Bioequivalence and Bioavailability Forum

Hi Mahmoud,

❝ In one of your lectures, you mentioned comparing the two profile as is, meaning AUC_0-12 to AUC_0-72, …

Well, that’s extreme. Did I really give such an example somewhere?

❝ … but won't be comparing orange vs apples, mean, if, for example the first AUC_0-12 (drug A) covers 50% of the profile while the comparator AUC_0-72 (drug B) covers 80%, is this a biased comparison?

If we talk about immediate release and the earliest common last sampling time point is at ≤2×t_max, no. In such a case absorption is essentially complete and the later time points are not informative at all (they describe only elimination, which is a property of the drug – not the formulations). See Fisher et al. 2016¹
My personal PK-guru Les Benet applied it in one of his studies.²

❝ Other method that was mentioned in the forum/lectures more often; is is doing log-linear regression using the terminal part of the profile with missing points and perform extrapolation to estimate such points, but no mentioned of such methods in any of the guidelines

Up to you. As long as you describe the procedure unambiguously in the SAP (which has to be accepted by the agency), fine. That’s my standard procedure for ages. No guideline is that specific.

❝ my question is: if comparing AUC_0-t as is (missing points are ignored) without doing the extrapolation and the BE criteria not met but when doing the extrapolation the BE is achieved, how such predicament will be handled by the assessor and/or CRO ?

Well, you should evaluate the study according to the SAP, right? Given, “at home” you can perform anything. If any other method will come to a conclusion different from the planned one and you present it as supportive information, I expect that any agency will essential say: “Thank you very much, interesting indeed. We play it safe and reject the study.”
Let’s reverse the idea. We know that a comparison of AUC_0–t is biased if the last measurable sampling time point in a certain subject differs for T and R (even if true bioavailabilities are identical). That’s not rocket science but basic PK. You followed the GL and the study passes. Would you really try another method afterwards (which fails) and show the result to the agency? I doubt it.

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1. Fisher D, Kramer W, Burmeister Getz E. Evaluation of a Scenario in Which Estimates of Bioequivalence Are Biased and a Proposed Solution: t_last (Common). J Clin Pharm. 2016; 56(7): 794–800. doi:10.1002/jcph.663. Open access.
   
2. Burmeister Getz E, Carroll KJ, Jones B, Benet LZ. Batch-to-Batch Pharmacokinetic Variability Confounds Current Bioequivalence Regulations: A Dry Powder Inhaler Randomized Clinical Trial. Clin Pharmacol Ther. 2016; 100(3): 223–231. doi:10.1002/cpt.373. Open access.