## Deficiencies or not [Study Assessment]

Dear Helmut.

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The statistically significant formulation effect for AUC

To continue with your example:

Assumed intra-subject CV of C

Assumed intra-subject CV of AUC

When assumed parameters used for sample size estimation will be theoretically observed in the study, i.e. the observed GMR will be 95% and observed intra-subect CV will be 10%, we will get 90% CI equal to 91.40-98.74% and statistically significant formulation effect (at a 10% significance level).

If the 90% CI does not contain 100%, the p value will always be <0.1 but how it could further exacerbated the uncertainty about fulfillment of the bioequivalence criteria? (Question for regulators.)

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I just want to point that it's observed more often for AUC

»

The only good thing on this point is that the regulators believe that test and reference IMPs are bioequivalent. (As they deal with power.)

Posteriori power is never ending story. The question on the power should be raised to the protocol, if it is addressed to the report, it is just a suggestion for future projects.

Additionaly You can remind them what the low power means: With lower power, the type II error (sponsor's risk) is higher - it means that the

I wish the regulators would be interested also in the type I error - it would mean that regulators do not believe that test and reference IMPs are bioequivalent. The probability of approving non-bioequivalent test product should be up to 5%. I noticed several studies which suprised me more than this deficiency letter. E.g. by using:

Btw. I am also sure you will get approval. As even studies where 90% CI was (partly) outside 80-125% were approved at the end.

Best regards,

zizou

PT Frustration - not related to vaccine

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3. ANOVA analysis of variance showed statistically significant (at a 5% significance level) differences in AUC_{(0-t)} between investigational products, which further exacerbated the uncertainty about fulfillment of the bioequivalence criteria.

The statistically significant formulation effect for AUC

_{(0-t)}is quite common. The sample size is ussualy estimated with intra-subject CV of C_{max}(as it is ussualy higher than of AUC_{(0-t)}).To continue with your example:

Assumed intra-subject CV of C

_{max}= 25% -> with assumed PE of 95% for target power 90%: n = 38Assumed intra-subject CV of AUC

_{(0-t)}e.g. 10%When assumed parameters used for sample size estimation will be theoretically observed in the study, i.e. the observed GMR will be 95% and observed intra-subect CV will be 10%, we will get 90% CI equal to 91.40-98.74% and statistically significant formulation effect (at a 10% significance level).

If the 90% CI does not contain 100%, the p value will always be <0.1 but how it could further exacerbated the uncertainty about fulfillment of the bioequivalence criteria? (Question for regulators.)

»

` 100% not within CI : 5.76% (∆ stat. significant)`

I just want to point that it's observed more often for AUC

_{(0-t)}than for C_{max}and it would be interesting to know the percentage of that also for AUC_{(0-t)}with lower variability. ;)»

2. Lack of a posteriori data on the power...

The only good thing on this point is that the regulators believe that test and reference IMPs are bioequivalent. (As they deal with power.)

Posteriori power is never ending story. The question on the power should be raised to the protocol, if it is addressed to the report, it is just a suggestion for future projects.

Additionaly You can remind them what the low power means: With lower power, the type II error (sponsor's risk) is higher - it means that the

**bioequivalent preparations**could be assessed wrongly as not bioequivalent with higher probability. The regulators should sleep well with higher type II error (unless the study was designed for e.g. 50% power from the start - but such protocols should be rejected).I wish the regulators would be interested also in the type I error - it would mean that regulators do not believe that test and reference IMPs are bioequivalent. The probability of approving non-bioequivalent test product should be up to 5%. I noticed several studies which suprised me more than this deficiency letter. E.g. by using:

- an approach - if study fail to conclude bioequivalence, perform bigger one.

As e.g. here in PAR DE/H/5934/003/DC (formerly UK/H/5815/003/DC) (PAR UK/H/5815/003/DC was also mentioned in this post but link to PAR UK/H/5815/003/DC isn't working anymore and I failed to find it elsewhere on the internet.)

`STUDY 1 - "was not considered suitable"`

STUDY 2 - N=19, Cmax GMR = 84.24, 90% CI 78.00 - 90.98 %, ISCV=13.72%

"Therefore the results failed to demonstrate that the test product desloratadine is bioequivalent to the reference product. This could probably be due to the number of drop-outs which was higher than expected, especially for desloratadine."

With assumption of low ISCV (observed ISCV was 13.72%) it could be sufficient to have N=12 (for statistical analysis) with standardly assumed GMR of 95% for at least 80% power.

So the reason for fail was observed GMR. Nevertheless (as usually) reason for repetition is low sample size resulting in the bigger repeated study regardless the TIE inflation.

STUDY 3 - N=32, Cmax GMR = 104.24, 90% CI 98.45 - 110.36 %, ISCV=13.53%

GMR in interval 95-105, ISCV lower than in previous study. BE is concluded.

If I would be a patient I would like to know how many bioequivalence studies were performed before achieving the bioeqivalence. (Or just report the TIE (the probability that it is non-bioequivalent treatment) if it is higher than 5%.)

- or another approach - scheme:

Image according to: PAR NL/H/4422/001/DC or the same in PAR Melatonin 3 mg film-coated tablets PL 39936/0006

Medicines & Healthcare products

Regulatory Agency

MHRA

Public Assessment Report

National Procedure

Melatonin 3 mg film-coated tablets

(melatonin)

PL 39936/0006

Arriello s.r.o - Again, I failed to find it on the internet (I downloaded it in the past). In the PAR PL 39936/0006, the results are reported with two more decimal places there, which is really better in this case.)

There is interesting pooling of 2-period pilot study with 3-period partial replicate pivotal study - evaluated in similar way as described by FDA for Groups. Nevertheless period 3 was only in the pivotal study so there could be some incomplete blocks? Moreover the pilot study is pilot study! The design was obviously changed from pilot to pivotal. Sampling times seem to be the same, but washout was changed from 3 to 6 days. Does it mean that the washout was insufficient in pilot study?

As the pilot study is providing us only with informations for conducting following pivotal study. The pilot study had neither concluded BE nor failed to conclude BE, i.e. no alpha spended in the pilot study. So simply the pilot study doesn't demonstrate bioequivalence. If the bioequivalence would be demonstrated in the pilot study, why would they continue with the pivotal study? So I think there is no study which demonstrated bioequivalence but only one study which failed.

Above that 90% CI of "pooled Cmax" (76–95%) is not within the standard range 80.00-125.00%. (Widen limits are based on one of the pooled studies - clinical justification for widening not reported in PAR - justification that calculated intra-subject CV is a reliable estimate and that it is not the result of outliers also not reported.)

Btw. I am also sure you will get approval. As even studies where 90% CI was (partly) outside 80-125% were approved at the end.

Best regards,

zizou

PT Frustration - not related to vaccine

### Complete thread:

- Deficiencies 🇵🇱 Helmut 2021-01-26 10:47 [Study Assessment]
- Deficiencies 🇵🇱 ElMaestro 2021-01-26 12:26
- Deficiencies 🇵🇱 Helmut 2021-01-26 18:52
- Deficiencies 🇵🇱 ElMaestro 2021-01-26 22:34

- Deficiencies 🇵🇱 Helmut 2021-01-26 18:52
- Deficiencies or notzizou 2021-01-31 01:07
- Deficiencies or not Helmut 2021-01-31 15:46

- Deficiencies 🇵🇱 ElMaestro 2021-01-26 12:26