Application of Population Pharmacokinetic Analysis to Characterize CYP2C19 Mediated Metabolic Mechanism of Voriconazole and Support Dose Optimization - Li, SiChan; Wu, SanLan; Gong, WeiJing; Cao, Peng; Chen, Xin; Liu, Wanyu; Xiang, Liping; Wang, Yang; Huang, JianGeng (Frontiers in Pharmacology, 2022)
Purpose: The aims of this study were to establish a joint population pharmacokinetic model for voriconazole and its N-oxide metabolite in immunocompromised patients, to determine the extent to which the CYP2C19 genetic polymorphisms influenced the pharmacokinetic parameters, and to evaluate and optimize the dosing regimens using a simulating approach. Methods: A population pharmacokinetic analysis was conducted using the Phoenix NLME software based on 427 plasma concentrations from 78 patients receiving multiple oral doses of voriconazole (200 mg twice daily). The final model was assessed by goodness of fit plots, non-parametric bootstrap method, and visual predictive check. Monte Carlo simulations were carried out to evaluate and optimize the dosing regimens. Results: A one-compartment model with first-order absorption and mixed linear and concentration-dependent-nonlinear elimination fitted well to concentration-time profile of voriconazole, while one-compartment model with first-order elimination well described the disposition of voriconazole N-oxide. Covariate analysis indicated that voriconazole pharmacokinetics was substantially influenced by the CYP2C19 genetic variations. Simulations showed that the recommended maintenance dose regimen would lead to subtherapeutic levels in patients with different CYP2C19 genotypes, and elevated daily doses of voriconazole might be required to attain the therapeutic range. Conclusions: The joint population pharmacokinetic model successfully characterized the pharmacokinetics of voriconazole and its N-oxide metabolite in immunocompromised patients. The proposed maintenance dose regimens could provide a rationale for dosage individualization to improve clinical outcomes and minimize drug-related toxicities.