## TSD statistical model - with multiple sites [Two-Stage / GS Designs]

Dear Helmut,

Thank you for sharing these references and valuable comments.

❝ BTW, the EMA’s modification of the model was shown to be irrelevant.

And if I deducted correctly, this helps that at least for FDA statistical model for TSD we can therefore omit interaction term and always combine stage data - as per Karalis model looks like this (1):
Stage 1: ‘sequence’, ‘period’, ‘treatment’ and ‘subject(sequence)’ all fixed
Stage 2 (EX): ‘sequence’, ‘treatment’, ‘stage’, ‘period(stage)’ and ‘subject(sequence × stage)’ all fixed - subject(sequence × stage) can also be random, since it produces same result.

We will conduct study on multiple sites, so it adds complexity to the statistical models to be used:
Stage 1 model: Sequence, Treatment, Site, Period (Site), Sequence*Site, Treatment*Site as fixed and Subject (Sequence*Site) as random
Stage 2 model: Sequence, Treatment, Site, Stage, Period (Site*Stage), Sequence*Site, Treatment*Site, Stage*Site, Sequence*Site*Stage as fixed effects and Subject (Sequence*Site*Stage) as random - and based on (1) we can omit Treatment*Site*Stage term.

❝ It is implemented in the -package Power2Stage since April 2018.

Indeed, we have used -package Power2Stage calculations when discussing approach with the FDA. These packages are lifesaver
Regardless FDA still requires us to submit simulations on the validated model to justify our "specific" TSD approach. We still need to figure out what this means.

❝ I recently faced a deficiency letter of a European agency where a study (passing BE with ‘Method B’ already in the first stage) was not accepted. Passed BE with the exact method as well…

But 'Method B' success in Stage 1 means your were already within the BE limits with even wider intervals (i.e. even smaller patient risk)! Cannot image why someone would reject this?

Regards
d_stat

1. Karalis V, Macheras P. On the Statistical Model of the Two-Stage Designs in Bioequivalence Assessment. J Pharm Pharmacol. 2014; 66(1): 48–52. doi:10.1111/jphp.12164.

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