Hi,
I have a complex model with manually coded ODEs and multiple compartments. VPC etc seem ok but simulation results are getting a bit weird.
I'd like to find out what people use to ensure that the NONMEM code written really represents the set of ODEs written on paper. Just to clarify, this is just to make sure the NONMEM instructions are actually a correct representation of the mathematical description of the model, not if the model is a correct representation of the biology at this stage.
This problem is not so obvious when you use the built-in macros but once the model grows complex, and has a lot manual inputs, it is more likely that a bug creeps in.
I'm looking for something more stringent than a code review by a peer.
Thank you advance for your time and attention,
Ana
------------------------------------------
Ana Bastos, Pharm, MSc, PhD student
Pharmacologie cellulaire et molculaire
(Cellular and Molecular Pharmacology Unit)
Louvain Drug Research Institute
Universit catholique de Louvain (Catholic University of Louvain)
UCL 7370 avenue E. Mounier 73
1200 Bruxelles, Belgique
NONMEM code verification
Hi,
I have a complex model with manually coded ODEs and multiple compartments. VPC
etc seem ok but simulation results are getting a bit weird.
I'd like to find out what people use to ensure that the NONMEM code written
really represents the set of ODEs written on paper. Just to clarify, this is
just to make sure the NONMEM instructions are actually a correct representation
of the mathematical description of the model, not if the model is a correct
representation of the biology at this stage.
This problem is not so obvious when you use the built-in macros but once the
model grows complex, and has a lot manual inputs, it is more likely that a bug
creeps in.
I'm looking for something more stringent than a code review by a peer.
Thank you advance for your time and attention,
Ana
------------------------------------------
Ana Bastos, Pharm, MSc, PhD student
Pharmacologie cellulaire et moléculaire
(Cellular and Molecular Pharmacology Unit)
Louvain Drug Research Institute
Université catholique de Louvain (Catholic University of Louvain)
UCL 7370 avenue E. Mounier 73
1200 Bruxelles, Belgique
Ana,
I call this process fixed effect (or deterministic) model qualification.
I code complex models using Berkeley Madonna then run NONMEM without any $EST or $SIM records. The NONMEM PRED values should agree with the Berkeley Madonna predictions if your structural model is coded the same way in both systems.
Best wishes,
Nick
Quoted reply history
On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
> Hi,
>
> I have a complex model with manually coded ODEs and multiple compartments. VPC etc seem ok but simulation results are getting a bit weird.
>
> I'd like to find out what people use to ensure that the NONMEM code written really represents the set of ODEs written on paper. Just to clarify, this is just to make sure the NONMEM instructions are actually a correct representation of the mathematical description of the model, not if the model is a correct representation of the biology at this stage.
>
> This problem is not so obvious when you use the built-in macros but once the model grows complex, and has a lot manual inputs, it is more likely that a bug creeps in.
>
> I'm looking for something more stringent than a code review by a peer.
>
> Thank you advance for your time and attention,
>
> Ana
>
> ------------------------------------------
> Ana Bastos, Pharm, MSc, PhD student
> Pharmacologie cellulaire et moléculaire
> (Cellular and Molecular Pharmacology Unit)
> Louvain Drug Research Institute
> Université catholique de Louvain (Catholic University of Louvain)
> UCL 7370 avenue E. Mounier 73
> 1200 Bruxelles, Belgique
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
email: [email protected]
http://holford.fmhs.auckland.ac.nz/
"Declarative languages are a form of dementia -- they have no memory of events"
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop,
B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models
- tests of assumptions and predictions. Journal of Pharmacology & Clinical
Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.
Ana:
The most common reason NONMEM may produce a different result than expected is
if the evaluation depends on covariates listed in the data set that changes
with each record, the default action of NONMEM is for an interval covering
T1>Time<=T2, it uses the covariate at record TIME=T2. This behavior can be
changed with $BIND. Also, if you program in discontinuities that vary with
model parameters, like changing a rate constant suddenly, you may want to use
the MTIME() system. Both of these items are discussed in viii.pdf.
Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428
Mobile: (925) 286-0769
[email protected]<mailto:[email protected]>
http://www.iconplc.com
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Nick Holford
Sent: Thursday, January 21, 2016 11:33 AM
To: [email protected]
Subject: Re: [NMusers] NONMEM code verification
Ana,
I call this process fixed effect (or deterministic) model qualification.
I code complex models using Berkeley Madonna then run NONMEM without any
$EST or $SIM records. The NONMEM PRED values should agree with the
Berkeley Madonna predictions if your structural model is coded the same
way in both systems.
Best wishes,
Nick
On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
>
> Hi,
>
>
> I have a complex model with manually coded ODEs and multiple
> compartments. VPC etc seem ok but simulation results are getting a bit
> weird.
>
>
> I'd like to find out what people use to ensure that the NONMEM code
> written really represents the set of ODEs written on paper. Just to
> clarify, this is just to make sure the NONMEM instructions are
> actually a correct representation of the mathematical description of
> the model, not if the model is a correct representation of the biology
> at this stage.
>
>
> This problem is not so obvious when you use the built-in macros but
> once the model grows complex, and has a lot manual inputs, it is more
> likely that a bug creeps in.
>
>
> I'm looking for something more stringent than a code review by a peer.
>
>
> Thank you advance for your time and attention,
>
>
> Ana
>
>
> ------------------------------------------
> Ana Bastos, Pharm, MSc, PhD student
> Pharmacologie cellulaire et moléculaire
> (Cellular and Molecular Pharmacology Unit)
> Louvain Drug Research Institute
> Université catholique de Louvain (Catholic University of Louvain)
> UCL 7370 avenue E. Mounier 73
> 1200 Bruxelles, Belgique
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
email: [email protected]<mailto:[email protected]>
http://holford.fmhs.auckland.ac.nz/
"Declarative languages are a form of dementia -- they have no memory of events"
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A,
Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite
pharmacokinetic models - tests of assumptions and predictions. Journal of
Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.
If working in R, you can use mrgsolve:
http://metrumrg.com/opensourcetools.html
It is open-source, validated R package interfacing with DLSODA solver in
ODEPACK.
It should be able to directly utilize your NONMEM data set:
http://metrumrg.com/mrgsolve-howdoi.html#implement-events-via-data-set
(you might need to rename some columns ... use tolower() or mrgsolve has a
function to do it).
If you're really making a really close comparison, pay attention to the
solver tolerances and the number of digits in the answer (you can control
them in both NONMEM and mrgsolve). Caution: mrgsolve advances with the
covariate at T1 (in Bob's example). But I guess I'd tend to take that
factor out of play and just look at predictions from some parameters
constant over time where possible (assuming you're really wanting to
diagnose what is happening with the ODEs; that's how I understood Nick's
post).
Kyle
Quoted reply history
On Thu, Jan 21, 2016 at 2:02 PM, Bauer, Robert <[email protected]>
wrote:
> Ana:
>
> The most common reason NONMEM may produce a different result than expected
> is if the evaluation depends on covariates listed in the data set that
> changes with each record, the default action of NONMEM is for an interval
> covering T1>Time<=T2, it uses the covariate at record TIME=T2. This
> behavior can be changed with $BIND. Also, if you program in
> discontinuities that vary with model parameters, like changing a rate
> constant suddenly, you may want to use the MTIME() system. Both of these
> items are discussed in viii.pdf.
>
>
>
>
>
>
>
> Robert J. Bauer, Ph.D.
>
> Vice President, Pharmacometrics R&D
>
> ICON Early Phase
>
> Office: (215) 616-6428
>
> Mobile: (925) 286-0769
>
> [email protected]
>
> www.iconplc.com
>
>
>
> *From:* [email protected] [mailto:[email protected]]
> *On Behalf Of *Nick Holford
> *Sent:* Thursday, January 21, 2016 11:33 AM
> *To:* [email protected]
> *Subject:* Re: [NMusers] NONMEM code verification
>
>
>
> Ana,
>
>
> I call this process fixed effect (or deterministic) model qualification.
>
> I code complex models using Berkeley Madonna then run NONMEM without any
> $EST or $SIM records. The NONMEM PRED values should agree with the
> Berkeley Madonna predictions if your structural model is coded the same
> way in both systems.
