Can anyone share NONMEM code of time-dependent residual error models
with me?
Many thanks in advance,
Best regards,
Xiang
The contents of this communication, including any attachments, may be
confidential, privileged or otherwise protected from disclosure. They are
intended solely for the use of the individual or entity to whom they are
addressed. If you are not the intended recipient, please do not read, copy,
use or disclose the contents of this communication. Please notify the sender
immediately and delete the communication in its entirety.
time-dependent residual error models
Xiang,
Here is an example. It might be possible to be more helpful if you revealed details of what you are trying to do.
$ERROR
IF (TIME.LT.1) THEN ; use eps(1) when time is less than 1
RUV=EPS(1)
ELSE ; otherwise use eps(2)
RUV=EPS(2)
ENDIF
Y=F+RUV
Nick
Yu, Xiang-Qing wrote:
> Can anyone share NONMEM code of time-dependent residual error models with me?
>
> Many thanks in advance,
>
> Best regards,
>
> Xiang
>
> The contents of this communication, including any attachments, may be confidential, privileged or otherwise protected from disclosure. They are intended solely for the use of the individual or entity to whom they are addressed. If you are not the intended recipient, please do not read, copy, use or disclose the contents of this communication. Please notify the sender immediately and delete the communication in its entirety.
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Xiang,
There is a rather elegant time-dependent residual error model described by
Phylinda Chan et al in:
BJCP, 2008;65(S1):76-85.
BW,
Joe
_____
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Yu, Xiang-Qing
Sent: den 22 september 2009 20:52
To: [email protected]
Subject: [NMusers] time-dependent residual error models
Can anyone share NONMEM code of time-dependent residual error models with
me?
Many thanks in advance,
Best regards,
Xiang
The contents of this communication, including any attachments, may be
confidential, privileged or otherwise protected from disclosure. They are
intended solely for the use of the individual or entity to whom they are
addressed. If you are not the intended recipient, please do not read, copy,
use or disclose the contents of this communication. Please notify the sender
immediately and delete the communication in its entirety.
Hi,
If Phylinda reads this I'd be interested to hear why she choose to use a plain vanilla first-order absorption model and a fancy time-dependent residual error model rather than trying to model a fancy absorption process with a plain vanilla residual error model?
Nick
Joseph Standing wrote:
> Xiang,
>
> There is a rather elegant time-dependent residual error model described by Phylinda Chan et al in:
>
> BJCP, 2008;65(S1):76-85.
>
> BW,
>
> Joe
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick,
I can't answer for Phylinda, but the general idea is to build the most
appropriate structural model that is supported by data. However, after that
is done, if there still is variation in residual error magnitude one should
take that into account and not ignore it. All models are wrong, and I would
say that in general our models for absorption are more wrong than our models
for disposition. That is not just because we have focused more on the
latter, but because the underlying processes governing absorption are of a
different nature (e.g. with discrete events like food intake, gastric
emptying, bile release and formulation disintegration and movement). Further
often part of the error magnitude is from timing errors. Such errors are
more pronounced when concentrations are changing fast (normally fastest
changes in absorption phase). We wrote on time-varying residual errors (and
alternatives such as residual error magnitude related to rate of change) in
these publications:
J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
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
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]] On
Behalf Of Nick Holford
Sent: Thursday, September 24, 2009 7:46 AM
To: nmusers
Subject: Re: [NMusers] time-dependent residual error models
Hi,
If Phylinda reads this I'd be interested to hear why she choose to use a
plain vanilla first-order absorption model and a fancy time-dependent
residual error model rather than trying to model a fancy absorption
process with a plain vanilla residual error model?
Nick
Joseph Standing wrote:
>
> Xiang,
>
>
>
> There is a rather elegant time-dependent residual error model
> described by Phylinda Chan et al in:
>
> BJCP, 2008;65(S1):76-85.
>
>
>
> BW,
>
> Joe
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick (and all),
A challenge has been issued and I must respond <grin>. I agree rate of
absorption is often not particularly important (we're usually more
interested in extent) - unless, of course, you're looking to maintain a
concentration above a certain threshold for a period of time, as is the
case with minimum inhibitory concentrations for tuberculosis chemotherapy,
for example. Here, rate of absorption can mean the difference between
killing an infectious organism or merely making it mildly uncomfortable.
The same would apply to any kind of irreversible dose-response.
Best
Justin
Justin Wilkins, PhD
Senior Modeler
Modeling & Simulation (Pharmacology)
CHBS, WSJ-027.6.076
Novartis Pharma AG
Lichtstrasse 35
CH-4056 Basel
Switzerland
Phone: +41 61 324 6549
Fax: +41 61 324 1246
Cell: +41 76 561 0949
Email : justin.wilkins
Nick Holford <n.holford
Sent by: owner-nmusers
24/09/2009 10:07
To
nmusers <nmusers
cc
Subject
Re: [NMusers] time-dependent residual error models
Mats,
I agree with your general idea but in this particular case there is no
description in the paper of efforts made to test structural models for
absorption apart from first order input with dose and food effects on
Ka. There seems to be quite a lot of time related structure in the
residual error model function that Phylinda reported and I would have
thought that at least some of this could have been explored via another
structural model e.g. involving parallel or sequential zero-order
inputs. It struck me as a rather unusual approach and I wondered what
the reasons for it were.
It does not really bother me which approach is used when describing
absorption (fancy structure+vanilla residual or vanilla structure+fancy
residual) because the details of the rate of absorption rarely have any
clinical relevance (Justin Wilkins may want to disagree <grin>). Of
course, as you point out the errors may often arise from poorly
reproducible fixed effects such as timing errors etc. and thus the goal
may be to describe the error adequately and not the structure because
the structure is not really fixed or of any interest.
Nick
Mats Karlsson wrote:
> Hi Nick,
>
> I can't answer for Phylinda, but the general idea is to build the most
> appropriate structural model that is supported by data. However, after
that
> is done, if there still is variation in residual error magnitude one
should
> take that into account and not ignore it. All models are wrong, and I
would
> say that in general our models for absorption are more wrong than our
models
> for disposition. That is not just because we have focused more on the
> latter, but because the underlying processes governing absorption are of
a
> different nature (e.g. with discrete events like food intake, gastric
> emptying, bile release and formulation disintegration and movement).
Further
> often part of the error magnitude is from timing errors. Such errors are
> more pronounced when concentrations are changing fast (normally fastest
> changes in absorption phase). We wrote on time-varying residual errors
(and
> alternatives such as residual error magnitude related to rate of change)
in
> these publications:
> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>
> 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
>
>
Quoted reply history
> -----Original Message-----
> From: owner-nmusers
On
> Behalf Of Nick Holford
> Sent: Thursday, September 24, 2009 7:46 AM
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Hi,
>
> If Phylinda reads this I'd be interested to hear why she choose to use a
> plain vanilla first-order absorption model and a fancy time-dependent
> residual error model rather than trying to model a fancy absorption
> process with a plain vanilla residual error model?
>
> Nick
>
> Joseph Standing wrote:
>
>> Xiang,
>>
>>
>>
>> There is a rather elegant time-dependent residual error model
>> described by Phylinda Chan et al in:
>>
>> BJCP, 2008;65(S1):76-85.
>>
>>
>>
>> BW,
>>
>> Joe
>>
>>
>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
n.holford
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick (and all),
A challenge has been issued and I must respond <grin>. I agree rate of
absorption is often not particularly important (we're usually more
interested in extent) - unless, of course, you're looking to maintain a
concentration above a certain threshold for a period of time, as is the
case with minimum inhibitory concentrations for tuberculosis chemotherapy,
for example. Here, rate of absorption can mean the difference between
killing an infectious organism or merely making it mildly uncomfortable.
The same would apply to any kind of irreversible dose-response.
