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RE: OMEGA BLOCK with mixture model?

From: Mats Karlsson <mats.karlsson>
Date: Tue, 14 Apr 2009 20:08:18 +0200

Dear Nele,


I think you may want to reconsider your model. If you have a negative
correlation between CL and F1, it is likely to be related to high
presystemic metabolism (first-pass) effect. If so, it seems strange to
assume that the F1 distribution would not change between the two
subpopulations. I think you need to have separate CL as well as F1 for the
two subpopulations. Thus I would have CL and F1 described by ETA(1) and
ETA(2) for subpopulation 1 and CL and F1 described by ETA(3) and ETA(4) for
the second subpopulation. If hepatic elimination is responsible for the
correlation, it is probably more parsimonious to use a semi-mechanistic
model with a hepatic compartment (with a single ETA for variation in
metabolic activity). Two examples of implementations of a separate hepatic
compartment are :

Piotrovskij et al. Pharm Res. 1997 Feb;14(2):230-7.

Gordi et al., Br J Clin Pharmacol. 2005 Feb;59(2):189-98


Best regards,




Mats Karlsson, PhD

Professor of Pharmacometrics

Dept of Pharmaceutical Biosciences

Uppsala University

Box 591

751 24 Uppsala Sweden

phone: +46 18 4714105

fax: +46 18 471 4003


From: owner-nmusers
Behalf Of nele.plock
Sent: Tuesday, April 14, 2009 5:09 PM
To: nmusers
Subject: [NMusers] OMEGA BLOCK with mixture model?


Dear all,

I am trying to fit a PK model to oral data. In the data, we observed two
things: First, CL seems to be negatively correlated with F1. Secondly, there
seem to be two subpopulations in the exposure, let's say a large group with
'normal' and a second group with high exposure. I would like to identify the
subpopulations using a mixture model, but keep the correlation between CL
and F1. Now I ran into problems when coding the $OMEGA BLOCK.

I figured the block to be something like:
0.1 ;CL1
0 FIX 0.1 ;CL2
0.01 0.01 0.1 ;F1

The error message that appears is:
a covariance is zero, but the block is not a band matrix

I assume that this means that I am not allowed to fix the correlation
between the two clearance-omegas to zero. However, it would be unreasonable
to allow a correlation, because the omegas belong to different
subpopulations, so there can't be a correlation. On the other hand, I did
not include subpopulations for F1, so how can I keep this correlation to
both CL-subgroups?

Any thoughts on this would be highly appreciated!
Best wishes

Dr. Nele Plock
Pharmacometrics -- Modeling and Simulation

Nycomed GmbH
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Received on Tue Apr 14 2009 - 14:08:18 EDT

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