Identification of Factors Influencing the Pharmacokinetics of Voriconazole and the Optimization of D

来源 :第四届定量药理学与新药评价国际会议·2013(The 4th International Symposium in Qu | 被引量 : 0次 | 上传用户:jessicazrz
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  Objective: The objective of this study is to estimate the population pharmacokinetics of voriconazole, to identify the factors influencing voriconazole pharmacokinetics, and to identify optimal dosage regimens for attaining target pharmacokinetic/pharmacodynamics (PK/PD) indices against Aspergilhis and Candida infections in patients with invasive fungal infections (IFIs).Methods: To prospectively quantitate the relationships between the pharmacokinetics parameters of voriconazole and covariates, a population pharmacokinetics analysis was conducted on pooled data from 406 samples taken from 151 patients with IFIs.Voriconazole plasma concentrations were measured by high-performance liquid chromatography (HPLC).The following covariates were tested: demographic factors, laboratory data, concomitant medications, and CYP2C 19 genotype.Monte Carlo simulation was used to evaluate the effectiveness of the currently recommended dosage regimen and to design an optimized pharmacodynarnics 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 (Vd) was 200 L, and the oral bioavailability (F) was 89.5%.CL was significantly associated with age, with the serum concentration of alkaline phosphatase, and with the CYP2C19 genotype.Based on the results of the Monte Carlo stimulation, we concluded that Aspergillus infections could be treated effectively with 200 mg 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 pharmacokinetics analyses and Monte Carlo simulations.
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