RE: OMEGA BLOCK with mixture model?
Dear all,
thank you for all your responses, and it seems to me the topic has raised
quite some discussions. Especially the point Diane brought up seemed to be
a very reasonable thought to me, and I will definitely try and see if this
changes anything with respect to model stability, and if I can omit the
correlation between the omegas.
Also, thanks for all the tips how to correctly code the OMEGA BLOCK.
Best regards
Nele
______________________________________________________________
Dr. Nele Plock
Pharmacometrics -- Modeling and Simulation
Nycomed GmbH
Byk-Gulden-Str. 2
D-78467 Konstanz, Germany
Fon: (+49) 7531 / 84 - 4759
Fax: (+49) 7531 / 84 - 94759
mailto: nele.plock
http://www.nycomed.com
County Court: Freiburg, Commercial Register HRB 701257
Chairman Supervisory Board: Charles Depasse
Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders
Ullman
drmould
15.04.2009 18:16
Please respond to
drmould
To
mats.karlsson
nmusers
cc
Subject
RE: [NMusers] OMEGA BLOCK with mixture model?
Dear All
I am not sure if this topic has been covered before or not, but as its
related to the question below, I thought I would bring it up again.
I have to wonder at the appropriateness of including the IIV term for F in
an omega BLOCK structure in the first place? I can certainly understand
estimating relative bioavailability and even estimating the associated
variability for F, although there are often estimatability issues for an
IIV term for F, even with IV data to help estimate F (or at least using a
reference value for F like one formulation or one occasion).
However because with orally administered drugs, CL is really CL/F then
there is an inherent correlation between CL and F. With F and CL, this
correlation is really in the THETA values so that if the model captures
the correlation at the THETA level, ie allow for larger clearance with
larger F (or vice versa), then the random effects for F and CL may be
uncorrelated. However, if the population model does not capture that
correlation at the THETA level, then correlation will be captured via the
random effects, possibly resulting in an over-parameterized OMEGA matrix.
As this latter situation seems to be very common (e.g. that the
correlation between F and CL etc is picked up in the etas) then one might
expect to see high condition numbers, zero gradients etc when IIV on F is
added to the omega BLOCK structure.
I would guess that as a rule, its probably more appropriate to keep the
IIV term for F out of a BLOCK structure. Can anybody comment on this?
Best regards,
Diane
Quoted reply history
From: owner-nmusers
On Behalf Of Mats Karlsson
Sent: Tuesday, April 14, 2009 2:08 PM
To: nele.plock
Subject: RE: [NMusers] OMEGA BLOCK with mixture model?
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
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
On 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:
$OMEGA BLOCK(3)
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
Nele
______________________________________________________________
Dr. Nele Plock
Pharmacometrics -- Modeling and Simulation
Nycomed GmbH
Byk-Gulden-Str. 2
D-78467 Konstanz, Germany
Fon: (+49) 7531 / 84 - 4759
Fax: (+49) 7531 / 84 - 94759
mailto: nele.plock
http://www.nycomed.com
County Court: Freiburg, Commercial Register HRB 701257
Chairman Supervisory Board: Charles Depasse
Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders
Ullman
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