>
> Best wishes,
>
> Nick
>
> On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
> >
> > Hi,
> >
> >
> > I have a complex model with manually coded ODEs and multiple
> > compartments. VPC etc seem ok but simulation results are getting a bit
> > weird.
> >
> >
> > I'd like to find out what people use to ensure that the NONMEM code
> > written really represents the set of ODEs written on paper. Just to
> > clarify, this is just to make sure the NONMEM instructions are
> > actually a correct representation of the mathematical description of
> > the model, not if the model is a correct representation of the biology
> > at this stage.
> >
> >
> > This problem is not so obvious when you use the built-in macros but
> > once the model grows complex, and has a lot manual inputs, it is more
> > likely that a bug creeps in.
> >
> >
> > I'm looking for something more stringent than a code review by a peer.
> >
> >
> > Thank you advance for your time and attention,
> >
> >
> > Ana
> >
> >
> > ------------------------------------------
> > Ana Bastos, Pharm, MSc, PhD student
> > Pharmacologie cellulaire et moléculaire
> > (Cellular and Molecular Pharmacology Unit)
> > Louvain Drug Research Institute
> > Université catholique de Louvain (Catholic University of Louvain)
> > UCL 7370 avenue E. Mounier 73
> > 1200 Bruxelles, Belgique
> >
>
> --
> Nick Holford, Professor Clinical Pharmacology
> Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
> University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
> office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
> email: [email protected]
> http://holford.fmhs.auckland.ac.nz/
>
> "Declarative languages are a form of dementia -- they have no memory of
> events"
>
> Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A,
> Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite
> pharmacokinetic models - tests of assumptions and predictions. Journal of
> Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
> Holford N. Clinical pharmacology = disease progression + drug action. Br J
> Clin Pharmacol. 2015;79(1):18-27.
>
>
>
>
Hi Ana,
What kind of weird behavior do you get?
If your model is complex in that it is nonlinear, it is likely that it shows
multistationarity or oscillations or other emergent behavior which you may not
expect. Some mathematical analysis of the structural model itself may be useful
in that case.
Suruchi.
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Kyle Baron
Sent: donderdag 21 januari 2016 22:42
To: Bauer, Robert
Cc: Nick Holford; [email protected]
Subject: Re: [NMusers] NONMEM code verification
If working in R, you can use mrgsolve:
http://metrumrg.com/opensourcetools.html
It is open-source, validated R package interfacing with DLSODA solver in
ODEPACK.
It should be able to directly utilize your NONMEM data set:
http://metrumrg.com/mrgsolve-howdoi.html#implement-events-via-data-set
(you might need to rename some columns ... use tolower() or mrgsolve has a
function to do it).
If you're really making a really close comparison, pay attention to the solver
tolerances and the number of digits in the answer (you can control them in both
NONMEM and mrgsolve). Caution: mrgsolve advances with the covariate at T1 (in
Bob's example). But I guess I'd tend to take that factor out of play and just
look at predictions from some parameters constant over time where possible
(assuming you're really wanting to diagnose what is happening with the ODEs;
that's how I understood Nick's post).
Kyle
On Thu, Jan 21, 2016 at 2:02 PM, Bauer, Robert
<[email protected]<mailto:[email protected]>> wrote:
Ana:
The most common reason NONMEM may produce a different result than expected is
if the evaluation depends on covariates listed in the data set that changes
with each record, the default action of NONMEM is for an interval covering
T1>Time<=T2, it uses the covariate at record TIME=T2. This behavior can be
changed with $BIND. Also, if you program in discontinuities that vary with
model parameters, like changing a rate constant suddenly, you may want to use
the MTIME() system. Both of these items are discussed in viii.pdf.
Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428<tel:%28215%29%20616-6428>
Mobile: (925) 286-0769<tel:%28925%29%20286-0769>
[email protected]<mailto:[email protected]>
http://www.iconplc.com
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Nick Holford
Sent: Thursday, January 21, 2016 11:33 AM
To: [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] NONMEM code verification
Ana,
I call this process fixed effect (or deterministic) model qualification.
I code complex models using Berkeley Madonna then run NONMEM without any
$EST or $SIM records. The NONMEM PRED values should agree with the
Berkeley Madonna predictions if your structural model is coded the same
way in both systems.
