Physiologically based pharmacokinetic (PBPK) modeling of gliclazide for different genotypes of CYP2C9 and CYP2C19.

Abstract

Gliclazide is a sulfonylurea hypoglycemic agent used to treat type 2 diabetes. Cytochrome P450 (CYP) 2C9 and CYP2C19 are primarily involved in the hepatic metabolism of gliclazide. The two CYP isozymes are highly polymorphic, and their genetic polymorphisms are known to significantly impact the pharmacokinetics of gliclazide. In the present study, the physiologically based pharmacokinetic (PBPK) model was developed using data from subjects whose pharmacokinetic parameters were influenced by the genetic polymorphisms of the CYP metabolic enzymes. All predicted plasma concentration-time profiles generated by the model showed visual agreement with the observed data, and the pharmacokinetic results were within the twofold error range. Individual simulation results showed additional metrics: average fold error (- 0.19 to 0.07), geometric mean fold error (1.13-1.56), and mean relative deviation (1.18-1.58) for AUC, C_max, T_1/2, T_max, CL/F, and V_d values. These results met the standard evaluation criteria. The validation across a total of 8 studies and 7 races also satisfied the twofold error range for AUC, C_max, and T_1/2. Therefore, variations in gliclazide exposure according to individuals' CYP2C9 and CYP2C19 genotypes were properly captured through PBPK modeling in this study. This PBPK model may allow us to predict the gliclazide pharmacokinetics of patients with genetic polymorphisms in CYP2C9 and CYPC19 under various conditions, ultimately contributing to the realization of individualized drug therapy.