Objective To evaluate the population pharmacokinetics of voriconazole (VRC) and identify the factors affecting it in Chinese patients with Talaromyces marneffei infection. Based on the final model, the optimal dosing regimen was further investigated in these patients. Methods Patients with talaromycosis from two hospitals who met the inclusion criteria were enrolled. Patients’ demographic information, VRC medication history, concomitant medications and laboratory test information data were recorded. A population pharmacokinetic model was developed through from the nonlinear mixed-effects models (NONMEM). Monte Carlo Simulation was applied to optimize the initial dosing regimens. Results A total of 146 blood samples taken from 46 patients with talaromycosis were included in the study. A one-compartment model was used to characterize VRC pharmacokinetics. Population estimates of clearance (CL) and volume of distribution (V) were 2.19 L/h and 88.4L, respectively. VRC clearance was significantly associated with C-reactive protein (CRP) level, which causing individual pharmacokinetics variation. CYP2C19 polymorphisms had no effect on voriconazole pharmacokinetic parameters. Based on the dosing simulations with CRP level, the initial dosing regimens was recommended are as follows: loading dose 150mg q12h 1day followed by maintenance dose 100mg q12h intravenous for CRP< 40mg/L, and loading dose 75mg q12h followed by maintenance dose 50mg q12h intravenous for CRP ≥ 40mg/L. Conclusion A population pharmacokinetic model of VRC was successfully established in patients with Talaromyces marneffei infection. CRP was identified to significantly affect VRC plasma concentration. Optimizing initial dosing regimens according to the CRP level may be useful to guide VRC dosing in clinical practice.

Aim: This prospective study aims to investigate the factors influencing voriconazole trough concentration (Cmin), develop a population pharmacokinetics (PPK) model and recommend an appropriate voriconazole dosing regimen for children with hematological malignancies. Methods: Prospectively enrolled a total of 70 children aged <18 years and 149 samples. The factors influencing voriconazole Cmin were analyzed by univariate analysis and multiple linear regression analysis. Nonlinear mixed effects modeling (NONMEM) was applied to establish the PPK model. Dosage simulation based on albumin (ALB) levels and CYP2C19 genotype. Results: Multiple linear regression results demonstrated that route of administration, ALB and concomitant administration with glucocorticoid (GLU) and proton pump inhibitors (PPIs) were significant factors of voriconazole Cmin. A one-compartment model could best describe the pharmacokinetics of voriconazole. The extensive metabolizers (EM), ALB were significant covariates of clearance (CL). The typical value of CL, the volume of distribution (V) and oral bioavailability (F) were 1.52 L/h, 35.7 L and 0.909, respectively. The recommended dosing regimens for EM patients with ALB level of 20.0~35.0 g/L, 35.1~45.0 g/L and 45.1~55.0 g/L were4, 8 and 12 mg/kg intravenously or orally twice daily, respectively, and were 2, 4 and 7 mg/kg by intravenous or oral administration twice daily for non-EM. Conclusion: We found that route of administration, ALB and co-administration of GLU and PPI had quantitative relationships with voriconazole Cmin. The combination of CYP2C19 genotype and ALB levels to determine the initial dosing regimen of voriconazole could provide a reference for individualized treatment in children with hematological malignancies.