Best
Justin
Justin Wilkins, PhD
Senior Modeler
Modeling & Simulation (Pharmacology)
CHBS, WSJ-027.6.076
Novartis Pharma AG
Lichtstrasse 35
CH-4056 Basel
Switzerland
Phone: +41 61 324 6549
Fax: +41 61 324 1246
Cell: +41 76 561 0949
Email : [email protected]
Nick Holford <[email protected]>
Sent by: [email protected]
24/09/2009 10:07
To
nmusers <[email protected]>
cc
Subject
Re: [NMusers] time-dependent residual error models
Mats,
I agree with your general idea but in this particular case there is no
description in the paper of efforts made to test structural models for
absorption apart from first order input with dose and food effects on
Ka. There seems to be quite a lot of time related structure in the
residual error model function that Phylinda reported and I would have
thought that at least some of this could have been explored via another
structural model e.g. involving parallel or sequential zero-order
inputs. It struck me as a rather unusual approach and I wondered what
the reasons for it were.
It does not really bother me which approach is used when describing
absorption (fancy structure+vanilla residual or vanilla structure+fancy
residual) because the details of the rate of absorption rarely have any
clinical relevance (Justin Wilkins may want to disagree <grin>). Of
course, as you point out the errors may often arise from poorly
reproducible fixed effects such as timing errors etc. and thus the goal
may be to describe the error adequately and not the structure because
the structure is not really fixed or of any interest.
Nick
Mats Karlsson wrote:
> Hi Nick,
>
> I can't answer for Phylinda, but the general idea is to build the most
> appropriate structural model that is supported by data. However, after
that
> is done, if there still is variation in residual error magnitude one
should
> take that into account and not ignore it. All models are wrong, and I
would
> say that in general our models for absorption are more wrong than our
models
> for disposition. That is not just because we have focused more on the
> latter, but because the underlying processes governing absorption are of
a
> different nature (e.g. with discrete events like food intake, gastric
> emptying, bile release and formulation disintegration and movement).
Further
> often part of the error magnitude is from timing errors. Such errors are
> more pronounced when concentrations are changing fast (normally fastest
> changes in absorption phase). We wrote on time-varying residual errors
(and
> alternatives such as residual error magnitude related to rate of change)
in
> these publications:
> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>
> 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
>
>
Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
On
> Behalf Of Nick Holford
> Sent: Thursday, September 24, 2009 7:46 AM
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Hi,
>
> If Phylinda reads this I'd be interested to hear why she choose to use a
> plain vanilla first-order absorption model and a fancy time-dependent
> residual error model rather than trying to model a fancy absorption
> process with a plain vanilla residual error model?
>
> Nick
>
> Joseph Standing wrote:
>
>> Xiang,
>>
>>
>>
>> There is a rather elegant time-dependent residual error model
>> described by Phylinda Chan et al in:
>>
>> BJCP, 2008;65(S1):76-85.
>>
>>
>>
>> BW,
>>
>> Joe
>>
>>
>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick,
Being a substrate of P-gp and CYP3A4, the compound itself has a very
complex absorption profile including dose non-linearity, double peaks,
food effects as well as high between individual and within individual
variability. Barry Weatherley has spent a substantial amount of time
and effort in understanding the dose non-linearity and some covariate
effects on the PK of this compound, including development of a very
complex flexible input model which was presented at PKUK in 2004. More
details of some of this modelling work can be found in a recent
publication.
http://www3.interscience.wiley.com/journal/122386172/abstract
The main objective of the meta-analysis was to develop a compartmental
model which would be useful in identifying significant covariates
explaining inter-individual variability and was simple enough to be used
in the later modelling of sparsely sampled PK in phase 2b/3 studies
where a full time profile and samples were likely to be clustered in the
elimination phase of the PK. We felt the first-order input with dose
and food effects on Ka in addition to the time-dependent residual error
model was adequate for this purpose.
For those who interested in the coding of the time-dependent residual
error model:
$ERROR
IPRED = F+.00001
LPRED = 0
IF(IPRED.GT.0) LPRED = LOG(IPRED)
PMAX=THETA(7)
TMAX=THETA(8)
K=THETA(9)
BASE=THETA(10)
P=K*TMAX
A=EXP(P)/TMAX**P
W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
IRES= DV-LPRED
IWRES= IRES/W
Y= LPRED+EPS(1) * W
Note:
i) $SIGMA (1 FIX)
ii) TAD=time after dose
Phylinda.
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]]
On Behalf Of Nick Holford
Sent: 24 September 2009 08:42
To: nmusers
Subject: Re: [NMusers] time-dependent residual error models
Mats,
I agree with your general idea but in this particular case there is no
description in the paper of efforts made to test structural models for
absorption apart from first order input with dose and food effects on
Ka. There seems to be quite a lot of time related structure in the
residual error model function that Phylinda reported and I would have
thought that at least some of this could have been explored via another
structural model e.g. involving parallel or sequential zero-order
inputs. It struck me as a rather unusual approach and I wondered what
the reasons for it were.
It does not really bother me which approach is used when describing
absorption (fancy structure+vanilla residual or vanilla structure+fancy
residual) because the details of the rate of absorption rarely have any
clinical relevance (Justin Wilkins may want to disagree <grin>). Of
course, as you point out the errors may often arise from poorly
reproducible fixed effects such as timing errors etc. and thus the goal
may be to describe the error adequately and not the structure because
the structure is not really fixed or of any interest.
Nick
Mats Karlsson wrote:
> Hi Nick,
>
> I can't answer for Phylinda, but the general idea is to build the most
> appropriate structural model that is supported by data. However, after
that
> is done, if there still is variation in residual error magnitude one
should
> take that into account and not ignore it. All models are wrong, and I
would
> say that in general our models for absorption are more wrong than our
models
> for disposition. That is not just because we have focused more on the
> latter, but because the underlying processes governing absorption are
of a
> different nature (e.g. with discrete events like food intake, gastric
> emptying, bile release and formulation disintegration and movement).
Further
> often part of the error magnitude is from timing errors. Such errors
are
> more pronounced when concentrations are changing fast (normally
fastest
> changes in absorption phase). We wrote on time-varying residual errors
(and
> alternatives such as residual error magnitude related to rate of
change) in
> these publications:
> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>
> 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
>
>
> -----Original Message-----
> From: [email protected]
[mailto:[email protected]] On
> Behalf Of Nick Holford
> Sent: Thursday, September 24, 2009 7:46 AM
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Hi,
>
> If Phylinda reads this I'd be interested to hear why she choose to use
a
> plain vanilla first-order absorption model and a fancy time-dependent
> residual error model rather than trying to model a fancy absorption
> process with a plain vanilla residual error model?
>
> Nick
>
> Joseph Standing wrote:
>
>> Xiang,
>>
>>
>>
>> There is a rather elegant time-dependent residual error model
>> described by Phylinda Chan et al in:
>>
>> BJCP, 2008;65(S1):76-85.
>>
>>
>>
>> BW,
>>
>> Joe
>>
>>
>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Phylinda,
Thanks for the explanation -- it seems that the more usual approach of
complex structure+simple residual error model had already been done by
Barry Weatherley.
Your simple structure+complex residual error is an interesting
alternative but apart from your feelings ("We felt ...") was there any
reason not to use Barry's structural model?
Nick
Chan, Phylinda wrote:
> Hi Nick,
>
> Being a substrate of P-gp and CYP3A4, the compound itself has a very
> complex absorption profile including dose non-linearity, double peaks,
> food effects as well as high between individual and within individual
> variability. Barry Weatherley has spent a substantial amount of time
> and effort in understanding the dose non-linearity and some covariate
> effects on the PK of this compound, including development of a very
> complex flexible input model which was presented at PKUK in 2004. More
> details of some of this modelling work can be found in a recent
> publication.
