RE: Two compartment model with fixed omega parameters
Dear Waroonrat,
That's almost a philosophical question! One could argue that the data simply do
not provide this information and so there is no way to estimate IIV for V2 and
Q. One could also argue that perhaps FOCE-I does not provide the most accurate
approximation to the likelihood possible, and that you could perhaps get closer
using SAEM or some other routine. I have always assumed that if FOCE-I cannot
recover it, it is not there, but I have seen some things lately that make me
believe this may not be the case. Try SAEM and see if that performs better :-).
Kind regards,
Rik
Quoted reply history
From: Waroonrat Sukarnjanaset [mailto:[email protected]]
Sent: 28 June 2017 11:49
To: Rik Schoemaker <[email protected]>
Cc: [email protected]
Subject: Re: [NMusers] Two compartment model with fixed omega parameters
Dear Martin and Rik,
Thank you so much for your helpful suggestions, I really appreciate it.
Could you please recommend me which estimation methods would be the possible
methods to estimate IIV for V2 and Q?
Sincerely,
Waroonrat
________________________________
From: Rik Schoemaker
<[email protected]<mailto:[email protected]>>
Sent: Tuesday, June 27, 2017 11:29 AM
To: Waroonrat Sukarnjanaset
Cc: [email protected]<mailto:[email protected]>
Subject: RE: [NMusers] Two compartment model with fixed omega parameters
Dear Waroonrat,
I fully support Martin's suggestions below, but to come back to your original
question: the fact that IIVs are set to zero for V2 and Q does not mean the
second compartment is 'gone'. If you would examine your model predictions,
inclusion of the second compartment -even without IIV- would result in the
characteristic bend in the elimination phase of your compound when viewed on
the log-scale. It is quite often that NONMEM FOCE-I cannot estimate IIV for V2
and Q and fixing them to zero can result in perfect predictions of your
observed concentration profiles including the two-compartment behaviour. No-one
would claim that these parameters are in fact the same for every single
subject, just that the data cannot support making them different for your
subjects in this case.
Kind regards,
Rik Schoemaker, PhD
Occams Coöperatie U.A.
Malandolaan 10
1187 HE Amstelveen
The Netherlands
http://www.occams.com
+31 20 441 6410
[email protected]<mailto:[email protected]>
[cid:[email protected]]
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Martin Bergstrand
Sent: 27 June 2017 11:30
To: Waroonrat Sukarnjanaset
<[email protected]<mailto:[email protected]>>
Cc: [email protected]<mailto:[email protected]>
Subject: RE: [NMusers] Two compartment model with fixed omega parameters
Dear Waroonrat,
To know if a model "adequately describe the data" you need to study model
diagnostics. Read more for example here:
http://onlinelibrary.wiley.com/doi/10.1002/psp4.12161/full
The AIC numbers in your case indicate that the two compartment model is a much
better description of your data than the one compartment model (read on AIC
here: https://en.wikipedia.org/wiki/Akaike_information_criterion). However,
this is only a relative comparison and as pointed out before does not say
anything about whether any of the models "adequately describe the data".
All the best,
Martin Bergstrand, Ph.D.
Senior Consultant
Pharmetheus AB
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Waroonrat Sukarnjanaset
Sent: Tuesday, June 27, 2017 10:52 AM
To: [email protected]<mailto:[email protected]>
Subject: [NMusers] Two compartment model with fixed omega parameters
Dear NMusers,
I have tried to find an appropriate base model.
I found that two compartment model with fixed Omega of V2 and Omega of Q = 0
(AIC 1860.17) provided smaller AIC than one compartment model (AIC 1921.83) did.
>From these findings (no variability on V2 and Q), is it suggesting that one
>cpt model could adequately describe the data?
I would truly appreciate it if you could give me some suggestions.
Kind regards,
Waroonrat