Bioequivalence and Bioavailability Forum

Hi Mikalai,

❝ I may be wrong but I cannot see how we can get a true within-subject CV of any drug.

Of course, you are right. The true CV_wR is unknown. But reference-scaling should be done for true HVD(P)s, i.e., where the population’s CV_wR >30%. However, \(s_{wR}\) is the best unbiased estimate of \(\sigma_{wR}\). The former is used in the expansion formula, i.e., treating \(s_{wR}\) as a true value.

❝ I may be wrong, but even with simulations (I suppose with simulations some assumptions regarding variance should be made), it is very difficult or even impossible.

There are essentially two options:

1. Our ad hoc solution¹ by simulating under the assumption \(s_{wR}=\sigma_{wR}\) to iteratively adjust \(\alpha\). That’s in the “spirit of the guideline” where the observed CV_wR is used for expanding the limits.
   
2. Muñoz et al.² suggested to “assume the worst” and – since the true value is unknown – adjust \(\alpha\) always as if CV_wR = 30%. That’s in any case the most conservative approach but might negatively impact power in case of high CVs (were the upper cap of scaling and the GMR-restriction already effectively controls the TIE). For examples see there.

Note that in both approaches the GMR of the Null is specified according to the expanded limits.

Still: The expansion is based on the observed CV_wR. We once had the crazy idea of using a very conservative (99.9%) CI instead. Doesn’t work because then we would practically never be allowed to scale…

❝ […] what regulators say on this subject?

Nothing. I raised this issue at numerous conferences. Dead silence. Armin Koch (co-author of one of the papers³ noting the inflated TIE) is a member of the EMA’s Biostatistical Working Party. Sent him an e-mail in 2016. No answer. 

❝ I do not remember any reflection on this matter in official documents (EMA, FDA)?

EMA = zero. At the 2^nd GBHI conference (Sep 2016, Rockville) László Endrenyi gave a presentation “Features, Constraints, and Extensions of the Scaling Approach” where he showed examples of the TIE, both for the EMA’s and the FDA’s approaches. Donald Schuirmann said “There is a recent paper in Pharm Res. showing how to deal with the inflation of the type I error. This is an excellent and applicable approach.” and told me in a coffee-break “… if this is correct, we have to modify our method”. Didn’t happen. Will ask him again next month at the 4th GBHI in Bethesda.

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1. Labes D, Schütz H. Inflation of Type I Error in the Evaluation of Scaled Average Bioequivalence, and a Method for its Control. Pharm Res. 2016: 33(11); 2805–14. doi:10.1007/s11095-016-2006-1.
   
2. Muñoz J, Alcaide D, Ocaña J. Consumer’s risk in the EMA and FDA regulatory approaches for bioequivalence in highly variable drugs. Stat Med. 2016: 35(12); 1933–43. doi:10.1002/sim.6834.
   
3. Wonnemann M, Frömke C, Koch A. Inflation of the Type I Error: Investigations on Regulatory Recommendations for Bioequivalence of Highly Variable Drugs. Pharm Res. 2015: 32(1); 135–43. doi:10.1007/s11095-014-1450-z.