>
> http://www3.interscience.wiley.com/journal/122386172/abstract
>
>
> The main objective of the meta-analysis was to develop a compartmental
> model which would be useful in identifying significant covariates
> explaining inter-individual variability and was simple enough to be used
> in the later modelling of sparsely sampled PK in phase 2b/3 studies
> where a full time profile and samples were likely to be clustered in the
> elimination phase of the PK. We felt the first-order input with dose
> and food effects on Ka in addition to the time-dependent residual error
> model was adequate for this purpose.
>
>
> For those who interested in the coding of the time-dependent residual
> error model:
> $ERROR
> IPRED = F+.00001
> LPRED = 0
> IF(IPRED.GT.0) LPRED = LOG(IPRED)
>
> PMAX=THETA(7)
> TMAX=THETA(8)
> K=THETA(9)
> BASE=THETA(10)
>
> P=K*TMAX
> A=EXP(P)/TMAX**P
>
> W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> IRES= DV-LPRED
> IWRES= IRES/W
> Y= LPRED+EPS(1) * W
>
> Note:
> i) $SIGMA (1 FIX)
> ii) TAD=time after dose
>
> Phylinda.
>
>
Quoted reply history
> -----Original Message-----
> From: owner-nmusers
> On Behalf Of Nick Holford
> Sent: 24 September 2009 08:42
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Mats,
>
> I agree with your general idea but in this particular case there is no
> description in the paper of efforts made to test structural models for
> absorption apart from first order input with dose and food effects on
> Ka. There seems to be quite a lot of time related structure in the
> residual error model function that Phylinda reported and I would have
> thought that at least some of this could have been explored via another
> structural model e.g. involving parallel or sequential zero-order
> inputs. It struck me as a rather unusual approach and I wondered what
> the reasons for it were.
>
> It does not really bother me which approach is used when describing
> absorption (fancy structure+vanilla residual or vanilla structure+fancy
> residual) because the details of the rate of absorption rarely have any
> clinical relevance (Justin Wilkins may want to disagree <grin>). Of
> course, as you point out the errors may often arise from poorly
> reproducible fixed effects such as timing errors etc. and thus the goal
> may be to describe the error adequately and not the structure because
> the structure is not really fixed or of any interest.
>
> Nick
>
>
> Mats Karlsson wrote:
>
>> Hi Nick,
>>
>> I can't answer for Phylinda, but the general idea is to build the most
>> appropriate structural model that is supported by data. However, after
>>
> that
>
>> is done, if there still is variation in residual error magnitude one
>>
> should
>
>> take that into account and not ignore it. All models are wrong, and I
>>
> would
>
>> say that in general our models for absorption are more wrong than our
>>
> models
>
>> for disposition. That is not just because we have focused more on the
>> latter, but because the underlying processes governing absorption are
>>
> of a
>
>> different nature (e.g. with discrete events like food intake, gastric
>> emptying, bile release and formulation disintegration and movement).
>>
> Further
>
>> often part of the error magnitude is from timing errors. Such errors
>>
> are
>
>> more pronounced when concentrations are changing fast (normally
>>
> fastest
>
>> changes in absorption phase). We wrote on time-varying residual errors
>>
> (and
>
>> alternatives such as residual error magnitude related to rate of
>>
> change) in
>
>> these publications:
>> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
>> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>>
>> 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
>>
>>
>> -----Original Message-----
>> From: owner-nmusers
>>
> [mailto:owner-nmusers
>
>> Behalf Of Nick Holford
>> Sent: Thursday, September 24, 2009 7:46 AM
>> To: nmusers
>> Subject: Re: [NMusers] time-dependent residual error models
>>
>> Hi,
>>
>> If Phylinda reads this I'd be interested to hear why she choose to use
>>
> a
>
>> plain vanilla first-order absorption model and a fancy time-dependent
>> residual error model rather than trying to model a fancy absorption
>> process with a plain vanilla residual error model?
>>
>> Nick
>>
>> Joseph Standing wrote:
>>
>>
>>> Xiang,
>>>
>>>
>>>
>>> There is a rather elegant time-dependent residual error model
>>> described by Phylinda Chan et al in:
>>>
>>> BJCP, 2008;65(S1):76-85.
>>>
>>>
>>>
>>> BW,
>>>
>>> Joe
>>>
>>>
>>>
>>
>>
>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Phylinda,
Thanks for the explanation -- it seems that the more usual approach of complex structure+simple residual error model had already been done by Barry Weatherley. Your simple structure+complex residual error is an interesting alternative but apart from your feelings ("We felt ...") was there any reason not to use Barry's structural model?
Nick
Chan, Phylinda wrote:
> Hi Nick,
>
> Being a substrate of P-gp and CYP3A4, the compound itself has a very
> complex absorption profile including dose non-linearity, double peaks,
> food effects as well as high between individual and within individual
> variability. Barry Weatherley has spent a substantial amount of time
> and effort in understanding the dose non-linearity and some covariate
> effects on the PK of this compound, including development of a very
> complex flexible input model which was presented at PKUK in 2004. More
> details of some of this modelling work can be found in a recent
>
> publication.
>
> http://www3.interscience.wiley.com/journal/122386172/abstract
>
> The main objective of the meta-analysis was to develop a compartmental
> model which would be useful in identifying significant covariates
> explaining inter-individual variability and was simple enough to be used
> in the later modelling of sparsely sampled PK in phase 2b/3 studies
> where a full time profile and samples were likely to be clustered in the
> elimination phase of the PK. We felt the first-order input with dose
> and food effects on Ka in addition to the time-dependent residual error
> model was adequate for this purpose.
>
> For those who interested in the coding of the time-dependent residual
>
> error model: $ERROR
>
> IPRED = F+.00001
> LPRED = 0
> IF(IPRED.GT.0) LPRED = LOG(IPRED)
>
> PMAX=THETA(7) TMAX=THETA(8) K=THETA(9)
>
> BASE=THETA(10)
>
> P=K*TMAX A=EXP(P)/TMAX**P
>
> W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> IRES= DV-LPRED
> IWRES= IRES/W
> Y= LPRED+EPS(1) * W
>
> Note:
> i) $SIGMA (1 FIX)
> ii) TAD=time after dose
>
> Phylinda.
>
Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
> On Behalf Of Nick Holford
> Sent: 24 September 2009 08:42
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Mats,
>
> I agree with your general idea but in this particular case there is no description in the paper of efforts made to test structural models for absorption apart from first order input with dose and food effects on Ka. There seems to be quite a lot of time related structure in the residual error model function that Phylinda reported and I would have thought that at least some of this could have been explored via another structural model e.g. involving parallel or sequential zero-order inputs. It struck me as a rather unusual approach and I wondered what the reasons for it were.
>
> It does not really bother me which approach is used when describing absorption (fancy structure+vanilla residual or vanilla structure+fancy residual) because the details of the rate of absorption rarely have any clinical relevance (Justin Wilkins may want to disagree <grin>). Of course, as you point out the errors may often arise from poorly reproducible fixed effects such as timing errors etc. and thus the goal may be to describe the error adequately and not the structure because the structure is not really fixed or of any interest.
>
> Nick
>
> Mats Karlsson wrote:
>
> > Hi Nick,
> >
> > I can't answer for Phylinda, but the general idea is to build the most
> > appropriate structural model that is supported by data. However, after
>
> that
>
> > is done, if there still is variation in residual error magnitude one
>
> should
>
> > take that into account and not ignore it. All models are wrong, and I
>
> would
>
> > say that in general our models for absorption are more wrong than our
>
> models
>
> > for disposition. That is not just because we have focused more on the
> > latter, but because the underlying processes governing absorption are
>
> of a
>
> > different nature (e.g. with discrete events like food intake, gastric
> > emptying, bile release and formulation disintegration and movement).
