RE: [NMusers] truncation & simulation

Dear Ron,

Your original dataset provided clearance estimates for 100 =
patients, which were all within the range 5 to 30 L/h.=
  When you simulated 4800 clearance values (= 2 cros=
s-over observations/subject x 12 subject/trial x 200 trials)=
, I would expect to see a wider range of clearance v=
alues in the simulation dataset than in the original ana=
lysis, simply because there are many more observations in =
the simulation dataset.

However, arbitrarily truncating clearance to the range of =
5 to 30 L/h may not be wise. Consider the subject =
whose simulated clearance values are 30 L/h and 32 L/h, =
a 6.7% difference. If both of these values are trunca=
ted to 30 L/h, then there is zero within-patient differe=
nce in clearance values (and zero within-patient difference =
in AUC), and the truncation procedure both (1) reduces t=
he mean within-subject treatment difference and (2) reduces =
the within-subject treatment variability. Either one of t=
hese effects would arbitrarily increase the statistical powe=
r of attaining bioequivalence.

Statistical power for a bioequivalence test depends on the=
 projected mean within-subject treatment difference (say <==
5%), the projected mean within-subject variability (estimated =
in your original population PK analysis), and the sample =
size. Instead of truncating clearance values, I think y=
ou should examine the effects of larger sample sizes on =
the statistical power; maybe run simulations with 16, 24, =
36, and 48 subjects per study. In reality, very few =
bioequivalence trials will be successful with only 12 subj=
ects.

Good luck,
Steve

Steven Troy
Sr. Director,
Clinical Pharmacology and Pharmacokinetics
Shire Pharmaceuticals


-----Original Message-----
From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.co=
m] On Behalf Of Ron Mathôt
Sent: Tuesday, April 22, 2008 3:18 PM
To: nmusers_at_globomaxnm.com
Subject: [NMusers] truncation & simulation

Dear NONMEM users,

Currently I am working on the simulation of a bio-equava=
lence trial. For
the reference compound a population PK model has been de=
rived on basis
of data from 100 patients. Values for between-and within-p=
atient
variability are available for all PK parameters. The simul=
ation
comprises a randomized cross-over study with 12 patients t=
aking the
test and reference compound. Two-hunderd trials are simul=
ated and
summarized. During the simulations I noticed that truncation=
 of the
simulated of PK parameters significantly influences the powe=
r of the
study to confirm bio-equivalence. For instance truncation of=
 simulated
oral clearances of both compounds from a range of 1-300 =
L/hr to 5 - 30
L/hr doubled the number of positive trials (due to decre=
ased within-
patient variability). Post-hoc estimates form the popPK stud=
y indicated
that clearance values of the reference compound are all =
within the
latter range of 5 to 30 L/hr. I expect that oral cle=
arance of the test
compound will not differ more than 5% from the reference=
 compound. In my
opinion simulation of trials with the smallest range will =
produce more
reliable estimates of the power to detect bio-equivalence.

I would greatly appreciate your comments on this subject.
Best regards,

Ron Mathôt

Department of Hospital Pharmacy and Clincal Pharmacology
Erasmus University Medical Center
Rotterdam
The Netherlands




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Received on Tue Apr 22 2008 - 16:59:40 EDT