Normal Distribution: Japan only [Regulatives / Guidelines]

posted by Helmut Homepage – Vienna, Austria, 2017-10-23 12:25 (1983 d 21:16 ago) – Posting: # 17906
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Hi DaLoe,

unless you submit the study in Japan and the analysis was planned based on untransformed data, no way (see the Japanese Q&A document, Q-32 to Q-34).
Note that you would have calculate the PE and its CI in the original domain (i.e., as differences) and the acceptance range for untransformed data would be –0.20xR to +0.20xR.
Please give complete information in the future. Since you are speaking about “RLD”: Is the study for FDA-submission?

❝ Recently we have conducted a Fasting PK study (single croosover). The statistical report is as follow:

Dependent   Ratio_%Ref_ CI_90_Lower CI_90_Upper CV%

Ln(Cmax)    118.34      103.66      135.11      37%

Ln(AUClast) 103.72       97.87      109.92      15%

❝ As can be seen, the upper limit of the confidence interval do not meet PK criteria.

I’m struggling to reproduce your CVs. Was the sample size for Cmax 42 and for AUC 38? If yes, why do they differ?

❝ One of the subject is clearly an outlayer according Lund test. Removing the subject of the study, the results would be as follow …

Outlier tests are generally not acceptable (even if stated in the SAP).

❝ … resulting in meeting PK criteria, borderline, but meets criteria.

BTW, your calculation is wrong. If you are interested in the ratio of untransformed data, use Fieller’s confidence interval.

❝ The thing is in my understanding it is not accepted to exlude a subject after the bioanalysis.

Correct. Only exception (EMA): Exclusion if AUC of the suspected outlier <5% of the geometric mean of subjects with “normal” AUCs. Applicable to the reference only. IMHO, no way for the FDA.

❝ How can we argue an outlier?

Bad luck. Smells of cherry picking. :cherry picking:

❝ On the other hand, we have demostrate that the distribution of the RLD in case of CMax it is not normal.

❝ Due the distribution is not normal, neither in RLD nor in Test, but extremely not normal in RLD, …

The distributions of R and T are not relevant in BE. Only the model’s residuals are. It is possible that both R and T have skewed distributions and the residuals are still normal.

❝ … when we normalize the sequence …


❝ … the results show we are not meeting PK criteria because of the upper limit of the confidence interval of the CMax.

This table is exactly like the one before. What are you trying to tell us?

❝ It is possible to arg the distribution RLD is non mormal to file the PK report with untransformed results?

For the FDA, no. For the EMA, very unlikely. In Japan, maybe.

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