>
> Further
>
> > often part of the error magnitude is from timing errors. Such errors
>
> are
>
> > more pronounced when concentrations are changing fast (normally
>
> fastest
>
> > changes in absorption phase). We wrote on time-varying residual errors
>
> (and
>
> > alternatives such as residual error magnitude related to rate of
>
> change) in
>
> > these publications: J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> >
> > J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
> >
> > 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
> >
> > -----Original Message-----
> > From: [email protected]
>
> [mailto:[email protected]] On
>
> > Behalf Of Nick Holford
> > Sent: Thursday, September 24, 2009 7:46 AM
> > To: nmusers
> > Subject: Re: [NMusers] time-dependent residual error models
> >
> > Hi,
> >
> > If Phylinda reads this I'd be interested to hear why she choose to use
>
> a
>
> > plain vanilla first-order absorption model and a fancy time-dependent residual error model rather than trying to model a fancy absorption process with a plain vanilla residual error model?
> >
> > Nick
> >
> > Joseph Standing wrote:
> >
> > > Xiang,
> > >
> > > There is a rather elegant time-dependent residual error model described by Phylinda Chan et al in:
> > >
> > > BJCP, 2008;65(S1):76-85.
> > >
> > > BW,
> > >
> > > Joe
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick,
There are 97 thetas and 87 omegas in the complex flexible input model.
Despite of the run time, it is impractical to apply such model for
covariates searching in the meta-analysis.
Phylinda.
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]]
On Behalf Of Nick Holford
Sent: 30 September 2009 04:31
To: nmusers
Subject: Re: [NMusers] time-dependent residual error models
Phylinda,
Thanks for the explanation -- it seems that the more usual approach of
complex structure+simple residual error model had already been done by
Barry Weatherley.
Your simple structure+complex residual error is an interesting
alternative but apart from your feelings ("We felt ...") was there any
reason not to use Barry's structural model?
Nick
Chan, Phylinda wrote:
> Hi Nick,
>
> Being a substrate of P-gp and CYP3A4, the compound itself has a very
> complex absorption profile including dose non-linearity, double peaks,
> food effects as well as high between individual and within individual
> variability. Barry Weatherley has spent a substantial amount of time
> and effort in understanding the dose non-linearity and some covariate
> effects on the PK of this compound, including development of a very
> complex flexible input model which was presented at PKUK in 2004.
More
> details of some of this modelling work can be found in a recent
> publication.
>
> http://www3.interscience.wiley.com/journal/122386172/abstract
>
>
> The main objective of the meta-analysis was to develop a compartmental
> model which would be useful in identifying significant covariates
> explaining inter-individual variability and was simple enough to be
used
> in the later modelling of sparsely sampled PK in phase 2b/3 studies
> where a full time profile and samples were likely to be clustered in
the
> elimination phase of the PK. We felt the first-order input with dose
> and food effects on Ka in addition to the time-dependent residual
error
> model was adequate for this purpose.
>
>
> For those who interested in the coding of the time-dependent residual
> error model:
> $ERROR
> IPRED = F+.00001
> LPRED = 0
> IF(IPRED.GT.0) LPRED = LOG(IPRED)
>
> PMAX=THETA(7)
> TMAX=THETA(8)
> K=THETA(9)
> BASE=THETA(10)
>
> P=K*TMAX
> A=EXP(P)/TMAX**P
>
> W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> IRES= DV-LPRED
> IWRES= IRES/W
> Y= LPRED+EPS(1) * W
>
> Note:
> i) $SIGMA (1 FIX)
> ii) TAD=time after dose
>
> Phylinda.
>
>
> -----Original Message-----
> From: [email protected]
[mailto:[email protected]]
> On Behalf Of Nick Holford
> Sent: 24 September 2009 08:42
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Mats,
>
> I agree with your general idea but in this particular case there is no
> description in the paper of efforts made to test structural models for
> absorption apart from first order input with dose and food effects on
> Ka. There seems to be quite a lot of time related structure in the
> residual error model function that Phylinda reported and I would have
> thought that at least some of this could have been explored via
another
> structural model e.g. involving parallel or sequential zero-order
> inputs. It struck me as a rather unusual approach and I wondered what
> the reasons for it were.
>
> It does not really bother me which approach is used when describing
> absorption (fancy structure+vanilla residual or vanilla
structure+fancy
> residual) because the details of the rate of absorption rarely have
any
> clinical relevance (Justin Wilkins may want to disagree <grin>). Of
> course, as you point out the errors may often arise from poorly
> reproducible fixed effects such as timing errors etc. and thus the
goal
> may be to describe the error adequately and not the structure because
> the structure is not really fixed or of any interest.
>
> Nick
>
>
> Mats Karlsson wrote:
>
>> Hi Nick,
>>
>> I can't answer for Phylinda, but the general idea is to build the
most
>> appropriate structural model that is supported by data. However,
after
>>
> that
>
>> is done, if there still is variation in residual error magnitude one
>>
> should
>
>> take that into account and not ignore it. All models are wrong, and I
>>
> would
>
>> say that in general our models for absorption are more wrong than our
>>
> models
>
>> for disposition. That is not just because we have focused more on the
>> latter, but because the underlying processes governing absorption are
>>
> of a
>
>> different nature (e.g. with discrete events like food intake, gastric
>> emptying, bile release and formulation disintegration and movement).
>>
> Further
>
>> often part of the error magnitude is from timing errors. Such errors
>>
> are
>
>> more pronounced when concentrations are changing fast (normally
>>
> fastest
>
>> changes in absorption phase). We wrote on time-varying residual
errors
>>
> (and
>
>> alternatives such as residual error magnitude related to rate of
>>
> change) in
>
>> these publications:
>> J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
>> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>>
>> 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
>>
>>
>> -----Original Message-----
>> From: [email protected]
>>
> [mailto:[email protected]] On
>
>> Behalf Of Nick Holford
>> Sent: Thursday, September 24, 2009 7:46 AM
>> To: nmusers
>> Subject: Re: [NMusers] time-dependent residual error models
>>
>> Hi,
>>
>> If Phylinda reads this I'd be interested to hear why she choose to
use
>>
> a
>
>> plain vanilla first-order absorption model and a fancy time-dependent
>> residual error model rather than trying to model a fancy absorption
>> process with a plain vanilla residual error model?
>>
>> Nick
>>
>> Joseph Standing wrote:
>>
>>
>>> Xiang,
>>>
>>>
>>>
>>> There is a rather elegant time-dependent residual error model
>>> described by Phylinda Chan et al in:
>>>
>>> BJCP, 2008;65(S1):76-85.
>>>
>>>
>>>
>>> BW,
>>>
>>> Joe
>>>
>>>
>>>
>>
>>
>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Phylinda,
Thanks for the explanation about the impracticability of using the 'complex flexible input' model. However, I would have thought the problem was not the run time but the upper limit on number of THETAs of 70 and on OMEGA+SIGMA of 70 in NONMEM (still there in NONMEM 7!).
"/III.2.9.1. Changing the Number of Theta’s, Eta’s, and Epsilon’s
LTH gives the maximum number of theta’s allowable. It must be between 1 and 70. LVR gives the maximum number of eta’s plus epsilon’s allowable. It must be between 1 and 70/" NONMEM VI User Guide III
Where would you get the ultra-big NONMEM version with 97 THETAs and 87 OMEGAs?
Nick
Chan, Phylinda wrote:
> Hi Nick,
>
> There are 97 thetas and 87 omegas in the complex flexible input model.
> Despite of the run time, it is impractical to apply such model for
> covariates searching in the meta-analysis.
>
> Phylinda.
>
Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
> On Behalf Of Nick Holford
> Sent: 30 September 2009 04:31
> To: nmusers
> Subject: Re: [NMusers] time-dependent residual error models
>
> Phylinda,
>
> Thanks for the explanation -- it seems that the more usual approach of complex structure+simple residual error model had already been done by Barry Weatherley. Your simple structure+complex residual error is an interesting alternative but apart from your feelings ("We felt ...") was there any reason not to use Barry's structural model?
