AUC for R– and S–HCQ of 2.34 and 2.68, respectively. These PBPK models offer reliable predictions for R– and S–HCQ enantioselective kinetics and shed light on previously unexplored scenarios.