Bioequivalence and Bioavailability Forum

Dear all,

I’m struggling in understanding HC’s rules. The current guidance states:

2.3.5 Outlier consideration
Comparative bioavailability studies are small studies compared to other clinical trials. One or two extreme values could have a large effect on the inference to be made from these small studies. The usual parametric assumptions and estimation are not robust against extreme values.

Specific procedures to identify and account for outliers should be pre-specified in the protocol. No more than 5% of the subjects may be considered to be outliers, unless there are 20 or fewer subjects, in which case only 1 subject may be removed. Any protocol for handling outliers should be followed before the results of the analysis are summarised into confidence intervals (i.e., regardless of whether results meet the standard, the outlier protocol should be followed).

The protocol for handling outliers should include the following.

1. The observation(s) should be identified by an outlier test. It is recommended that a simple outlier test, such as a studentised residual being greater than 3, be used.
   
2. The observation(s) should be outside the range of all the other observations regardless of formulation. In other words, the procedure should only identify observations which are very different from all others collected.
   
3. The subject in question should be identified as an outlier for all parameters, for either the test or reference product, upon which the bioequivalence decision is to be based. Parameters of interest are usually an AUC and C_max measure, but in some instances other parameters are required.

I’m fine with the introduction and the first two procedures. The third one gives me headaches. What is meant by “The subject in question should be identified as an outlier for all parameters”? It is not uncommon that one PK metric shows extreme values but not others. Is it really meant that in such a case the outlier cannot be excluded?

Background: I have a pilot study on my desk where 4 PK metrics are agreed upon with HC as primary (C_max, AUC_0–t, and two partial AUCs) for the pivotal study. One subject showed for the first pAUC a T/R-ratio of 6.993 (!) with a studentized residual of –7.198. Studentized residuals of the other metrics are fine. OK, it’s a pilot study. Would already pass BE with flying colors for 3 metrics but the upper 90% CI for the first pAUC is 156.4% (CV 50.1%). After exluding the subject the CV would decrease to 22.1%. Do I understand the guidance correctly: I’m not allowed to exclude the pAUC of the outlying subject cause the other metrics are fine?
in writing the protocol of the pivotal study.