>
> Nick
>
> Chan, Phylinda wrote:
>
> > Hi Nick,
> >
> > Being a substrate of P-gp and CYP3A4, the compound itself has a very
> > complex absorption profile including dose non-linearity, double peaks,
> > food effects as well as high between individual and within individual
> > variability. Barry Weatherley has spent a substantial amount of time
> > and effort in understanding the dose non-linearity and some covariate
> > effects on the PK of this compound, including development of a very
> > complex flexible input model which was presented at PKUK in 2004.
>
> More
>
> > details of some of this modelling work can be found in a recent
> >
> > publication.
> >
> > http://www3.interscience.wiley.com/journal/122386172/abstract
> >
> > The main objective of the meta-analysis was to develop a compartmental
> > model which would be useful in identifying significant covariates
> > explaining inter-individual variability and was simple enough to be
>
> used
>
> > in the later modelling of sparsely sampled PK in phase 2b/3 studies
> > where a full time profile and samples were likely to be clustered in
>
> the
>
> > elimination phase of the PK. We felt the first-order input with dose
> > and food effects on Ka in addition to the time-dependent residual
>
> error
>
> > model was adequate for this purpose.
> >
> > For those who interested in the coding of the time-dependent residual
> >
> > error model: $ERROR
> >
> > IPRED = F+.00001
> > LPRED = 0
> > IF(IPRED.GT.0) LPRED = LOG(IPRED)
> >
> > PMAX=THETA(7) TMAX=THETA(8) K=THETA(9)
> >
> > BASE=THETA(10)
> >
> > P=K*TMAX A=EXP(P)/TMAX**P
> >
> > W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> > IRES= DV-LPRED
> > IWRES= IRES/W
> > Y= LPRED+EPS(1) * W
> >
> > Note:
> > i) $SIGMA (1 FIX)
> > ii) TAD=time after dose
> >
> > Phylinda.
> >
> > -----Original Message-----
> > From: [email protected]
>
> [mailto:[email protected]]
>
> > On Behalf Of Nick Holford
> > Sent: 24 September 2009 08:42
> > To: nmusers
> > Subject: Re: [NMusers] time-dependent residual error models
> >
> > Mats,
> >
> > I agree with your general idea but in this particular case there is no
>
> > description in the paper of efforts made to test structural models for
>
> > absorption apart from first order input with dose and food effects on Ka. There seems to be quite a lot of time related structure in the residual error model function that Phylinda reported and I would have thought that at least some of this could have been explored via
>
> another
>
> > structural model e.g. involving parallel or sequential zero-order inputs. It struck me as a rather unusual approach and I wondered what the reasons for it were.
> >
> > It does not really bother me which approach is used when describing absorption (fancy structure+vanilla residual or vanilla
>
> structure+fancy
>
> > residual) because the details of the rate of absorption rarely have
>
> any
>
> > clinical relevance (Justin Wilkins may want to disagree <grin>). Of course, as you point out the errors may often arise from poorly reproducible fixed effects such as timing errors etc. and thus the
>
> goal
>
> > may be to describe the error adequately and not the structure because the structure is not really fixed or of any interest.
> >
> > Nick
> >
> > Mats Karlsson wrote:
> >
> > > Hi Nick,
> > >
> > > I can't answer for Phylinda, but the general idea is to build the
>
> most
>
> > > appropriate structural model that is supported by data. However,
>
> after
>
> > that
> >
> > > is done, if there still is variation in residual error magnitude one
> >
> > should
> >
> > > take that into account and not ignore it. All models are wrong, and I
> >
> > would
> >
> > > say that in general our models for absorption are more wrong than our
> >
> > models
> >
> > > for disposition. That is not just because we have focused more on the
> > > latter, but because the underlying processes governing absorption are
> >
> > of a
> >
> > > different nature (e.g. with discrete events like food intake, gastric
> > > emptying, bile release and formulation disintegration and movement).
> >
> > Further
> >
> > > often part of the error magnitude is from timing errors. Such errors
> >
> > are
> >
> > > more pronounced when concentrations are changing fast (normally
> >
> > fastest
> >
> > > changes in absorption phase). We wrote on time-varying residual
>
> errors
>
> > (and
> >
> > > alternatives such as residual error magnitude related to rate of
> >
> > change) in
> >
> > > these publications: J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> > >
> > > J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
> > >
> > > 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
> > >
> > > -----Original Message-----
> > > From: [email protected]
> >
> > [mailto:[email protected]] On
> >
> > > Behalf Of Nick Holford
> > > Sent: Thursday, September 24, 2009 7:46 AM
> > > To: nmusers
> > > Subject: Re: [NMusers] time-dependent residual error models
> > >
> > > Hi,
> > >
> > > If Phylinda reads this I'd be interested to hear why she choose to
>
> use
>
> > a
> >
> > > plain vanilla first-order absorption model and a fancy time-dependent
>
> > > residual error model rather than trying to model a fancy absorption process with a plain vanilla residual error model?
> > >
> > > Nick
> > >
> > > Joseph Standing wrote:
> > >
> > > > Xiang,
> > > >
> > > > There is a rather elegant time-dependent residual error model described by Phylinda Chan et al in:
> > > >
> > > > BJCP, 2008;65(S1):76-85.
> > > >
> > > > BW,
> > > >
> > > > Joe
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Nick, only occasionally it is worth while to forget to read the manual!
In this instance (using NONMEM V, not tried for NONMEM 6), I needed more than the allotted ration of THETAs and ETAs. I had to increase the variables within *SIZES to allocate bigger LTH, LVR etc. Bill Bachman gave me a spreadsheet to get the exact sizes of all the array variables.
The only problem was that the output file could not count the THETAs and ETAs beyond 70 for labelling them. So above this number the labels for THETAs and ETAs were hieroglyphics but the values were fine.
Barry
In message < [email protected] >, Nick Holford < [email protected] > writes
> Phylinda,
>
> Thanks for the explanation about the impracticability of using the 'complex flexible input' model. However, I would have thought the problem was not the run time but the upper limit on number of THETAs of 70 and on OMEGA+SIGMA of 70 in NONMEM (still there in NONMEM 7!).
>
> "/III.2.9.1. Changing the Number of Theta’s, Eta’s, and Epsilon’s
>
> LTH gives the maximum number of theta’s allowable. It must be between 1 and 70. LVR gives the maximum number of eta’s plus epsilon’s allowable. It must be between 1 and 70/" NONMEM VI User Guide III
>
> Where would you get the ultra-big NONMEM version with 97 THETAs and 87 OMEGAs?
>
> Nick
>
> Chan, Phylinda wrote:
>
> > Hi Nick,
> >
> > There are 97 thetas and 87 omegas in the complex flexible input model.
> > Despite of the run time, it is impractical to apply such model for
> > covariates searching in the meta-analysis.
> >
> > Phylinda.
> >
> > -----Original Message-----
Quoted reply history
> > From: [email protected] [mailto:[email protected]]
> > On Behalf Of Nick Holford
> > Sent: 30 September 2009 04:31
> > To: nmusers
> > Subject: Re: [NMusers] time-dependent residual error models
> >
> > Phylinda,
> >
> > Thanks for the explanation -- it seems that the more usual approach of complex structure+simple residual error model had already been done by Barry Weatherley. Your simple structure+complex residual error is an interesting alternative but apart from your feelings ("We felt ...") was there any reason not to use Barry's structural model?
> >
> > Nick
> >
> > Chan, Phylinda wrote:
> >
> > > Hi Nick,
> > >
> > > Being a substrate of P-gp and CYP3A4, the compound itself has a very
> > > complex absorption profile including dose non-linearity, double peaks,
> > > food effects as well as high between individual and within individual
> > > variability. Barry Weatherley has spent a substantial amount of time
> > > and effort in understanding the dose non-linearity and some covariate
> > > effects on the PK of this compound, including development of a very
> > > complex flexible input model which was presented at PKUK in 2004.
