Nonmem ADVAN3 TRANS6 example

[Generated automatically as a Tutorial summary]

Model Description

Name:

advan3trans6_pop

Title:

Nonmem ADVAN3 TRANS6 example

Author:

PoPy for PK/PD

Abstract:

ADVAN 3 TRANS6 problem. Central compartment with a peripheral compartment.
trans 6 parameters:-
* K21 is the rate from the peripheral to the central compartment
* ALPHA
* BETA
map to advan3 parameters:-
* K21 = K21
* K12 = ALPHA+BETA-K21-K
* KE = APLHA*BETA/K21
ALPHA<K21<BETA. This must be true for model to work.
Keywords:

advan3; trans6; two compartment model

Input Script:

advan3trans6_tut.pyml

Diagram:

Comparison

True objective value

-3360.5554

Final fitted objective value

-3364.1589

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[ALPHA]

0.1

0.197

0.2

2.95e-03

1.48%

f[DIFFALPHAK21]

0.2

0.3…

0.3

4.34e-04

0.14%

f[DIFFK21BETA]

0.2

0.302

0.3

2.17e-03

0.72%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PNOISE]

0.05

0.00992

0.01

7.53e-05

0.75%

f[ANOISE]

0.05

0.00962

0.01

3.83e-04

3.83%

Compare Variance f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[ALPHA_isv]

0.04

0.0968

0.1

3.23e-03

3.23%

f[ALPHA_isv;DIFFALPHAK21_isv]

0

-0.0011

0

1.10e-03

inf

f[ALPHA_isv;DIFFK21BETA_isv]

0

-0.000817

0

8.17e-04

inf

f[DIFFALPHAK21_isv;ALPHA_isv]

0

-0.0011

0

1.10e-03

inf

f[DIFFALPHAK21_isv]

0.08

0.0525

0.05

2.51e-03

5.02%

f[DIFFALPHAK21_isv;DIFFK21BETA_isv]

0

0.0028

0

2.80e-03

inf

f[DIFFK21BETA_isv;ALPHA_isv]

0

-0.000817

0

8.17e-04

inf

f[DIFFK21BETA_isv;DIFFALPHAK21_isv]

0

0.0028

0

2.80e-03

inf

f[DIFFK21BETA_isv]

0.07

0.0124

0.02

7.63e-03

38.13%

Outputs

Fitted f[X] values (after fitting)

f[ALPHA] = 0.1970
f[DIFFALPHAK21] = 0.2996
f[DIFFK21BETA] = 0.3022
f[PNOISE] = 0.0099
f[ANOISE] = 0.0096
f[ALPHA_isv,DIFFALPHAK21_isv,DIFFK21BETA_isv] = [
    [ 0.0968, -0.0011, -0.0008 ],
    [ -0.0011, 0.0525, 0.0028 ],
    [ -0.0008, 0.0028, 0.0124 ],
]

Generated data .csv file

Synthetic Data:

synthetic_data.csv

Gen and Fit Summaries

Inputs

True f[X] values (for simulation)

f[ALPHA] = 0.2000
f[DIFFALPHAK21] = 0.3000
f[DIFFK21BETA] = 0.3000
f[PNOISE] = 0.0100
f[ANOISE] = 0.0100
f[ALPHA_isv,DIFFALPHAK21_isv,DIFFK21BETA_isv] = [
    [ 0.1000, 0.0000, 0.0000 ],
    [ 0.0000, 0.0500, 0.0000 ],
    [ 0.0000, 0.0000, 0.0200 ],
]

Starting f[X] values (before fitting)

f[ALPHA] = 0.1000
f[DIFFALPHAK21] = 0.2000
f[DIFFK21BETA] = 0.2000
f[PNOISE] = 0.0500
f[ANOISE] = 0.0500
f[ALPHA_isv,DIFFALPHAK21_isv,DIFFK21BETA_isv] = [
    [ 0.0400, 0.0000, 0.0000 ],
    [ 0.0000, 0.0800, 0.0000 ],
    [ 0.0000, 0.0000, 0.0700 ],
]