Bayesian approach to bioequivalence assessment: an example.

The statistical methods required for a Bayesian analysis of bioequivalence are outlined and numerically illustrated. The analysis consists of the calculation of the posterior probability, given the experimental results, that the ratio of true means of a new and a standard formulation of a drug with respect to some biological response lies in a given interval. Nomograms helpful for the calculation of these probabilities are provided.

Comparison of different methods for decision-making in bioequivalence assessment.

If the regulatory requirements are symmetrical, the use of symmetrical confidence intervals as a decision rule for bioequivalence assessment leads, as shown by simulations, to better level properties and an inferior power compared to a rule based on shortest confidence intervals. A choice between these two approaches will have to depend on a loss function. For asymmetric regulatory requirements, symmetrical confidence intervals should not be used; however, a decision can still be based on posterior probabilities, pr (theta epsilon [r1, r2]/x), or shortest confidence intervals. For purposes of inference, presentation and interpretation of results, we think that the use of symmetrical confidence intervals alone can be misleading and we therefore recommend that the posterior probabilities and densities, or at least the shortest confidence intervals, be given.