> >
> > More
> >
> > > details of some of this modelling work can be found in a recent
> > > publication.
> > > http://www3.interscience.wiley.com/journal/122386172/abstract
> > >
> > > The main objective of the meta-analysis was to develop a compartmental
> > > model which would be useful in identifying significant covariates
> > > explaining inter-individual variability and was simple enough to be
> >
> > used
> >
> > > in the later modelling of sparsely sampled PK in phase 2b/3 studies
> > > where a full time profile and samples were likely to be clustered in
> >
> > the
> >
> > > elimination phase of the PK. We felt the first-order input with dose
> > >
> > > and food effects on Ka in addition to the time-dependent residual
> >
> > error
> >
> > > model was adequate for this purpose.
> > >
> > > For those who interested in the coding of the time-dependent residual
> > > error model: $ERROR
> > > IPRED = F+.00001
> > > LPRED = 0
> > > IF(IPRED.GT.0) LPRED = LOG(IPRED)
> > >
> > > PMAX=THETA(7) TMAX=THETA(8) K=THETA(9)
> > > BASE=THETA(10)
> > >
> > > P=K*TMAX A=EXP(P)/TMAX**P
> > >
> > > W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> > > IRES= DV-LPRED
> > > IWRES= IRES/W
> > > Y= LPRED+EPS(1) * W
> > >
> > > Note:
> > > i) $SIGMA (1 FIX)
> > > ii) TAD=time after dose
> > >
> > > Phylinda.
> > >
> > > -----Original Message-----
> > > From: [email protected]
> >
> > [mailto:[email protected]]
> >
> > > On Behalf Of Nick Holford
> > > Sent: 24 September 2009 08:42
> > > To: nmusers
> > > Subject: Re: [NMusers] time-dependent residual error models
> > >
> > > Mats,
> > >
> > > I agree with your general idea but in this particular case there is no
> >
> > > description in the paper of efforts made to test structural models for
> >
> > > absorption apart from first order input with dose and food effects on Ka. There seems to be quite a lot of time related structure in the residual error model function that Phylinda reported and I would have thought that at least some of this could have been explored via
> >
> > another
> >
> > > structural model e.g. involving parallel or sequential zero-order inputs. It struck me as a rather unusual approach and I wondered what reasons for it were.
> > >
> > > It does not really bother me which approach is used when describing absorption (fancy structure+vanilla residual or vanilla
> >
> > structure+fancy
> >
> > > residual) because the details of the rate of absorption rarely have
> >
> > any
> >
> > > clinical relevance (Justin Wilkins may want to disagree <grin>). Of course, as you point out the errors may often arise from poorly reproducible fixed effects such as timing errors etc. and thus the
> >
> > goal
> >
> > > may be to describe the error adequately and not the structure because the structure is not really fixed or of any interest.
> > >
> > > Nick
> > >
> > > Mats Karlsson wrote:
> > >
> > > > Hi Nick,
> > > >
> > > > I can't answer for Phylinda, but the general idea is to build the
> >
> > most
> >
> > > > appropriate structural model that is supported by data. However,
> >
> > after
> >
> > > that
> > >
> > > > is done, if there still is variation in residual error magnitude
> > >
> > > should
> > >
> > > > take that into account and not ignore it. All models are wrong, and
> > >
> > > would
> > >
> > > > say that in general our models for absorption are more wrong than
> > >
> > > models
> > >
> > > > for disposition. That is not just because we have focused more on
> > > >
> > > > latter, but because the underlying processes governing absorption are
> > >
> > > of a
> > >
> > > > different nature (e.g. with discrete events like food intake, gastric
> > > >
> > > > emptying, bile release and formulation disintegration and movement).
> > >
> > > Further
> > >
> > > > often part of the error magnitude is from timing errors. Such errors
> > >
> > > are
> > >
> > > > more pronounced when concentrations are changing fast (normally
> > >
> > > fastest
> > >
> > > > changes in absorption phase). We wrote on time-varying residual
> >
> > errors
> >
> > > (and
> > >
> > > > alternatives such as residual error magnitude related to rate of
> > >
> > > change) in
> > >
> > > > these publications: J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> > > >
> > > > J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
> > > >
> > > > 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
> > > >
> > > > -----Original Message-----
> > > > From: [email protected]
> > >
> > > [mailto:[email protected]] On
> > >
> > > > Behalf Of Nick Holford
> > > > Sent: Thursday, September 24, 2009 7:46 AM
> > > > To: nmusers
> > > > Subject: Re: [NMusers] time-dependent residual error models
> > > >
> > > > Hi,
> > > >
> > > > If Phylinda reads this I'd be interested to hear why she choose to
> >
> > use
> >
> > > a
> > >
> > > > plain vanilla first-order absorption model and a fancy time-dependent
> >
> > > > residual error model rather than trying to model a fancy absorption process with a plain vanilla residual error model?
> > > >
> > > > Nick
> > > >
> > > > Joseph Standing wrote:
> > > >
> > > > > Xiang,
> > > > >
> > > > > There is a rather elegant time-dependent residual error model described by Phylinda Chan et al in:
> > > > >
> > > > > BJCP, 2008;65(S1):76-85.
> > > > >
> > > > > BW,
> > > > >
> > > > > Joe
Barry,
Thanks for this information. It is good to know that one can ignore this
limitation. I never understood why it was there - especially in NONMEM 7
which was supposed to be a complete rewrite with more flexible structure.
The inability to write out a label for THETA and ETA after 70 is just
one of those odd things about this program...
Nick
Barry Weatherley wrote:
> Nick, only occasionally it is worth while to forget to read the manual!
> In this instance (using NONMEM V, not tried for NONMEM 6), I needed
> more than the allotted ration of THETAs and ETAs. I had to increase
> the variables within *SIZES to allocate bigger LTH, LVR etc. Bill
> Bachman gave me a spreadsheet to get the exact sizes of all the array
> variables.
>
> The only problem was that the output file could not count the THETAs
> and ETAs beyond 70 for labelling them. So above this number the
> labels for THETAs and ETAs were hieroglyphics but the values were fine.
>
> Barry
>
>
> In message <4AC65A15.5050901
> <n.holford
>> Phylinda,
>>
>> Thanks for the explanation about the impracticability of using the
>> 'complex flexible input' model. However, I would have thought the
>> problem was not the run time but the upper limit on number of THETAs
>> of 70 and on OMEGA+SIGMA of 70 in NONMEM (still there in NONMEM 7!).
>>
>> "/III.2.9.1. Changing the Number of Theta’s, Eta’s, and Epsilon’s
>> LTH gives the maximum number of theta’s allowable. It must be between
>> 1 and 70.
>> LVR gives the maximum number of eta’s plus epsilon’s allowable. It
>> must be between 1 and 70/" NONMEM VI User Guide III
>>
>> Where would you get the ultra-big NONMEM version with 97 THETAs and
>> 87 OMEGAs?
>>
>> Nick
>>
>> Chan, Phylinda wrote:
>>> Hi Nick,
>>>
>>> There are 97 thetas and 87 omegas in the complex flexible input model.
>>> Despite of the run time, it is impractical to apply such model for
>>> covariates searching in the meta-analysis.
>>>
>>> Phylinda.
>>>
>>>
>>> -----Original Message-----
Quoted reply history
>>> From: owner-nmusers
>>> [mailto:owner-nmusers
>>> On Behalf Of Nick Holford
>>> Sent: 30 September 2009 04:31
>>> To: nmusers
>>> Subject: Re: [NMusers] time-dependent residual error models
>>>
>>> Phylinda,
>>>
>>> Thanks for the explanation -- it seems that the more usual approach
>>> of complex structure+simple residual error model had already been
>>> done by Barry Weatherley.
