## Outlier PK Study – Non Normal Distribution [Regulatives / Guidelines]

Good Morning

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.

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

Dependent   Ratio_%Ref_ CI_90_Lower CI_90_Upper CV% Ln(Cmax)    112.3365    101.6649    124.1284    29.36% Ln(AUClast) 102.4207     96.91779   108.2361    14.98%

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

The thing is in my understanding it is not accepted to exlude a subject after the bioanalysis. How can we argue an outlier?

On the other hand, we have demostrate that the distribution of the RLD in case of CMax it is not normal. If we apply the arithmetic means (not transformed) to our subjects, the result is:

Obs PK   Mean_Ratio Lower_90 Upper_90 BE_Limits Result  1  AUCT 101.989    96.703   107.274  80-120    BE Untrans.  2  Cmax  93.634    83.252   104.016  80-120    BE Untrans

meeting perfectly the BE criteria (80 - 120%) even including the outlier.

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

Obs PK   Mean_Ratio Lower_90 Upper_90 BE_Limits Result  1  AUCT 101.989    96.703   107.274  80-120    BE untransformed  2  Cmax  93.634    83.252   104.016  80-120    BE untransformed

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