Date:

2025-04-30

Title of Paper:

Identification of factors influencing the pharmacokinetics of voriconazole and the optimization of dosage regimens based on Monte Carlo simulation in patients with invasive fungal infections

Journal:

Journal of antimicrobial chemotherapy

Summary:

Abstract
OBJECTIVES:
The objective of this study was to estimate the population pharmacokinetics of voriconazole, to identify the factors influencing voriconazole pharmacokinetics and to identify optimal dosage regimens for attaining target pharmacokinetic/pharmacodynamic indices against Aspergillus and Candida infections in patients with invasive fungal infections (IFIs).
METHODS:
To prospectively quantify the relationships between the pharmacokinetic parameters of voriconazole and covariates, a population pharmacokinetic analysis was conducted on pooled data from 406 samples taken from 151 patients with IFIs. Voriconazole plasma concentrations were measured by HPLC. The following covariates were tested: demographic factors, laboratory data, concomitant medications and CYP2C19 genotype. Monte Carlo simulation was used to evaluate the effectiveness of the currently recommended dosage regimen and to design an optimized pharmacodynamic dosage strategy for voriconazole.
RESULTS:
The data were appropriately fit by a one-compartment model with first-order absorption and elimination. The voriconazole clearance (CL) was 6.95 L/h, the volume of distribution (V) was 200 L and the oral bioavailability (F) was 89.5%. CL was significantly associated with age, the serum concentration of alkaline phosphatase and the CYP2C19 genotype. Based on the results of the Monte Carlo stimulation, we concluded that Aspergillus infections could be treated effectively with 200 mg of voriconazole administered intravenously or orally twice daily and that Candida infections could be treated with 300 mg administered orally twice daily or with 200 mg administered intravenously twice daily.
CONCLUSIONS:
This study showed that optimal voriconazole dosage regimens could be determined successfully with prospective population pharmacokinetic analyses and Monte Carlo simulations.
KEYWORDS:
Aspergillus; Candida; NONMEM; pharmacodynamics; population pharmacokinetics

Co-author:

Taotao Wang, Yalin Dong*

Translation or Not:

No

Date of Publication:

2014-02-01