Bioequivalence and Bioavailability Forum

Dear all,

recently I read the EMA’s BE guideline again. Was not a particularly good idea.

4.1.8 Evaluation: Presentation of data
If for a particular formulation at a particular strength multiple studies have been performed some of which demonstrate bioequivalence and some of which do not, the body of evidence must be considered as a whole. Only relevant studies, as defined in section 4.1, need be considered. The existence of a study which demonstrates bioequivalence does not mean that those which do not can be ignored. The applicant should thoroughly discuss the results and justify the claim that bioequivalence has been demonstrated. Alternatively, when relevant, a combined analysis of all studies can be provided in addition to the individual study analyses. It is not acceptable to pool together studies which fail to demonstrate bioequivalence in the absence of a study that does.

It happens regularly that a study was repeated. Sometimes (esp. without a pilot study) it turned out that there were too few sampling time points around t_max, or the variability was larger and/or the T/R-ratio worse than assumed. A higher than anticipated dropout-rate rarely is a problem. However, in all of these cases the study is underpowered and may fail.
If the study is repeated and passes BE, all seems to be good. Submit the synopsis of the failed study and the full report of the passing one, together with a discussion/justification of why you repeated it. After that sometimes an agency wants to see the full report of the failed study as well. So far, so good – I thought.
I came across a case where the EMA asked for a »coverage probability«. I beg your pardon, the what? In frequentist inference the outcome of any test is dichotomous (in BE regardless whether TOST or the confidence interval inclusion approach is applied). Either the study passed or failed. Full stop. ‘Coverage probability’ smells of Bayesian statistics, which had its heyday in the mid 1980s. History, gone with the wind.

Now it gets tricky, namely the sentence »Alternatively, when relevant, a combined analysis of all studies can be provided in addition to the individual study analyses.« Alternatively? What might be considered relevant?
Pooling of data is always only exploratory and supportive. If the failed study is not complete crap, any confidence interval of the pooled data will be likely narrower than the ones of both of the studies (large sample size, more degrees of freedom). Which confidence level one uses is actually arbitrary. In each of the confirmatory studies, the entire α was already spent. Hence, α = 0.0294 (the wrong one of the guideline’s two-stage design) or α = 0.0304 (the correct one for equivalence but in a parallel group-sequential design) is wrong as any other. If you really want to dive into the murky water, report the usual 90% CI. Even if the 90% CI is outside the BE-limits, it does not matter.

P.S.: The M13A does not contain stuff like that. THX!