From: Chiaying Lin <*cylin292*>

Date: Tue, 8 Sep 2015 22:29:12 +0800

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.

[image: 內置圖片 1]

Received on Tue Sep 08 2015 - 10:29:12 EDT

Date: Tue, 8 Sep 2015 22:29:12 +0800

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.

[image: 內置圖片 1]

Received on Tue Sep 08 2015 - 10:29:12 EDT