Effect of CYP2C19 polymorphism on nelfinavir to M8 biotransformation in HIV patients

Abstract

What is already known about this subject: * Nelfinavir is an HIV protease inhibitor, substrate of the transporter P-glycoprotein and metabolized via CYP2C19, CYP3A4 and CYP3A5 enzymes. * Pharmacokinetic studies have shown wide interindividual variability of nelfinavir concentrations, some of this variability perhaps caused by variant drug metabolism or transporter genes. * For CYP3A4*1B and CYP3A5*3 polymorphism, results from three studies are in agreement, showing no difference in nelfinavir concentrations between patients with these different genotypes. * However, for MDR1 and CYP2C19 polymorphism, there have been contradictory studies, showing either no impact on nelfinavir concentration or modified concentrations which could influence virological response.

What this study adds: * Patients with an *1/*2 or *2/*2 genotype for CYP2C19 had a nelfinavir to M8 biotransformation divided by 2 compared with *1/*1 patients. * No evidence of any influence of MDR1 polymorphism on nelfinavir absorption could be detected.

Aims: To evaluate the effect of CYP2C19 polymorphism on nelfinavir and M8 pharmacokinetic variability in human immunodeficiency virus-infected patients and to study the link between pharmacokinetic exposure and short-term efficacy and toxicity.

Methods: Nelfinavir (n = 120) and M8 (n = 119) concentrations were measured in 34 protease inhibitor-naive patients. Two weeks after initiating the treatment, blood samples were taken before, 1, 3 and 6 h after drug administration. Genotyping for CYP3A4, 3A5, 2C19 and MDR1 was performed. A population pharmacokinetic model was developed to describe nelfinavir-M8 concentration time-courses and to estimate interpatient variability. The influence of individual characteristics and genotypes were tested using a likelihood ratio test. Estimated mean (C(mean)), maximal (C(max)) and trough (C(trough)) nelfinavir and M8 concentrations were correlated to short-term virological efficacy and tolerance using Spearman nonparametric correlation tests.

Results: A one-compartment model with first-order absorption, elimination and metabolism to M8 best described nelfinavir data. M8 was modelled by an additional compartment. Mean pharmacokinetic estimates and the corresponding intersubject variabilities were: absorption rate 0.17 h(-1) (99%), absorption lag time 0.82 h, apparent nelfinavir total clearance 52 l h(-1) (49%), apparent nelfinavir volume of distribution 191 l, M8 elimination rate constant 1.76 h(-1) and nelfinavir to M8 0.39 h(-1) (59%) in *1/*1 patients and 0.20 h(-1) in *1/*2 or *2/*2 patients for CYP2C19*2. Nelfinavir C(mean) was positively correlated to glycaemia and triglyceride increases (P = 0.02 and P = 0.04, respectively).

Conclusions: The rate of metabolism of nelfinavir to M8 was reduced by 50% in patients with *1/*2 or *2/*2 genotype for CYP2C19 compared with those with *1/*1 genotype.

Figure 1

Pharmacokinetic compartment model for nelfinavir and M8 plasma concentration after a nelfinavir oral dose D. Nelfinavir (in compartment 1) undergoes irreversible biotransformation to produce M8 (in compartment 2). F denotes bioavailability of nelfinavir, k_a the first-order absorption rate constant, V the nelfinavir distribution volume, k_e the nelfinavir elimination constant rate, k_m the first-order metabolic rate constant, V_m the M8 distribution volume and k_em the M8 elimination rate constant

Figure 2

Observed (points) and predicted (lines) plasma concentrations of nelfinavir (top) and M8 (bottom) vs. time: for CYP2C19 wild type, i.e. patients GG for CYP2C19*2 (empty points and dashed lines) and for CYP2C19 mutated patients, i.e. AG or AA for CYP2C19*2 (full points and lines). For nelfinavir, full and dashed lines are superposed

Figure 3

Evaluation of the final model: comparison between the 5th (dash line), 50th (full line) and 95th (dash line) percentile obtained from 1000 simulations and the observed data (points) for nelfinavir (top) and M8 (bottom)

Figure 4

Correlation between C_mean,N and the change in glycaemia or triglyceride rate between week 4 and week −4