Best wishes,
Nick
On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
>
> Hi,
>
>
> I have a complex model with manually coded ODEs and multiple
> compartments. VPC etc seem ok but simulation results are getting a bit
> weird.
>
>
> I'd like to find out what people use to ensure that the NONMEM code
> written really represents the set of ODEs written on paper. Just to
> clarify, this is just to make sure the NONMEM instructions are
> actually a correct representation of the mathematical description of
> the model, not if the model is a correct representation of the biology
> at this stage.
>
>
> This problem is not so obvious when you use the built-in macros but
> once the model grows complex, and has a lot manual inputs, it is more
> likely that a bug creeps in.
>
>
> I'm looking for something more stringent than a code review by a peer.
>
>
> Thank you advance for your time and attention,
>
>
> Ana
>
>
> ------------------------------------------
> Ana Bastos, Pharm, MSc, PhD student
> Pharmacologie cellulaire et moléculaire
> (Cellular and Molecular Pharmacology Unit)
> Louvain Drug Research Institute
> Université catholique de Louvain (Catholic University of Louvain)
> UCL 7370 avenue E. Mounier 73
> 1200 Bruxelles, Belgique
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730<tel:%2B64%289%29923-6730> mobile:NZ+64(21)46 23 53
email: [email protected]<mailto:[email protected]>
http://holford.fmhs.auckland.ac.nz/
"Declarative languages are a form of dementia -- they have no memory of events"
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A,
Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite
pharmacokinetic models - tests of assumptions and predictions. Journal of
Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.
Hi,
Adding to Suruchi, one issue I have encountered in the past when working with
complex or mathematically stiff models is that different integrators
occasionally give different results.
This will usually show up as instability of one of the integrators (big jumps
up and down on a percent basis from one point to the next). In the past
several years, this is getting rarer, but it can never be eliminated while
using computers and numerical methods.
Thanks,
Bill
Quoted reply history
On Jan 22, 2016, at 5:21, "Bakshi, S.D."
<[email protected]<mailto:[email protected]>> wrote:
Hi Ana,
What kind of weird behavior do you get?
If your model is complex in that it is nonlinear, it is likely that it shows
multistationarity or oscillations or other emergent behavior which you may not
expect. Some mathematical analysis of the structural model itself may be useful
in that case.
Suruchi.
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Kyle Baron
Sent: donderdag 21 januari 2016 22:42
To: Bauer, Robert
Cc: Nick Holford; [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] NONMEM code verification
If working in R, you can use mrgsolve:
https://urldefense.proofpoint.com/v2/url?u=http-3A__metrumrg.com_opensourcetools.html&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=xZxJx4fKx0tHuBPX2jrymatHCBV3ia4MDZXvDqjP_qw&e=
It is open-source, validated R package interfacing with DLSODA solver in
ODEPACK.
It should be able to directly utilize your NONMEM data set:
https://urldefense.proofpoint.com/v2/url?u=http-3A__metrumrg.com_mrgsolve-2Dhowdoi.html-23implement-2Devents-2Dvia-2Ddata-2Dset&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=1jnINFT9t3Y9xLxm6u7WDT-q0RoQgWvx7vkwAnMgp5Q&e=
(you might need to rename some columns ... use tolower() or mrgsolve has a
function to do it).
If you're really making a really close comparison, pay attention to the solver
tolerances and the number of digits in the answer (you can control them in both
NONMEM and mrgsolve). Caution: mrgsolve advances with the covariate at T1 (in
Bob's example). But I guess I'd tend to take that factor out of play and just
look at predictions from some parameters constant over time where possible
(assuming you're really wanting to diagnose what is happening with the ODEs;
that's how I understood Nick's post).
Kyle
On Thu, Jan 21, 2016 at 2:02 PM, Bauer, Robert
<[email protected]<mailto:[email protected]>> wrote:
Ana:
The most common reason NONMEM may produce a different result than expected is
if the evaluation depends on covariates listed in the data set that changes
with each record, the default action of NONMEM is for an interval covering
T1>Time<=T2, it uses the covariate at record TIME=T2. This behavior can be
changed with $BIND. Also, if you program in discontinuities that vary with
model parameters, like changing a rate constant suddenly, you may want to use
the MTIME() system. Both of these items are discussed in viii.pdf.
Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428<tel:%28215%29%20616-6428>
Mobile: (925) 286-0769<tel:%28925%29%20286-0769>
[email protected]<mailto:[email protected]>
www.iconplc.com&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=Y_rKfgK60QKPvt-a1cR51zCfjhe03CecdbU1RGJHEmk&e=">https://urldefense.proofpoint.com/v2/url?u=http-3A__www.iconplc.com&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=Y_rKfgK60QKPvt-a1cR51zCfjhe03CecdbU1RGJHEmk&e=
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Nick Holford
Sent: Thursday, January 21, 2016 11:33 AM
To: [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] NONMEM code verification
Ana,
I call this process fixed effect (or deterministic) model qualification.
I code complex models using Berkeley Madonna then run NONMEM without any
$EST or $SIM records. The NONMEM PRED values should agree with the
Berkeley Madonna predictions if your structural model is coded the same
way in both systems.
Best wishes,
Nick
On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
>
> Hi,
>
>
> I have a complex model with manually coded ODEs and multiple
> compartments. VPC etc seem ok but simulation results are getting a bit
> weird.
>
>
> I'd like to find out what people use to ensure that the NONMEM code
> written really represents the set of ODEs written on paper. Just to
> clarify, this is just to make sure the NONMEM instructions are
> actually a correct representation of the mathematical description of
> the model, not if the model is a correct representation of the biology
> at this stage.
>
>
> This problem is not so obvious when you use the built-in macros but
> once the model grows complex, and has a lot manual inputs, it is more
> likely that a bug creeps in.
>
>
> I'm looking for something more stringent than a code review by a peer.
>
>
> Thank you advance for your time and attention,
>
>
> Ana
>
>
> ------------------------------------------
> Ana Bastos, Pharm, MSc, PhD student
> Pharmacologie cellulaire et moléculaire
> (Cellular and Molecular Pharmacology Unit)
> Louvain Drug Research Institute
> Université catholique de Louvain (Catholic University of Louvain)
> UCL 7370 avenue E. Mounier 73
> 1200 Bruxelles, Belgique
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730<tel:%2B64%289%29923-6730> mobile:NZ+64(21)46 23 53
email: [email protected]<mailto:[email protected]>
https://urldefense.proofpoint.com/v2/url?u=http-3A__holford.fmhs.auckland.ac.nz_&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=n_lm1CsMIyouNC38ssmFpdHdQGI1_0IDXFKGjy0C-iE&e=
"Declarative languages are a form of dementia -- they have no memory of events"
Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A,
Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite
pharmacokinetic models - tests of assumptions and predictions. Journal of
Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.
Hi,
Thank you all for your input.
Nick - I'll follow your approach, but I'll try to use the R package suggested
by Kyle, as I don't have Berckeley Madonna.
Suruchi - The weird behaviour is that the model simulation is suggesting that
for a given Probability of treatment target, a lower dose is needed as the
weight goes up and dosing interval goes up. Weight is incorporated in the model
using allometric scaling for different parameters. The drug is a penicillin.
The model diagnostics, including VPCs, look OK, but this result seems to be
counter-intuitive...Has anyone seen a behaviour like that before?
Ana
Quoted reply history
________________________________
From: [email protected] <[email protected]> on behalf of
Denney, William S. <[email protected]>
Sent: 22 January 2016 15:03
To: Bakshi, S.D.
Cc: [email protected]
Subject: Re: [NMusers] NONMEM code verification
Hi,
Adding to Suruchi, one issue I have encountered in the past when working with
complex or mathematically stiff models is that different integrators
occasionally give different results.
This will usually show up as instability of one of the integrators (big jumps
up and down on a percent basis from one point to the next). In the past
several years, this is getting rarer, but it can never be eliminated while
using computers and numerical methods.
Thanks,
Bill
On Jan 22, 2016, at 5:21, "Bakshi, S.D."
<[email protected]<mailto:[email protected]>> wrote:
Hi Ana,
What kind of weird behavior do you get?
If your model is complex in that it is nonlinear, it is likely that it shows
multistationarity or oscillations or other emergent behavior which you may not
expect. Some mathematical analysis of the structural model itself may be useful
in that case.
