Influence of the cytochrome P450 2B6 genotype on population pharmacokinetics of efavirenz in human immunodeficiency virus patients
- PMID: 19433561
- PMCID: PMC2704695
- DOI: 10.1128/AAC.01537-08
Influence of the cytochrome P450 2B6 genotype on population pharmacokinetics of efavirenz in human immunodeficiency virus patients
Abstract
A population pharmacokinetic model for efavirenz has been developed from therapeutic drug monitoring data in human immunodeficiency virus (HIV)-positive patients by using a nonlinear mixed-effect model. The efavirenz plasma concentrations (n = 375) of 131 patients were analyzed using high-performance liquid chromatography with UV detection. Pharmacokinetic parameters were estimated according to a one-compartment model. The effects of sex, age, total body weight, height, body mass index, and HIV treatment were analyzed. In a subgroup of 32 patients, genetic polymorphisms of the cytochrome P450 2B6 gene (CYP2B6), CYP3A4, and MDR1 were also investigated. Efavirenz oral clearance and the apparent volume of distribution were 9.50 liters/h and 311 liters, respectively. The model included only the effect of CYP2B6 polymorphisms on efavirenz clearance; this covariate reduced the intersubject variability of clearance by about 27%. Patients showing G/T and T/T CYP2B6 polymorphisms exhibited efavirenz clearances that were about 50% and 75% lower than those observed in the patients without these polymorphisms (G/G). Accordingly, to obtain EFV steady-state concentrations within the therapeutic range (1 to 4 mg/liter), it would be advisable to implement a gradual reduction in dose to 400 or 200 mg/day for patients that are intermediate or poor metabolizers, respectively. However, the remaining interindividual variability observed in the pharmacokinetic parameters of the model highlights the need for dose individualization to avoid inadequate exposure to efavirenz and suggests that these recommended doses be used with caution and confirmed by therapeutic drug monitoring and clinical efficacy. The population model can be implemented in pharmacokinetic clinical software for dosage optimization by using the Bayesian approach.
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