Nele,
I dont agree that with this assertion "I know that in a one-compartment
model, NONMEM would not be able to differentiate between IIV on volume
or IIV on F1"
If you use this approach (similar to that suggested by Mats)
$OMEGA 0.5 ; BSV_F1
$OMEGA BLOCK(2)
.5 ; BSV_CL
0 .5 ; BSV_V ; Note zero covariance between CL and V
$PK
F1=EXP(BSV_F1) ; relative 'bioavailability, protein binding, etc.'
CL=POP_CL*EXP(BSV_CL)
V=POP_CL*EXP(BSV_V)
then you can in theory identy the 3 BSV components. This is because
anything that causes between subject variability in F1 (which can be
differences in bioavailability, protein binding, dose error) will affect
CL and V identically. If there is an additonal uncorrelated source of
BSV for CL e.g. renal function, and BSV for V e.g. partition into fat,
then this can be identified. The $PK code above is equivalent to this:
CL=POP_CL*EXP(BSV_F1 + BSV_CL)
V=POP_CL*EXP(BSV_F1 + BSV_V)
Nick
nele.pl...@nycomed.com wrote:
Dear Mats,
thank you, that is exactly what I am trying now (as I have IIV on
central volume). I will now only include the diagonal elements of the
omega matrix, and have included the correlation in the thetas as CL/F.
Let's see how this works.
One question out of curiosity: I know that in a one-compartment model,
NONMEM would not be able to differentiate between IIV on volume or IIV
on F1. But with more compartments, this should work, shouldn't it,
even if I only have oral data?
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.pl...@nycomed.com
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
*mats.karls...@farmbio.uu.se*
16.04.2009 09:05
To
drmo...@pri-home.net, Nele Plock/DEKON/AP/alt...@altana-mail,
nmusers@globomaxnm.com
cc
Subject
RE: [NMusers] OMEGA BLOCK with mixture model?
Hi Diane,
With oral data only I would normally model with BLOCK(2) on CL/F and
V/F or a DIAG(3) on CL/F, V/F and relative F. The latter may have some
advantages for diagnostics, covariate model building etc. Also, if the
underlying model truly is a mixture model on F, it could be
parsimonious, needing mixture only one parameter only. You can’t have
IIV on CL, V and relF + off-diagonal elements without
overparameterizing the model. However, although I have never tried it,
I guess that a BLOCK(2) on CL and relative F could work, provided you
have no ETA on V. If you also have an ETA on V all the problems you
mention would be realized. I don’t know if Nele has IIV on V, but if
so, she should definitely reduce IIV model size. With respect to the
mixture model, maybe it is possible to reparameterize such that the
mixture component only concerns one ETA.
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:* Diane R Mould [mailto:drmo...@attglobal.net] *
Sent:* Wednesday, April 15, 2009 6:16 PM*
To:* 'Mats Karlsson'; nele.pl...@nycomed.com; nmus...@globomaxnm.com*
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
------------------------------------------------------------------------
*From:* owner-nmus...@globomaxnm.com
[mailto:owner-nmus...@globomaxnm.com] *On Behalf Of *Mats Karlsson*
Sent:* Tuesday, April 14, 2009 2:08 PM*
To:* nele.pl...@nycomed.com; nmus...@globomaxnm.com*
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-nmus...@globomaxnm.com
[mailto:owner-nmus...@globomaxnm.com] *On Behalf Of
*nele.pl...@nycomed.com*
Sent:* Tuesday, April 14, 2009 5:09 PM*
To:* nmus...@globomaxnm.com*
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.pl...@nycomed.com
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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Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
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