Dear Bill,
Appreciate your reply a lot. The issue is from KA. Adding KA or not did
have this problem. However, regarding your statement "it is rare to have
enough data to fit true IIV", can you explain more about this. My data set
is from Phase I studies, and I thought this should be enough for thi
Hi Xinting,
This is a rather broad (and often highly-opinionated) topic. At the highest
level, you can only fit parameters in a model where you have enough data to
estimate the parameter. A simple example is that if you have data that you
want to fit an Emax model to with measurements only up
Dear Nick,
In your reply to Siwei, you proposed the following code:
$PK
; CL=(CLnon-renal*f(age) + CLrenal*f(renal_function)) * allometric WT
CL=(THETA(1)*EXP(THETA(2)*(AGE-40)) + THETA(3)*CLCR/100)*(WT/70)**0.75
I would like to make a comment on the coding of the renal function. If CLCR
is
I am not sure that you need likelihood profiling or any other
sophisticated procedures to study this particular problem. You can look
at relative standard errors of the parameter estimates: if one of the
ETAs is poorly estimated, this is the candidate for removal. For
two-compartment models, it
Hans,
I agree with you that what I wrote was not properly explained. Thanks
for pointing this out. My previous comment was related to a question
about time-varying covariates. You raise other important issues about
how to use renal function as a covariate so I have re-named this thread
and of
Hi, Sebastien, Bill, Nick, Leonid, Mats and Hans:
Thank you all very much for the suggestions and nice discussions. I enjoyed
to learn from this thread and I am very clear how this should be handled
now. I believe this thread also provided a nice record for other new folks
like me to learn from.
I am sorry for multiple posting, but by mistake, this workshop was
listed as closed on ICON web site for the last two weeks while it is
actually open for enrollment. You can register by e-mailing
Lisa R. Wilhelm
lisa.wilh...@iconplc.com
Tel: 410-696-3060
Thanks
Leonid
Dear Siwei,
If you have a time-varying covariate, you may want to entertain the extended
models possible/necessary for time-varying, as opposed to time-constant,
covariates. See Wählby et al Models for time-varying covariates in
population pharmacokinetic-pharmacodynamic analysis. Br J Clin P
