Dear NMusers,
I'm a NM beginner modeling for a monoclonal antibody. Below is 12
subjects's individual predicted plot , it seems that nonlinear
elimination (Michaelis-Menten) model can fit the data well. However, when
running the control stream (two compartment models with linear and
non-linear elimination), the resulting Q THETA SE% and OMEGA SE% are quite
large even thought successful minimization.From the Correlation Matrix , I
find that THETA (1) (VMAX) and THETA(2) (KM)are highly correlated (9.67E-01).
Another problem is the .fit file can't be produced.
I have tried various error models and initial estimations, however, none
had better improvement and often got error message (error 134
or parameter estimate is near its boundary). Does re-parameterization
helpful ? or need to change to other models?
Any suggestions for solving the problems are highly appreciated.
(control stream will be send in another e-mail)
two compartment with nonlinear elimination
Chiaying,
Your concentration-time profiles seem to suggest that there’s an absorption
phase which was not accounted for in your model/control stream. What was the
route of administration?
Ken
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Chiaying Lin
Sent: Tuesday, September 08, 2015 7:57 AM
To: [email protected]
Subject: [NMusers] two compartment with nonlinear elimination
Dear NMusers,
I'm a NM beginner modeling for a monoclonal antibody. Below is 12 subjects's
individual predicted plot , it seems that nonlinear elimination
(Michaelis-Menten) model can fit the data well. However, when running the
control stream (two compartment models with linear and non-linear elimination),
the resulting Q THETA SE% and OMEGA SE% are quite large even thought successful
minimization.From the Correlation Matrix , I find that THETA (1) (VMAX) and
THETA(2) (KM)are highly correlated (9.67E-01). Another problem is the .fit file
can't be produced.
I have tried various error models and initial estimations, however, none had
better improvement and often got error message (error 134 or parameter estimate
is near its boundary). Does re-parameterization helpful ? or need to change to
other models?
Any suggestions for solving the problems are highly appreciated.
(control stream will be send in another e-mail)
Hi Ken,
It's given via iv infusion. The infusion rate (RATE) and ruraiton (DUR) are
included in the data file. I also have defined D1=DUR in the $PK block.
There is something wrong?
#IDTIMEAMTNDVLNDVEVIDMDVCMTBWAGEDOSERATEDUR1081.3..11181.35081.3-2110.254.8
1.568616181.35081.3 .111182.890372181.35081.3 .1
Quoted reply history
2015-09-08 23:34 GMT+08:00 Ken Luu <[email protected]>:
> Chiaying,
>
>
>
> Your concentration-time profiles seem to suggest that there’s an
> absorption phase which was not accounted for in your model/control stream.
> What was the route of administration?
>
>
>
> Ken
>
>
>
> *From:* [email protected] [mailto:[email protected]]
> *On Behalf Of *Chiaying Lin
> *Sent:* Tuesday, September 08, 2015 7:57 AM
> *To:* [email protected]
> *Subject:* [NMusers] two compartment with nonlinear elimination
>
>
>
> Dear NMusers,
>
> I'm a NM beginner modeling for a monoclonal antibody. Below is 12
> subjects's individual predicted plot , it seems that nonlinear
> elimination (Michaelis-Menten) model can fit the data well. However, when
> running the control stream (two compartment models with linear and
> non-linear elimination), the resulting Q THETA SE% and OMEGA SE% are quite
> large even thought successful minimization.From the Correlation Matrix , I
> find that THETA (1) (VMAX) and THETA(2) (KM)are highly correlated
> (9.67E-01). Another problem is the .fit file can't be produced.
>
>
>
> I have tried various error models and initial estimations, however, none
> had better improvement and often got error message (error 134
> or parameter estimate is near its boundary). Does re-parameterization
> helpful ? or need to change to other models?
>
>
>
> Any suggestions for solving the problems are highly appreciated.
>
>
>
> (control stream will be send in another e-mail)
>
Hi Chiaying,
I didn’t realize that you were using D1 and setting the RATE to -2. I
personally haven’t coded it this way for an IV route (may others who have could
chime in). I’ve seen D1 being estimated as a parameter in an extravascular
model. My first inclination, without viewing your results in detail, is to
provide the actual rate in the data file and remove D1. You may just get the
same results but at least you can rule out that the problem is due to your
existing parameterization.
Ken
Quoted reply history
From: Chiaying Lin [mailto:[email protected]]
Sent: Tuesday, September 08, 2015 6:17 PM
To: Ken Luu; [email protected]
Subject: Re: [NMusers] two compartment with nonlinear elimination
Hi Ken,
It's given via iv infusion. The infusion rate (RATE) and ruraiton (DUR) are
included in the data file. I also have defined D1=DUR in the $PK block. There
is something wrong?
#ID
TIME
AMT
NDV
LNDV
EVID
MDV
CMT
BW
AGE
DOSE
RATE
DUR
1
0
81.3
.
