title: Integration of absorption, distribution, metabolism, and elimination genotyping data into a population pharmacokinetic analysis of nevirapine.
abstract: OBJECTIVE
  The aim of this analysis was to show the applicability of a newly developed algorithm to assess the influence of genetic variants and other covariates on nevirapine's drug disposition. The algorithm combines high-throughput genotyping data and nonlinear mixed effects modeling methods.
  
  
  METHODS
  Patients, who participated in the 2NN pharmacokinetic sub study, were reconsented and reenrolled into a clinical trial for genotyping analysis. Overall, 198 single nucleotide polymorphisms located in 45 absorption, distribution, metabolism, and elimination related genes were genotyped using the Illumina BeadArray technology. Data analysis was performed using NONMEM VI and SAS 9.1.3.
  
  
  RESULTS
  Overall, 1260 nevirapine plasma concentrations were obtained from 271 genotyped patients. Plasma concentration-time profiles of nevirapine were best described by a one-compartment model with auto-induced first-order elimination process. Nevirapine clearance was 19.4% reduced in Asian/Black patients, compared with Caucasian/Hispanic patients. For single nucleotide polymorphism rs3745274 (CYP2B6 516G>T) heterozygous patients (GT) showed a 15.3% reduced clearance; patients with homozygous CYP2B6 516TT alleles showed a 30.6% reduced clearance compared to patients with homozygous 516GG alleles. Patients carrying the homozygote genotype of rs12768009 (CYP2C19 8403AA), highly linked to rs4244285 (CYP2C19*2), showed a 26.8% reduced clearance compared with patients with CYP2C19 8403 AG and GG alleles.
  
  
  CONCLUSIONS
  By integration of high-throughput genotyping data into a pharmacometric analysis of nevirapine, the impact of the CYP2B6 516G>T polymorphism on nevirapine's exposure was confirmed and quantified. In addition, a new hypothesis with regard to CYP2C19 involvement in nevirapine metabolism has been generated. The analysis presented might help to optimize and individualize the therapy for patients treated with nevirapine to add to their therapeutic benefit.
authors.affiliation: Translational Medicine, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany. thorsten.lehr@boehringer-ingelheim.com
authors.forename: Thorsten
authors.initials: T
authors.lastname: Lehr
authors.forename: Jing
authors.initials: J
authors.lastname: Yuan
authors.forename: David
authors.initials: D
authors.lastname: Hall
authors.forename: Heike
authors.initials: H
authors.lastname: Zimdahl-Gelling
authors.forename: Hans Guenter
authors.initials: HG
authors.lastname: Schaefer
authors.forename: Alexander
authors.initials: A
authors.lastname: Staab
authors.forename: Thomas R
authors.initials: TR
authors.lastname: MacGregor
authors.forename: Supriya
authors.initials: S
authors.lastname: Jayadev
mesh_terms: D000042:Absorption / Q000187:drug effects; D000328:Adult; D019380:Anti-HIV Agents / Q000378:metabolism* / Q000493:pharmacokinetics* / Q000494:pharmacology; D003198:Computer Simulation; D030541:Databases, Genetic; D004305:Dose-Response Relationship, Drug; D005260:Female; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D019829:Nevirapine / Q000378:metabolism* / Q000493:pharmacokinetics* / Q000494:pharmacology; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D014018:Tissue Distribution / Q000187:drug effects; D055815:Young Adult
chemical_list: D019380:Anti-HIV Agents; D019829:Nevirapine