>>> Your simple structure+complex residual error is an interesting
>>> alternative but apart from your feelings ("We felt ...") was there
>>> any reason not to use Barry's structural model?
>>>
>>> Nick
>>>
>>> Chan, Phylinda wrote:
>>>
>>>> Hi Nick,
>>>>
>>>> Being a substrate of P-gp and CYP3A4, the compound itself has a very
>>>> complex absorption profile including dose non-linearity, double peaks,
>>>> food effects as well as high between individual and within individual
>>>> variability. Barry Weatherley has spent a substantial amount of time
>>>> and effort in understanding the dose non-linearity and some covariate
>>>> effects on the PK of this compound, including development of a very
>>>> complex flexible input model which was presented at PKUK in 2004.
>>>>
>>> More
>>>
>>>> details of some of this modelling work can be found in a recent
>>>> publication.
>>>> http://www3.interscience.wiley.com/journal/122386172/abstract
>>>>
>>>>
>>>> The main objective of the meta-analysis was to develop a compartmental
>>>> model which would be useful in identifying significant covariates
>>>> explaining inter-individual variability and was simple enough to be
>>>>
>>> used
>>>
>>>> in the later modelling of sparsely sampled PK in phase 2b/3 studies
>>>> where a full time profile and samples were likely to be clustered in
>>>>
>>> the
>>>
>>>> elimination phase of the PK. We felt the first-order input with dose
>>>> and food effects on Ka in addition to the time-dependent residual
>>>>
>>> error
>>>
>>>> model was adequate for this purpose.
>>>>
>>>>
>>>> For those who interested in the coding of the time-dependent residual
>>>> error model: $ERROR
>>>> IPRED = F+.00001
>>>> LPRED = 0
>>>> IF(IPRED.GT.0) LPRED = LOG(IPRED)
>>>>
>>>> PMAX=THETA(7) TMAX=THETA(8) K=THETA(9)
>>>> BASE=THETA(10)
>>>>
>>>> P=K*TMAX A=EXP(P)/TMAX**P
>>>>
>>>> W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
>>>> IRES= DV-LPRED
>>>> IWRES= IRES/W
>>>> Y= LPRED+EPS(1) * W
>>>>
>>>> Note:
>>>> i) $SIGMA (1 FIX)
>>>> ii) TAD=time after dose
>>>>
>>>> Phylinda.
>>>>
>>>>
>>>> -----Original Message-----
>>>> From: owner-nmusers
>>>>
>>> [mailto:owner-nmusers
>>>
>>>> On Behalf Of Nick Holford
>>>> Sent: 24 September 2009 08:42
>>>> To: nmusers
>>>> Subject: Re: [NMusers] time-dependent residual error models
>>>>
>>>> Mats,
>>>>
>>>> I agree with your general idea but in this particular case there is no
>>>>
>>>
>>>
>>>> description in the paper of efforts made to test structural models for
>>>>
>>>
>>>
>>>> absorption apart from first order input with dose and food effects
>>>> on Ka. There seems to be quite a lot of time related structure in
>>>> the residual error model function that Phylinda reported and I
>>>> would have thought that at least some of this could have been
>>>> explored via
>>>>
>>> another
>>>> structural model e.g. involving parallel or sequential zero-order
>>>> inputs. It struck me as a rather unusual approach and I wondered
>>>> what reasons for it were.
>>>>
>>>> It does not really bother me which approach is used when describing
>>>> absorption (fancy structure+vanilla residual or vanilla
>>>>
>>> structure+fancy
>>>> residual) because the details of the rate of absorption rarely have
>>>>
>>> any
>>>> clinical relevance (Justin Wilkins may want to disagree <grin>). Of
>>>> course, as you point out the errors may often arise from poorly
>>>> reproducible fixed effects such as timing errors etc. and thus the
>>>>
>>> goal
>>>> may be to describe the error adequately and not the structure
>>>> because the structure is not really fixed or of any interest.
>>>>
>>>> Nick
>>>>
>>>>
>>>> Mats Karlsson wrote:
>>>>
>>>>> Hi Nick,
>>>>>
>>>>> I can't answer for Phylinda, but the general idea is to build the
>>>>>
>>> most
>>>
>>>>> appropriate structural model that is supported by data. However,
>>>>>
>>> after
>>>
>>>>>
>>>> that
>>>>
>>>>> is done, if there still is variation in residual error magnitude
>>>>>
>>>> should
>>>>
>>>>> take that into account and not ignore it. All models are wrong, and
>>>>>
>>>> would
>>>>
>>>>> say that in general our models for absorption are more wrong than
>>>>>
>>>> models
>>>>
>>>>> for disposition. That is not just because we have focused more on
>>>>> latter, but because the underlying processes governing absorption are
>>>>>
>>>> of a
>>>>
>>>>> different nature (e.g. with discrete events like food intake, gastric
>>>>> emptying, bile release and formulation disintegration and movement).
>>>>>
>>>> Further
>>>>
>>>>> often part of the error magnitude is from timing errors. Such errors
>>>>>
>>>> are
>>>>
>>>>> more pronounced when concentrations are changing fast (normally
>>>>>
>>>> fastest
>>>>
>>>>> changes in absorption phase). We wrote on time-varying residual
>>>>>
>>> errors
>>>
>>>>>
>>>> (and
>>>>
>>>>> alternatives such as residual error magnitude related to rate of
>>>>>
>>>> change) in
>>>>
>>>>> these publications: J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
>>>>> J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
>>>>>
>>>>> 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
>>>>>
>>>>>
>>>>> -----Original Message-----
>>>>> From: owner-nmusers
>>>>>
>>>> [mailto:owner-nmusers
>>>>
>>>>> Behalf Of Nick Holford
>>>>> Sent: Thursday, September 24, 2009 7:46 AM
>>>>> To: nmusers
>>>>> Subject: Re: [NMusers] time-dependent residual error models
>>>>>
>>>>> Hi,
>>>>>
>>>>> If Phylinda reads this I'd be interested to hear why she choose to
>>>>>
>>> use
>>>
>>>>>
>>>> a
>>>>> plain vanilla first-order absorption model and a fancy time-dependent
>>>>>
>>>
>>>
>>>>> residual error model rather than trying to model a fancy
>>>>> absorption process with a plain vanilla residual error model?
>>>>>
>>>>> Nick
>>>>>
>>>>> Joseph Standing wrote:
>>>>>
>>>>>> Xiang,
>>>>>>
>>>>>>
>>>>>> There is a rather elegant time-dependent residual error model
>>>>>> described by Phylinda Chan et al in:
>>>>>>
>>>>>> BJCP, 2008;65(S1):76-85.
>>>>>>
>>>>>>
>>>>>> BW,
>>>>>>
>>>>>> Joe
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>>
>>
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Barry,
Thanks for this information. It is good to know that one can ignore this limitation. I never understood why it was there - especially in NONMEM 7 which was supposed to be a complete rewrite with more flexible structure.
The inability to write out a label for THETA and ETA after 70 is just one of those odd things about this program...
Nick
Barry Weatherley wrote:
> Nick, only occasionally it is worth while to forget to read the manual!
>
> In this instance (using NONMEM V, not tried for NONMEM 6), I needed more than the allotted ration of THETAs and ETAs. I had to increase the variables within *SIZES to allocate bigger LTH, LVR etc. Bill Bachman gave me a spreadsheet to get the exact sizes of all the array variables.
>
> The only problem was that the output file could not count the THETAs and ETAs beyond 70 for labelling them. So above this number the labels for THETAs and ETAs were hieroglyphics but the values were fine.
>
> Barry
>
> In message < [email protected] >, Nick Holford < [email protected] > writes
>
> > Phylinda,
> >
> > Thanks for the explanation about the impracticability of using the 'complex flexible input' model. However, I would have thought the problem was not the run time but the upper limit on number of THETAs of 70 and on OMEGA+SIGMA of 70 in NONMEM (still there in NONMEM 7!).