.
1
1
1
81.3
50
81.3
-2
1
1
0.25
4.8
1.568616
1
81.3
50
81.3
.
1
1
1
18
2.890372
1
81.3
50
81.3
.
1
2015-09-08 23:34 GMT+08:00 Ken Luu <[email protected]<mailto:[email protected]>>:
Chiaying,
Your concentration-time profiles seem to suggest that there’s an absorption
phase which was not accounted for in your model/control stream. What was the
route of administration?
Ken
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Chiaying Lin
Sent: Tuesday, September 08, 2015 7:57 AM
To: [email protected]<mailto:[email protected]>
Subject: [NMusers] two compartment with nonlinear elimination
Dear NMusers,
I'm a NM beginner modeling for a monoclonal antibody. Below is 12 subjects's
individual predicted plot , it seems that nonlinear elimination
(Michaelis-Menten) model can fit the data well. However, when running the
control stream (two compartment models with linear and non-linear elimination),
the resulting Q THETA SE% and OMEGA SE% are quite large even thought successful
minimization.From the Correlation Matrix , I find that THETA (1) (VMAX) and
THETA(2) (KM)are highly correlated (9.67E-01). Another problem is the .fit file
can't be produced.
I have tried various error models and initial estimations, however, none had
better improvement and often got error message (error 134 or parameter estimate
is near its boundary). Does re-parameterization helpful ? or need to change to
other models?
Any suggestions for solving the problems are highly appreciated.
(control stream will be send in another e-mail)
Hi Chiaying,
Following on Ken’s email. The way I usually code infusion models is to put
the actual RATE in the input data file. Then NONMEM, by defaults, would know
the infusion time by having the AMT and RATE column in the dataset. Therefore,
you don’t need to add a parameter for the duration in your code.
Best,
Sincerely,
Ahmad Abuhelwa, PhD Candidate
Australian Center for Pharmacometrics |P1-09| Playford Building
School of Pharmacy and Medical Sciences
University of South Australia- City East Campus
Adelaide, South Australia
Australia
Email:
[email protected]<mailto:[email protected]>
Mobile: +61 413118743
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Ken Luu
Sent: Wednesday, 9 September 2015 11:30 AM
To: Chiaying Lin <[email protected]>; [email protected]
Subject: RE: [NMusers] two compartment with nonlinear elimination
Hi Chiaying,
I didn’t realize that you were using D1 and setting the RATE to -2. I
personally haven’t coded it this way for an IV route (may others who have could
chime in). I’ve seen D1 being estimated as a parameter in an extravascular
model. My first inclination, without viewing your results in detail, is to
provide the actual rate in the data file and remove D1. You may just get the
same results but at least you can rule out that the problem is due to your
existing parameterization.
Ken
From: Chiaying Lin [mailto:[email protected]]
Sent: Tuesday, September 08, 2015 6:17 PM
To: Ken Luu; [email protected]<mailto:[email protected]>
Subject: Re: [NMusers] two compartment with nonlinear elimination
Hi Ken,
It's given via iv infusion. The infusion rate (RATE) and ruraiton (DUR) are
included in the data file. I also have defined D1=DUR in the $PK block. There
is something wrong?
#ID
TIME
AMT
NDV
LNDV
EVID
MDV
CMT
BW
AGE
DOSE
RATE
DUR
1
0
81.3
.
.
1
1
1
81.3
50
81.3
-2
1
1
0.25
4.8
1.568616
1
81.3
50
81.3
.
1
1
1
18
2.890372
1
81.3
50
81.3
.
1
2015-09-08 23:34 GMT+08:00 Ken Luu <[email protected]<mailto:[email protected]>>:
Chiaying,
Your concentration-time profiles seem to suggest that there’s an absorption
phase which was not accounted for in your model/control stream. What was the
route of administration?
Ken
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]<mailto:[email protected]>] On
Behalf Of Chiaying Lin
Sent: Tuesday, September 08, 2015 7:57 AM
To: [email protected]<mailto:[email protected]>
Subject: [NMusers] two compartment with nonlinear elimination
Dear NMusers,
I'm a NM beginner modeling for a monoclonal antibody. Below is 12 subjects's
individual predicted plot , it seems that nonlinear elimination
(Michaelis-Menten) model can fit the data well. However, when running the
control stream (two compartment models with linear and non-linear elimination),
the resulting Q THETA SE% and OMEGA SE% are quite large even thought successful
minimization.From the Correlation Matrix , I find that THETA (1) (VMAX) and
THETA(2) (KM)are highly correlated (9.67E-01). Another problem is the .fit file
can't be produced.
I have tried various error models and initial estimations, however, none had
better improvement and often got error message (error 134 or parameter estimate
is near its boundary). Does re-parameterization helpful ? or need to change to
other models?
Any suggestions for solving the problems are highly appreciated.
(control stream will be send in another e-mail)