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Dear All,
We have done a cross-over study in 24 subjects to evaluate the effect
of co-administration of drug B on the bioavailability of A. The
purpose of the study was to hopefully demonstrate that B intake does
not affect exposure to A, and that for developing a combination
product no efficacy studies will be required.
The subjects received A + placebo and A + B in randomized order for
several weeks, with a wash-out of several weeks between the treatment
periods. The combination A+B is hereafter called the test T and A +
placebo the reference R. Samples were drawn on Day 1 of each period;
troughs to evaluate attainment of steady state and complete profiles
after the last dose of each period. We have gone through a lot of
effort to ensure medication intake and believe that the study was
properly designed.
Initially one group of 10 subjects and another group of 14 were to be
enrolled, as 24 subjects in one go was not feasible. Treatment order
was randomized and blocked for these two groups. But eventually due
to recruitment problems one group of 8 subjects and one group of 16
subjects was enrolled, three weeks apart. In the group of 8 subjects 5
got the order R-T; 2 got the order T-R and one (T-R) dropped out. In
the group of 16 subjects 7 got the order R-T; 7 got the order T-R and
two (T-R) dropped out. So in all, 12 got the order R-T and 9 the order
T-R (three R-T's dropped out, unrelated to the treatment).
The ratio T to R for AUCtau on the last dosing day (n=21) was 0.89,
90% CI 0.85 to 0.94; similar values were obtained for Cmax. Although
the 90%CI falls within 0.80-1.25, 1.0 is not included so I looked at
the data in more detail, mostly plots and geometric means for the two
treatment sequences, and this seemed to point at a sequence effect.
The group receiving sequence R-T (n=12) had a perfect geometric mean
AUCtau ratio (T to R) of 1.01, minimum individual ratio 0.80, maximum
was 1.26 (I am not making this up (:-)).
The group receiving sequence T-R (n=9) had a geometric mean AUCtau
ratio (T to R) of 0.78, minimum individual ratio 0.68, maximum was 0.98.
The low ratios for the group receiving T-R (n=9) appeared to be due to
a raised AUCtau for the reference treatment in Period 2. Geometric
mean AUCs for the test in Period 1 (n=9) or test in Period 2 (n=12)
and for the reference in Period 1 (n=12) were virtually the same; the
only AUC that was substantially higher was R in Period 2 (n=9). Then I
looked at the Day 1 data and the troughs and all these profiles
indicated a higher exposure in the nine subjects receiving the
Reference in Period 2. The wash out was such that a carry-over effect
was not to be expected, so we seem to be left with an unexplained
sequence effect.
As I have not encountered this before, and am not much of a
statistician, any help is appreciated. Do we need to go into all this
detail in the study report or just stick to the fact that technically
speaking the treatments are bioequivalent? Is there any way to find
out by whatever statistical test what has been going on? How will
regulatory agencies look upon such a study result? Should we go talk
with them? Helmut Schueltz has already kindly offered suggestions and
thought it would be interesting for all and suggested to put it on the
forum.
One other explanation could be the following, far-fetched maybe as too
many assumptions all need to be true at the same time:
1) there is a Period effect (which may for instance have to do with
different food intake in Autumn and in Winter) leading to a higher
exposure in Period 2 for both sequences;
2) co-administration of B does reduce the exposure to A, irrespective
of sequence
3) exposure to A is intrinsically higher in the n=9 subjects than in
the n=12 subjects due to inter-subject variability (CV's were appr.
30-50%).
Then the group R-T (n=12) has a raised exposure to A in Period 2 due
to 'winter' and a reduced exposure due to B intake which levels out
'winter' and R and T come out the same (as they did).
The group T-R (n=9) has a raised exposure to A in Period 2 due to
'winter' which is not counteracted by B, so a high R, and a reduced
exposure in Period 1 due to B (Test). However, since they had a higher
intrinsic exposure to A to start with, their exposure to test in
Period 1 comes out the same for the n=12 in Period 2 and also the same
as R for n=12 in Period 1.
Does this make any sense?
