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[NMusers] Validation and power of the Mixture Model

From: HUI, Ka Ho <>
Date: Wed, 14 Oct 2015 16:17:05 +0000

Dear all,

I am a fresh research student. Previously, I had the experience in developi=
ng a pharmacogenetics-based population PK model using NONMEM, but this is t=
he first time I work with the Mixture Model in NONMEM and I have some quest=
ions about it.

I have two datasets on hand, where patients' clearance are believed to be a=
ffected by their genotypes. While I have their genotypic information, I als=
o wish to know if the Mixture Model in NONMEM can help me accurately catego=
rize the population even if the genotypic information are "hidden" from NON=
MEM. The results turned out to be unsatisfactory somehow. For the subpopula=
tions with a distinctively different typical values of clearance, the sensi=
tivity and specificity can approach 100%, but for those with less differenc=
es, the average accuracy drops to 60-70%. Although it is not difficult to u=
nderstand that the computer will not be able to categorize these subjects w=
hen they have similar parameters (either mean values too close or variances=
 too large...), I am wondering if there is any general approach to utilize =
the best out of the Mixture Model function.

Regarding the power of the Mixture Model, I wonder if there has been any va=
lidation done before for datasets with different characteristics. For examp=
les, is there any previous study that looked into the accuracy of the Mixtu=
re Model function and can somehow express the typical accuracy in terms of =
the difference in, say, the mean plasma levels, between 2 subpopulations.

Last but not least, it would be great if anyone can kindly advise me any go=
od teaching materials about the Mixture Model in NONMEM.

Matthew Hui

Received on Wed Oct 14 2015 - 12:17:05 EDT

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