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We have a product which we intend to submit to the US FDA. We have
done Fed and fasted BE study as per the US regulatory requirements.
In fed state, we have excellent results for the Cmax and AUC. The
point estimate is around 100 and the CIs (Confidence Intervals) are
not farther than +/- 5% from the mean for both the PK parameters.
However, in fasted study, surprisingly we have the CIs for Cmax
failing on the higher side just by a whisker with 125.5% as the upper
limit value. The point estimate is also on the higher side with a
value of about 117%.
Upon observing the data, we found that we have two volunteers, whose
T/R ratios are almost 200%. We have calculated the data without these
volunteers, even when one of these volunteer is eliminated from the
study, the study is passing successfully.
Since we have already passed the fed study comfortably, we don't
intend to do any changes in the formulation.
My query is:
1. Can we consider these two (or one of these two) as an outlier's?
And to do a mini-study involving these two volunteers plus some new
volunteer, to confirm the same.
1. Considering FDA's view point is it possible to repeat the
analysis of these two volunteers. Or to repeat the analysis of the
entire set of volunteers. Then to report the PK parameters based on
the repeat analysis results.
1. If none of these options are acceptable and we want to repeat the
study under fasted state with higher number of volunteers, i s it
justifiable to do the same with same formulation?
Thanks you all in advance.
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The following message was posted to: PharmPK
please first have a look a my previous answer to Isra's question
about retesting (especially the problem with no a-priori strategy
for dealing with outliers).
<>Just some interesting points:
Your confidence intervals are rather narrow (10% in the fed study and
17% in the fasted study).
Two subjects with a T/R ratio of 200% can only pull up the mean from
100% to 117% if your sample size is 12 and the other subjects 'stay'
at 100%. In order to get such a confidence interval I am guessing
your CV to be rather small (<10%) - therefore your drug is not a
>Since we have already passed the fed study comfortably, we don't
>intend to do any changes in the formulation.
Ok, maybe it's a product failure of the reference - but what if it's
a subject-by-formulation interaction?
>1. Can we consider these two (or one of these two) as an outlier's?
>And to do a mini-study involving these two volunteers plus some new
>volunteer, to confirm the same.
<>Yes, but what is your decision rule? Just exclude them, because you
don't like the results?
If you retest these two volunteers, you should also retest some of
the 'normal performing' subjects - not new ones.
One Caveat: Statistics will be very tricky - nothing for M$-Excel ;-)
>2. Considering FDA's view point is it possible to repeat the
>analysis of these two volunteers. Or to repeat the analysis of the
>entire set of volunteers. Then to report the PK parameters based on
>the repeat analysis results.
IMHO no way (both questions).
>3. If none of these options are acceptable and we want to repeat the
>study under fasted state with higher number of volunteers, i s it
>justifiable to do the same with same formulation?
<>Even if you repeat the study with a higher sample size, you are
BE. And maybe you will face the same problems again. One option would
be planning for a bail out procedure based on your previous study.
Presumably your data are not (log-)normally distributed (which is a
prerequisite for ANOVA), so you may opt for a nonparametric method.
Or you define exclusion rules which have to be applied prior to the
But: in my experience FDA don't like it, and it will be a risky business
without prior consultation with FDA's review staff.
Consultancy Services for Bioequivalence and Bioavailability Studies
tel/fax +43 1 2311746
Bioequivalence/Bioavailability Forum at http://forum.bebac.at
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It would be good idea to identify one subject that is really making a
difference when removed form the BE stats. The better way to go would
be to redose that particular subject along with approximately 20% of
the total number of subjects used in that particular study. Subjects
that comprise the 20% would behave as controls for the add-on study.
All you have to show is that the Cmax ratio of the outlier subject is
in allignment to the geomean Cmax ratios of the main study. once the
add-on study indicates that particular subject was indeed an outlier
then that subject could be removed from the final BE stats report of
your main study.
Repeat analysis should be performed with a clear objective. Too many
repeats are not considered good by the federal agency. I agree too,
that too many repeats are indicative of a lack of control on the
assay at that first glance. If repeats are to be done it should be
performed on a particular timepoint that is suspicious and should
also be justified for.
Yes, you could repeat that study with the same formulation but have
to base reasons to show that the product is BioInequivalent and not
really product failure.
Hope this helps
Manish Issar, Ph.D
4700 Sandoz Drive
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