Suruchi.
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Kyle Baron
Sent: donderdag 21 januari 2016 22:42
To: Bauer, Robert
Cc: Nick Holford; [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] NONMEM code verification
If working in R, you can use mrgsolve:
https://urldefense.proofpoint.com/v2/url?u=http-3A__metrumrg.com_opensourcetools.html&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=xZxJx4fKx0tHuBPX2jrymatHCBV3ia4MDZXvDqjP_qw&e=
It is open-source, validated R package interfacing with DLSODA solver in
ODEPACK.
It should be able to directly utilize your NONMEM data set:
https://urldefense.proofpoint.com/v2/url?u=http-3A__metrumrg.com_mrgsolve-2Dhowdoi.html-23implement-2Devents-2Dvia-2Ddata-2Dset&d=CwMGaQ&c=UE1eNsedaKncO0Yl_u8bfw&r=4WqjVFXRfAkMXd6y3wiAtxtNlICJwFMiogoD6jkpUkg&m=ppRE3mLmLwEUK40XIVKCcYhDBPg6Ut8daFHz3--izi4&s=1jnINFT9t3Y9xLxm6u7WDT-q0RoQgWvx7vkwAnMgp5Q&e=
(you might need to rename some columns ... use tolower() or mrgsolve has a
function to do it).
If you're really making a really close comparison, pay attention to the solver
tolerances and the number of digits in the answer (you can control them in both
NONMEM and mrgsolve). Caution: mrgsolve advances with the covariate at T1 (in
Bob's example). But I guess I'd tend to take that factor out of play and just
look at predictions from some parameters constant over time where possible
(assuming you're really wanting to diagnose what is happening with the ODEs;
that's how I understood Nick's post).
Kyle
On Thu, Jan 21, 2016 at 2:02 PM, Bauer, Robert
<[email protected]<mailto:[email protected]>> wrote:
Ana:
The most common reason NONMEM may produce a different result than expected is
if the evaluation depends on covariates listed in the data set that changes
with each record, the default action of NONMEM is for an interval covering
T1>Time<=T2, it uses the covariate at record TIME=T2. This behavior can be
changed with $BIND. Also, if you program in discontinuities that vary with
model parameters, like changing a rate constant suddenly, you may want to use
the MTIME() system. Both of these items are discussed in viii.pdf.
Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428<tel:%28215%29%20616-6428>
Mobile: (925) 286-0769<tel:%28925%29%20286-0769>
[email protected]<mailto:[email protected]>
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From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Nick Holford
Sent: Thursday, January 21, 2016 11:33 AM
To: [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] NONMEM code verification
Ana,
I call this process fixed effect (or deterministic) model qualification.
I code complex models using Berkeley Madonna then run NONMEM without any
$EST or $SIM records. The NONMEM PRED values should agree with the
Berkeley Madonna predictions if your structural model is coded the same
way in both systems.
Best wishes,
Nick
On 20-Jan-16 11:14, Ana Miranda Bastos wrote:
>
> Hi,
>
>
> I have a complex model with manually coded ODEs and multiple
> compartments. VPC etc seem ok but simulation results are getting a bit
> weird.
>
>
> I'd like to find out what people use to ensure that the NONMEM code
> written really represents the set of ODEs written on paper. Just to
> clarify, this is just to make sure the NONMEM instructions are
> actually a correct representation of the mathematical description of
> the model, not if the model is a correct representation of the biology
> at this stage.
>
>
> This problem is not so obvious when you use the built-in macros but
> once the model grows complex, and has a lot manual inputs, it is more
> likely that a bug creeps in.
>
>
> I'm looking for something more stringent than a code review by a peer.
>
>
> Thank you advance for your time and attention,
>
>
> Ana
>
>
> ------------------------------------------
> Ana Bastos, Pharm, MSc, PhD student
> Pharmacologie cellulaire et moléculaire
> (Cellular and Molecular Pharmacology Unit)
> Louvain Drug Research Institute
> Université catholique de Louvain (Catholic University of Louvain)
> UCL 7370 avenue E. Mounier 73
> 1200 Bruxelles, Belgique
>
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
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