Abstract
In this paper, we introduce a Bayesian analysis for bioequivalence data assuming multivariate pharmacokinetic measures. With the introduction of correlation parameters between the pharmacokinetic measures or between the random effects in the bioequivalence models, we observe a good improvement in the bioequivalence results. These results are of great practical interest since they can yield higher accuracy and reliability for the bioequivalence tests, usually assumed by regulatory offices. An example is introduced to illustrate the proposed methodology by comparing the usual univariate bioequivalence methods with multivariate bioequivalence. We also consider some usual existing discrimination Bayesian methods to choose the best model to be used in bioequivalence studies.
ACKNOWLEDGMENTS
The authors acknowledge helpful suggestions by the editor and the referees of this paper. J. A. A. was partially funded by a CNPq grant number 300235/2005-4. R. M. S. was partially funded by a FAPESP grant number 2007/01594-0.
Notes
(S.D.: standard deviation; C.V.: coefficient of variation).