> >
> > "/III.2.9.1. Changing the Number of Theta’s, Eta’s, and Epsilon’s
> >
> > LTH gives the maximum number of theta’s allowable. It must be between 1 and 70. LVR gives the maximum number of eta’s plus epsilon’s allowable. It must be between 1 and 70/" NONMEM VI User Guide III
> >
> > Where would you get the ultra-big NONMEM version with 97 THETAs and 87 OMEGAs?
> >
> > Nick
> >
> > Chan, Phylinda wrote:
> >
> > > Hi Nick,
> > >
> > > There are 97 thetas and 87 omegas in the complex flexible input model.
> > > Despite of the run time, it is impractical to apply such model for
> > > covariates searching in the meta-analysis.
> > >
> > > Phylinda.
> > >
> > > -----Original Message-----
> > >
Quoted reply history
> > > From: [email protected] [ mailto: [email protected] ]
> > >
> > > On Behalf Of Nick Holford
> > > Sent: 30 September 2009 04:31
> > > To: nmusers
> > > Subject: Re: [NMusers] time-dependent residual error models
> > >
> > > Phylinda,
> > >
> > > Thanks for the explanation -- it seems that the more usual approach of complex structure+simple residual error model had already been done by Barry Weatherley. Your simple structure+complex residual error is an interesting alternative but apart from your feelings ("We felt ...") was there any reason not to use Barry's structural model?
> > >
> > > Nick
> > >
> > > Chan, Phylinda wrote:
> > >
> > > > Hi Nick,
> > > >
> > > > Being a substrate of P-gp and CYP3A4, the compound itself has a very
> > > > complex absorption profile including dose non-linearity, double peaks,
> > > > food effects as well as high between individual and within individual
> > > > variability. Barry Weatherley has spent a substantial amount of time
> > > > and effort in understanding the dose non-linearity and some covariate
> > > > effects on the PK of this compound, including development of a very
> > > > complex flexible input model which was presented at PKUK in 2004.
> > >
> > > More
> > >
> > > > details of some of this modelling work can be found in a recent
> > > > publication.
> > > > http://www3.interscience.wiley.com/journal/122386172/abstract
> > > >
> > > > The main objective of the meta-analysis was to develop a compartmental
> > > > model which would be useful in identifying significant covariates
> > > > explaining inter-individual variability and was simple enough to be
> > >
> > > used
> > >
> > > > in the later modelling of sparsely sampled PK in phase 2b/3 studies
> > > > where a full time profile and samples were likely to be clustered in
> > >
> > > the
> > >
> > > > elimination phase of the PK. We felt the first-order input with dose
> > > > and food effects on Ka in addition to the time-dependent residual
> > >
> > > error
> > >
> > > > model was adequate for this purpose.
> > > >
> > > > For those who interested in the coding of the time-dependent residual
> > > > error model: $ERROR
> > > > IPRED = F+.00001
> > > > LPRED = 0
> > > > IF(IPRED.GT.0) LPRED = LOG(IPRED)
> > > >
> > > > PMAX=THETA(7) TMAX=THETA(8) K=THETA(9)
> > > > BASE=THETA(10)
> > > >
> > > > P=K*TMAX A=EXP(P)/TMAX**P
> > > >
> > > > W= PMAX*A*(TAD+.01)**P*EXP(-K*(TAD+.01))+BASE
> > > > IRES= DV-LPRED
> > > > IWRES= IRES/W
> > > > Y= LPRED+EPS(1) * W
> > > >
> > > > Note:
> > > > i) $SIGMA (1 FIX)
> > > > ii) TAD=time after dose
> > > >
> > > > Phylinda.
> > > >
> > > > -----Original Message-----
> > > > From: [email protected]
> > >
> > > [mailto:[email protected]]
> > >
> > > > On Behalf Of Nick Holford
> > > > Sent: 24 September 2009 08:42
> > > > To: nmusers
> > > > Subject: Re: [NMusers] time-dependent residual error models
> > > >
> > > > Mats,
> > > >
> > > > I agree with your general idea but in this particular case there is no
> > >
> > > > description in the paper of efforts made to test structural models for
> > >
> > > > absorption apart from first order input with dose and food effects on Ka. There seems to be quite a lot of time related structure in the residual error model function that Phylinda reported and I would have thought that at least some of this could have been explored via
> > >
> > > another
> > >
> > > > structural model e.g. involving parallel or sequential zero-order inputs. It struck me as a rather unusual approach and I wondered what reasons for it were.
> > > >
> > > > It does not really bother me which approach is used when describing absorption (fancy structure+vanilla residual or vanilla
> > >
> > > structure+fancy
> > >
> > > > residual) because the details of the rate of absorption rarely have
> > >
> > > any
> > >
> > > > clinical relevance (Justin Wilkins may want to disagree <grin>). Of course, as you point out the errors may often arise from poorly reproducible fixed effects such as timing errors etc. and thus the
> > >
> > > goal
> > >
> > > > may be to describe the error adequately and not the structure because the structure is not really fixed or of any interest.
> > > >
> > > > Nick
> > > >
> > > > Mats Karlsson wrote:
> > > >
> > > > > Hi Nick,
> > > > >
> > > > > I can't answer for Phylinda, but the general idea is to build the
> > >
> > > most
> > >
> > > > > appropriate structural model that is supported by data. However,
> > >
> > > after
> > >
> > > > that
> > > >
> > > > > is done, if there still is variation in residual error magnitude
> > > >
> > > > should
> > > >
> > > > > take that into account and not ignore it. All models are wrong, and
> > > >
> > > > would
> > > >
> > > > > say that in general our models for absorption are more wrong than
> > > >
> > > > models
> > > >
> > > > > for disposition. That is not just because we have focused more on
> > > > > latter, but because the underlying processes governing absorption are
> > > >
> > > > of a
> > > >
> > > > > different nature (e.g. with discrete events like food intake, gastric
> > > > > emptying, bile release and formulation disintegration and movement).
> > > >
> > > > Further
> > > >
> > > > > often part of the error magnitude is from timing errors. Such errors
> > > >
> > > > are
> > > >
> > > > > more pronounced when concentrations are changing fast (normally
> > > >
> > > > fastest
> > > >
> > > > > changes in absorption phase). We wrote on time-varying residual
> > >
> > > errors
> > >
> > > > (and
> > > >
> > > > > alternatives such as residual error magnitude related to rate of
> > > >
> > > > change) in
> > > >
> > > > > these publications: J Pharmacokinet Biopharm. 1995 Dec;23(6):651-72.
> > > > > J Pharmacokinet Biopharm. 1998 Apr;26(2):207-46
> > > > >
> > > > > 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
> > > > >
> > > > > -----Original Message-----
> > > > > From: [email protected]
> > > >
> > > > [mailto:[email protected]] On
> > > >
> > > > > Behalf Of Nick Holford
> > > > > Sent: Thursday, September 24, 2009 7:46 AM
> > > > > To: nmusers
> > > > > Subject: Re: [NMusers] time-dependent residual error models
> > > > >
> > > > > Hi,
> > > > >
> > > > > If Phylinda reads this I'd be interested to hear why she choose to
> > >
> > > use
> > >
> > > > a
> > > >
> > > > > plain vanilla first-order absorption model and a fancy time-dependent
> > >
> > > > > residual error model rather than trying to model a fancy absorption process with a plain vanilla residual error model?
> > > > >
> > > > > Nick
> > > > >
> > > > > Joseph Standing wrote:
> > > > >
> > > > > > Xiang,
> > > > > >
> > > > > > There is a rather elegant time-dependent residual error model described by Phylinda Chan et al in:
> > > > > >
> > > > > > BJCP, 2008;65(S1):76-85.
> > > > > >
> > > > > > BW,
> > > > > >
> > > > > > Joe
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford