Optimal Design in Bioequivalence Studies Analyzed with Nonlinear Mixed Effects Models

• Activity Number: 386
• Type: Invited
• Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Statisticians in the Pharmaceutical Industry
• Author(s): France Mentre*+ and Thu Thuy N'guyen and Anne Dubois and Caroline Bazzoli
• Companies: Universite Paris-Diderot and Universite Paris-Diderot/INSERM and Universite Paris-Diderot/INSERM and Universite Paris-Diderot/INSERM
• Keywords: pharmacokinetics ; optimal design ; nonlinear mixed models ; PFIM ; bioequivalence ; cross over trials

Abstract

Nonlinear mixed effects models (NLMEM) can be used to analyze crossover pharmacokinetic bioequivalence or interaction trials. Before the modelling step, it is important to define an appropriate design which has an important impact on the precision of parameter estimates and on the power of tests. We propose an extension of the evaluation of the Fisher Information Matrix for NLMEM including within subject variability in addition to between subject variability using a first order expansion of the model. We also include fixed effects for covariates like treatment, period and sequence usually tested in crossover trials. We use the predicted standard errors to predict the power of the Wald test for difference or for bioequivalence and to compute the number of subject needed. These extensions are implemented in the newly released version PFIM 3.2 and were evaluated by simulations.