Re: Improved absorption profile by forcing volume of the central compartment
"The method with interaction does not work due to the small sample size."
I do not think that this is correct. Sample size should not be an issue for FOCEI. If you have lag
time with random effect, this could be a problem for FOCE, but not the sample size.
Leonid
nonmem
> Hello Brenda,
>
> Your sample looks small.
>
> I have 38 subjects with rich data. FO method works, but plots for sume
> subjects do not look very good and there are few local maxima. The
> method with interaction does not work due to the small sample size.
> Although the prelimenary data are useful, nothing can make the plots
> perfect. I have to increase the sample size.
>
> Try to run the model for each subject without population estimates. It
> will give you an idea how the first order approcximation affects your
> plots.
>
> Try to play with the model of error. If your doses are very different,
> you may need to use CV+additive model.
>
> Try to implement correlation between Cl and V2, but set correlation
> between Ka and the other parameters to zero.
>
> Good luck,
> Pavel
>
Quoted reply history
> ----- Original Message -----
> From: Jurgen Bulitta
> Date: Tuesday, April 24, 2007 3:47 pm
> Subject: Re: [NMusers] Improved absorption profile by forcing volume of
> the central compartment
> To: "B.C.M. Winter - De" , nmusers
>
> > Dear Brenda,
> >
> > Just a couple of comments and questions:
> > 1) Is there a specific reason why you are using FO for a dataset
> > with
> > frequent sampling? How large is your between subject
> > variability?
> > I would recommend considering FOCE+I in your case (for a more
> > detailed assessment, see e.g. Bauer R et al. AAPS J. 2007;9:E60-83.)
> >
> > 2) Have you tried a 3 compartment model? I would try this, as
> > you
> > potentially have frequent observations during the absorption
> > phase.
> > The number of compartments depends on the rate of absorption,
> > sampling frequency, and (sometimes) method of analysis. So I
> > would
> > not worry too much, if you get something else than other reports
> > in literature.
> >
> > 3) I would recommend running visual predictive checks for each
> > group
> > of patients to check, if you have adequate predictive
> > performance in
> > each group. The parameter variability model could be one reason,
> > why you observe better individual fits but a worse objective
> > function
> > when you fix the volume. In addition, you could prepare some
> > boxplots
> > for the eta distributions in each group.
> >
> > 4) Did you try some of the models described by Dr. Nick Holford
> > in his 1992
> > cefetamet pivoxil paper? (J Pharmacokinet Biopharm. 1992;20:421-42.)
> >
> > 5) Sometimes, using a full variance covariance matrix for the
> > absorption
> > parameters improves the predictive performance during the
> > absorption
> > phase notably.
> >
> > Hope some of this will work (-:
> > Best regards
> > Juergen
> >
> >
> > -----------------------------------------------
> > Juergen Bulitta, PhD, Post-doctoral Fellow
> > Pharmacometrics, University at Buffalo, NY, USA
> > Phone: +1 716 645 2855 ext. 281, j
> > -----------------------------------------------
> >
> >
> >
> >