I have built a minimal PBPK model based on that of Fiserova-Bergerova V. Inhalation Anesthesia using physiologically based pharmacokinetic models. Drug Metab Rev. 1992;24:531-557
The project is attached. My question, why is Phoenix reporting F for the IV dosed subjects? How do I get the software to recognize IV F = 1?
Since F is a structural parameter, NLME will try to find a population estimate and calculate a posthoc value for each subject irrespective of dose route.
Note that the F values in posthoc-table for the subjects with IV are shrunk to the structural parameter value with zeroed eta: ilogit( tvFexp(nF) = ilogit( 0.917678exp(0)) = 0.714569
NLME failed to find nF for those subjects since it is impossible.
The attached project file shows you a method to distinguish the subjects by their respective dose routes. It defines a covariate ‘PODoseFlag’ and applies it to the definition of parameter F.
Bernd: As you probably noticed, I used up a lot of covariates in this model. How else can I get PML Phoenix to use weight and cardiac output of the individuals to multiply with a scalar (ie %CO * patients CO) for a specific tissue without using covariates?
Bernd; You don’t see a problem in this reduced version of the model, but when I add the 2 metabolites I triple the number of covariates and I think I run into the 32 covariate maximum, because PML seems to ignore the last added covariates. How is that 32 max counted? I think it is for every call on a covariate, ie for Vc1, Vc2 and Vc3 the wieght covar is called 3 times. It is easy to reach 32 when you add all of the tissue and flow parameters *3!
there is no maximum of 32 covariates. There might have been in a previous version of Phoenix, but the current version, 8.1., does not have a maximum there. The only restriction that we found for covariates is *Maximum number of covariate categories or occasions = 40.
Please check the project file attached where we created a hypothetical examples in PHX8.1 with 45 covariates included in a single parameter, and found that PML correctly incorporates all the covariates inside. In addition, it runs without any issue, but extremely slow:
It seems that, at that time, it has this maximum 32 restriction. To avoid this, Serge proposed using Scenario run mode to reduce the number of covariates, and then do a covariate search (see details inside this link).