Bioequivalence and Bioavailability Forum

Hi David,

❝ ❝ [quote from ICE E9]

❝ ❝ Did you ever see that in a protocol? I didn’t.

❝

❝ Never saw it either, although at the planning stage a lot of sensitivity analysis are done (at least, in the studies I work with)

AFAIK, in phase III that’s regularly done. I know some people doing it in BE. However, it doesn’t make it to the protocol. Hence, the EC is left out in the rain.

❝ Not hard-core frequentist, but going bayesian is still a crime for some statisticians and I would only go that way if other alternatives are not available

❝ ❝ Again: Post hoc power. How relevant is it?

❝

❝ It might be relevant, if you note a trend in approved studies: for instance, if most of them are significantly (still to be defined what might be significantly) overpowered and the assumptions defined in sample size calculation are far way from the observed parameters, I think this might be an issue that should handled and it is being neglected.

Agree. Concerning overpowering see this post and play around with the functions exppower.TOST() and expsampleN.TOST() in PowerTOST. Surprises guaranteed. See also this presentation (slide 8 and followings) and this article.

❝ By the regulators, which should be (again, imo) more open to share their information on CV and GMR of already approved drugs, and by the sponsors that should present strong justifications (as per ICH E9) on their protocols, such as sensitivity analysis and references that support their assumptions (other than "available literature" and "in-house data") and should look more carefuly to other design strategies available instead of just plugging a CV based on intuition.

Agree, again.

❝ Otherwise, we are assuming that sample size is magic performed by the sta­tis­tician to acchieve the maximum budget of the project

Do you know Clarke’s third law?

Any sufficiently advanced technology is indistinguishable from magic.