Bioequivalence and Bioavailability Forum

Dear BE-proff,

❝ I have the following data:

❝ n=20

❝ CV=0.18 (for Cmax and AUC)

❝ GMR1 = 0.97

❝ GMR2=1.19

❝

❝ If to calculate size based on GMR1 I think it's better to use a script:

❝ (...) if to use GMR = 1.19 we see something terrible:

❝ (...) What to do in such situations?

If your product has a true GMR of 1.19 for a primary ratio, then 166 may be a sample that meets your power requirement size.
However, bear in mind that such calculations involve models with assumptions, notably a Normal distribution on the log scale. Your GMR from the trial is an estimate and not a true value; a good guess is that there is 50% chance the true GMR is worse.

In this paper, the author tried to look into the various options for situations like yours: How to use the result from one trial in the planning of the next?
The answer was: You have several options, but you do not get any easy solution that allows high power and low sample size if you try to make use of the observed GMR (and that, by the way, is also why pilot trials are not good approaches for telling if candidate formulations are so promising that a pivotal trial is merited). And if you gamble and use a GMR for planning that is closer to 1.0 than what you observed previously then you are also easily screwing yourself.