From: Mats Karlsson <*mats.karlsson*>

Date: Thu, 16 Apr 2009 09:50:08 +0200

Hi Nele,

So what exactly is the IIV model you are testing? Showing code is =

probably clearest. A model with only diagonal IIV in CL/F and V/F may =

well be underparameterized.

What happened with the mixture?

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: nele.plock

Sent: Thursday, April 16, 2009 9:12 AM

To: mats.karlsson

Cc: nmusers

Subject: RE: [NMusers] OMEGA BLOCK with mixture model?

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.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

mats.karlsson

16.04.2009 09:05

To

drmould

nmusers

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:drmould

Sent: Wednesday, April 15, 2009 6:16 PM

To: 'Mats Karlsson'; nele.plock

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-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

----------------------------------------------------------------------

Proprietary or confidential information belonging to Nycomed Group may

be contained in this message. If you are not the addressee indicated

in this message, please do not copy or deliver this message to anyone.

In such case, please destroy this message and notify the sender by

reply e-mail. Please advise the sender immediately if you or your

employer do not consent to Internet e-mail for messages of this kind.

Opinions, conclusions and other information in this message that

pertain to the sender's employer and its products and services

represent the opinion of the sender and do not necessarily represent

or reflect the views and opinions of the employer.

----------------------------------------------------------------------

----------------------------------------------------------------------

Proprietary or confidential information belonging to Nycomed Group may

be contained in this message. If you are not the addressee indicated

in this message, please do not copy or deliver this message to anyone.

In such case, please destroy this message and notify the sender by

reply e-mail. Please advise the sender immediately if you or your

employer do not consent to Internet e-mail for messages of this kind.

Opinions, conclusions and other information in this message that

pertain to the sender's employer and its products and services

represent the opinion of the sender and do not necessarily represent

or reflect the views and opinions of the employer.

----------------------------------------------------------------------

Received on Thu Apr 16 2009 - 03:50:08 EDT

Date: Thu, 16 Apr 2009 09:50:08 +0200

Hi Nele,

So what exactly is the IIV model you are testing? Showing code is =

probably clearest. A model with only diagonal IIV in CL/F and V/F may =

well be underparameterized.

What happened with the mixture?

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: nele.plock

Sent: Thursday, April 16, 2009 9:12 AM

To: mats.karlsson

Cc: nmusers

Subject: RE: [NMusers] OMEGA BLOCK with mixture model?

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.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

mats.karlsson

16.04.2009 09:05

To

drmould

nmusers

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:drmould

Sent: Wednesday, April 15, 2009 6:16 PM

To: 'Mats Karlsson'; nele.plock

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-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

----------------------------------------------------------------------

Proprietary or confidential information belonging to Nycomed Group may

be contained in this message. If you are not the addressee indicated

in this message, please do not copy or deliver this message to anyone.

In such case, please destroy this message and notify the sender by

reply e-mail. Please advise the sender immediately if you or your

employer do not consent to Internet e-mail for messages of this kind.

Opinions, conclusions and other information in this message that

pertain to the sender's employer and its products and services

represent the opinion of the sender and do not necessarily represent

or reflect the views and opinions of the employer.

----------------------------------------------------------------------

----------------------------------------------------------------------

Proprietary or confidential information belonging to Nycomed Group may

be contained in this message. If you are not the addressee indicated

in this message, please do not copy or deliver this message to anyone.

In such case, please destroy this message and notify the sender by

reply e-mail. Please advise the sender immediately if you or your

employer do not consent to Internet e-mail for messages of this kind.

Opinions, conclusions and other information in this message that

pertain to the sender's employer and its products and services

represent the opinion of the sender and do not necessarily represent

or reflect the views and opinions of the employer.

----------------------------------------------------------------------

Received on Thu Apr 16 2009 - 03:50:08 EDT