A novle polymorphism in ABCB1 gene, CYP2B6*6 and sex predict single dose efavirenz population pharmacokinetics in Ugandans
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Date
2009Author
Mukonzo, Jackson K
Röshammar, Daniel
Waako, Paul
Andersson, Maria
Fukasawa, Takashi
Milani, Lili
Svensson, Jan Olof
Ogwal-Okeng, Jasper
Gustafsson, Lars L.
Aklillu, Eleni
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AIMS Efavirenz exhibits pharmacokinetic variability causing varied clinical response. The aim was to develop an integrated population pharmacokinetic/pharmacogenetic model and investigate the impact of genetic variations, sex, demographic and biochemical variables on single-dose efavirenz pharmacokinetics among Ugandan subjects, using NONMEM. METHODS Efavirenz plasma concentrations (n = 402) from 121 healthy subjects were quantified by high-performance liquid chromatography. Subjects were genotyped for 30 single nucleotide polymorphisms (SNPs), of which six were novel SNPs in CYP2B6, CYP3A5 and ABCB1. The efavirenz pharmacokinetics was described by a two-compartment model with zero- followed by first-order absorption. RESULTS Apparent oral clearance (95% confidence interval) was 4 l h l-1 (3.5, 4.5) in extensive metabolizers. In the final model, incorporating multiple covariates, statistical significance was found only for CYP2B6*6 and CYP2B6*11 on apparent oral clearance as well as ABCB1 (rs3842) on the relative bioavailability. Subjects homozygous for CYP2B6*6 (G516T, A785G) and *11 displayed 21 and 20% lower apparent oral clearance, respectively. Efavirenz relative bioavailability was 26% higher in subjects homozygous for ABCB1 (rs3842). The apparent peripheral volume of distribution was twofold higher in women compared with men. CONCLUSIONS The model identified the four factors CYP2B6*6, CYP2B6*11, a novel variant allele in ABCB1 (rs3842) and sex as major predictors of efavirenz plasma exposure in a healthy Ugandan population after single-dose administration. Use of mixed-effects modelling allowed the analysis and integration of multiple pharmacogenetic and demographic covariates in a pharmacokinetic population model.