title: Bioequivalence tests based on individual estimates using non-compartmental or model-based analyses: evaluation of estimates of sample means and type I error for different designs.
abstract: OBJECTIVE
  The main objective of this work is to compare the standard bioequivalence tests based on individual estimates of the area under the curve and the maximal concentration obtained by non-compartmental analysis (NCA) to those based on individual empirical Bayes estimates (EBE) obtained by nonlinear mixed effects models.
  
  
  METHODS
  We evaluate by simulation the precision of sample means estimates and the type I error of bioequivalence tests for both approaches. Crossover trials are simulated under H ( 0 ) using different numbers of subjects (N) and of samples per subject (n). We simulate concentration-time profiles with different variability settings for the between-subject and within-subject variabilities and for the variance of the residual error.
  
  
  RESULTS
  Bioequivalence tests based on NCA show satisfactory properties with low and high variabilities, except when the residual error is high, which leads to a very poor type I error, or when n is small, which leads to biased estimates. Tests based on EBE lead to an increase of the type I error, when the shrinkage is above 20%, which occurs notably when NCA fails.
  
  
  CONCLUSIONS
  For small n or data with high residual error, tests based on a global data analysis should be considered instead of those based on individual estimates.
authors.affiliation: INSERM UMR 738, Université Paris Diderot, 16 rue Henri Huchard, 75018, Paris, France. anne.dubois@inserm.fr
authors.forename: Anne
authors.initials: A
authors.lastname: Dubois
authors.forename: Sandro
authors.initials: S
authors.lastname: Gsteiger
authors.forename: Etienne
authors.initials: E
authors.lastname: Pigeolet
authors.forename: France
authors.initials: F
authors.lastname: Mentré
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D018592:Cross-Over Studies; D006801:Humans; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D012107:Research Design; D013810:Therapeutic Equivalency