Thanks in advance for any thoughts or suggestions,
Frieda Ebes
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Hi Frieda,
Did you add the GROUP variable in your ANOVA model? Although you've
seen differences by sequence, did they have significant p-values? Your
results are curious, but in the end of the day what matters most in BE
trials is the bottom line. Your variability in the data is fairly high
(in one group, the confidence intervals touch both goal posts!) so I
would have to wonder if the sequence differences you are seeing are
just an artifact of high intrasubject variability. Further, with only
9 people in one sequence group, you really don't have enough subjects
to resolve differences between sequences. To answer your questions
about what a plausible explanation for your difference is, you'd
literally have to design and run another study. There are too many
variables here and not enough subjects. What I would do in the final
report is acknowledge a sequence difference if the p values were less
than 5%. Why? I don't know. Do we ever really know the reason for
sure? We never get to know why, because we only ever seem to look in
the central compartment for bioequivalence. Since this is steady-state
though it's tough for me to buy that this is a true carry-over effect.
Most of the time we are asking "why did it fail?" rather than "why did
it pass?". I suppose that's the industry's bias showing through. Why
do failed studies get all the attention? I've never seen someone put
this much thought into a passed study. Good on you for going the extra
mile.
Good luck,
-Dave
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The following message was posted to: PharmPK
Dear Frieda!
PK interaction studies are similar to BE studies, but not equal. Let's
start with the fundamental pharmacokinetic relationship
f(a) x D = AUC x CL
or, rewritten
f(a) x D
AUC = --------
CL
In BE testing we are relying on two assumptions (unfortunatelly many
people are not aware of #1):
(1) CL remains constant during the study
(2) D is the same (no potency correction)
For two formulations (T, R) we have
AUC(T) f(T) x D(T) CL(R)
------ = ----------- x ----
AUC(R) f(R) x D(R) CL(T)
applying assumptions (1) and (2) we get
AUC(T)
f(rel) = ------
AUC(R)
In a PK interaction study assumption #1 (equal clearances) may not hold!
Contrary to BE studies, where the AUC-ratio is only a measure of the
absorption characteristics of formulations, the concomitant treatment
of drug B may influence the clearance of drug A (AUC therefore is a
composite parameter).
See a basic paper published in 1994 by Schall et al.[1] and the chapter
'Analysis of pharmacokinetic interactions' in Hauschke et al. (2007).[2]
If the CI falls with the commonly applied acceptance range (AR) 'lack of
interaction' is likely (because a ratio close to unity would imply
either no influence of T on f(R) and CL(R) or an influence on both f(R)
and CL(R) in opposite directions to the same degree - which is
considered improbable).
The authors suggest in any case no further analyses, but include such an
possible influence on the clearance in the wording of the conclusion,
like 'the amount of drug A available in the systemic circulation is not
affected by concomitant administration of drug B' rather than 'drug B
does not affect the absoprtion of drug A'.
If an influence is observed (CI not within AR), the authors suggest a
second step in the analysis, namely
(1) the elimination half life of drug A
(2) the ratio of AUC/Tel (or AUC x kel)
The second metric was also proposed by Abdallah (1998)[3] in another
context (to 'reduce variability' of HVDs).
This is only an entry point from my side; though you didn't see residual
concentrations after the washout, some residual effects of T on the PK
cannot be excluded (higher concentration of the reference in the TR
group). IMHO I would go with the second part of the analysis
notwithstanding you have already shown a CI within the AR. Anyhow, from
a clinical point of view for a combination product any interaction may
go into the labeling (US) / SmPC (EU). Must sleep over it...
[1] Schall R Hundt HKL and HG Luus
Pharmacokinetic characteristics for extent of absorption and
clearance in drug/drug interaction studies
Int J Clin Pharmacol Ther 32/12, 633-637 (1994)
[2] Hauschke D, Steinijans V and I Pigeot
Bioequivalence Studies in Drug Development
John Wiley, Chichester, pp 175-203 (2007)
[3] HY Abdallah
An Area Correction Method To Reduce Intrasubject Variability In
Bioequivalence Studies
J Pharm Pharmaceut Sci 1(2), 60-65 (1998)
All the best,
Helmut
Ing. Helmut Schuetz
BEBAC - Consultancy Services for
Bioequivalence and Bioavailability Studies
Neubaugasse 36/11
1070 Vienna, Austria
e-mail helmut.schuetz.-a-.bebac.at
web http://bebac.at/
contact http://bebac.at/Contact.htm
forum http://forum.bebac.at=
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