4.3 Article

Influence of CYP2B6 516G>T polymorphism and interoccasion variability (IOV) on the population pharmacokinetics of efavirenz in HIV-infected South African children

Journal

EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY
Volume 68, Issue 4, Pages 339-347

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00228-011-1148-7

Keywords

Efavirenz; Clearance; CYP2B6 516G > T; NONMEM

Funding

  1. North-West University
  2. National Research Foundation (NRF)
  3. Medical Research Council (MRC)
  4. [5U2RTW007370]
  5. [5U2RTW007373]

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To investigate the influence of CYP2B6 516G > T polymorphism, as a covariate, and of interoccasion variability (IOV) on the oral clearance (CL/F) of efavirenz (EFV) in treatment-na < ve black South African children over a period of 24 months post-antiretroviral therapy (ART) initiation. HIV-infected black children (n = 60, aged 3-16 years), with no prior exposure to ART, eligible to commence ART and attending an outpatient clinic were enrolled into this study. Blood samples were taken at mid-dose interval at 1, 3, 6, 12, 18 and 24 months post-ART initiation. EFV plasma samples were determined with an adapted and validated LC/MS/MS method. Genotyping of the CYP2B6 G516T single nucleotide polymorphism (SNP) was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). NONMEM was used for the population pharmacokinetic modelling. EFV concentrations below 1 mu g/mL accounted for 18% (116/649), EFV concentrations > 4 mu g/mL accounted for 29.5% (192/649) and concentrations within the therapeutic range (1-4 mu g/mL) represented 52.5% (341/649) of all the samples determined. The covariates age, weight and CYP2B6 G516Tgenotype were included in the final model with population estimates for CL/F determined as 2.46, 4.60 and 7.33 L/h for the T/T, G/T and G/G genotype groups respectively. The inclusion of both age and weight to predict accurate EFV CL values for the respective genotype groups within this paediatric population was required, whereas the addition of gender and body surface area did not improve the predictions. The importance of introducing IOV in a PK model for a longitudinal study with sparsely collected data was again highlighted by this investigation.

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