title: Impact of modelling intra-subject variability on tests based on non-linear mixed-effects models in cross-over pharmacokinetic trials with application to the interaction of tenofovir on atazanavir in HIV patients.
abstract: We evaluated the impact of modelling intra-subject variability on the likelihood ratio test (LRT) and the Wald test based on non-linear mixed effects models in pharmacokinetic interaction and bioequivalence cross-over trials. These tests were previously found to achieve a good power but an inflated type I error when intra-subject variability was not taken into account. Trials were simulated under H0 and several H1 and analysed with the NLME function. Different configurations of the number of subjects n and of the number of samples per subject J were evaluated for pharmacokinetic interaction and bioequivalence trials. Assuming intra-subject variability in the model dramatically improved the type I error of both interaction tests. For the Wald test, the type I error decreased from 22, 14 and 7.7 per cent for the original (n = 12, J = 10), intermediate (n = 24, J = 5) and sparse (n = 40, J = 3) designs, respectively, down to 7.5, 6.4 and 3.5 per cent when intra-subject variability was modelled. The LRT achieved very similar results. This improvement seemed mostly due to a better estimation of the standard error of the treatment effect. For J = 10, the type I error was found to be closer to 5 per cent when n increased when modelling intra-subject variability. Power was satisfactory for both tests. For bioequivalence trials, the type I error of the Wald test was 6.4, 5.7 and 4.2 per cent for the original, intermediate and sparse designs, respectively, when modelling intra-subject variability. We applied the Wald test to the pharmacokinetic interaction of tenofovir on atazanavir, a novel protease inhibitor. A significant decrease of the area under the curve of atazanavir was found when patients received tenofovir.
authors.affiliation: INSERM U738, Paris, France. xaviere.panhard@bch.aphp.fr
authors.forename: Xavière
authors.initials: X
authors.lastname: Panhard
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: Taburet
authors.forename: Christophe
authors.initials: C
authors.lastname: Piketti
authors.forename: France
authors.initials: F
authors.lastname: Mentré
mesh_terms: D000225:Adenine / Q000031:analogs & derivatives* / Q000493:pharmacokinetics / Q000627:therapeutic use; D019380:Anti-HIV Agents / Q000493:pharmacokinetics* / Q000627:therapeutic use; D000069446:Atazanavir Sulfate; D015982:Bias; D018592:Cross-Over Studies; D004347:Drug Interactions; D005602:France; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D016013:Likelihood Functions; D017711:Nonlinear Dynamics; D009842:Oligopeptides / Q000493:pharmacokinetics* / Q000627:therapeutic use; D063065:Organophosphonates / Q000493:pharmacokinetics* / Q000627:therapeutic use; D011725:Pyridines / Q000493:pharmacokinetics* / Q000627:therapeutic use; D000068698:Tenofovir
chemical_list: D019380:Anti-HIV Agents; D009842:Oligopeptides; D063065:Organophosphonates; D011725:Pyridines; D000069446:Atazanavir Sulfate; D000068698:Tenofovir; D000225:Adenine