• Language: en

First order absorption model with peripheral compartment

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:builtin_tut_example
Title:First order absorption model with peripheral compartment
Author:J.R. Hartley
Abstract:
A two compartment PK model with bolus dose and
first order absorption, similar to a Nonmem advan4trans4 model.
Keywords:tutorial; pk; advan4; dep_two_cmp; first order
Input Script:builtin_tut_example.pyml
Diagram:

True f[X] values

f[KA] = 0.2000
f[CL] = 2.0000
f[V1] = 50.0000
f[Q] = 1.0000
f[V2] = 80.0000
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.1000, 0.0100, 0.0100, 0.0100, 0.0100 ],
    [ 0.0100, 0.0300, -0.0100, 0.0200, 0.0200 ],
    [ 0.0100, -0.0100, 0.0900, 0.0100, 0.0100 ],
    [ 0.0100, 0.0200, 0.0100, 0.0700, 0.0100 ],
    [ 0.0100, 0.0200, 0.0100, 0.0100, 0.0500 ]
]
f[PNOISE] = 0.1500

Starting f[X] values

f[KA] = 1.0000
f[CL] = 1.0000
f[V1] = 20.0000
f[Q] = 0.5000
f[V2] = 100.0000
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.0500, 0.0100, 0.0100, 0.0100, 0.0100 ],
    [ 0.0100, 0.0500, 0.0100, 0.0100, 0.0100 ],
    [ 0.0100, 0.0100, 0.0500, 0.0100, 0.0100 ],
    [ 0.0100, 0.0100, 0.0100, 0.0500, 0.0100 ],
    [ 0.0100, 0.0100, 0.0100, 0.0100, 0.0500 ]
]
f[PNOISE] = 0.1000

Outputs

Fitted f[X] values

f[KA] = 0.2115
f[CL] = 2.0587
f[V1] = 53.0562
f[Q] = 0.9970
f[V2] = 104.3821
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.1078, 0.0156, -0.0551, 0.0615, -0.0371 ],
    [ 0.0156, 0.0658, 0.0054, -0.0648, -0.0879 ],
    [ -0.0551, 0.0054, 0.0535, -0.0610, 0.0215 ],
    [ 0.0615, -0.0648, -0.0610, 0.3495, 0.0985 ],
    [ -0.0371, -0.0879, 0.0215, 0.0985, 0.1857 ]
]
f[PNOISE] = 0.1415

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-881.0041

Final fitted objective value

-898.8908

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 1 0.212 0.2 5.76% 1.15e-02
f[CL] 1 2.06 2 2.94% 5.87e-02
f[V1] 20 53.1 50 6.11% 3.06e+00
f[Q] 0.5 0.997 1 0.30% 2.95e-03
f[V2] 100 104 80 30.48% 2.44e+01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE] 0.1 0.141 0.15 5.70% 8.54e-03

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA_isv] 0.05 0.108 0.1 7.81% 7.81e-03
f[KA_isv;CL_isv] 0.01 0.0156 0.01 55.61% 5.56e-03
f[KA_isv;V1_isv] 0.01 -0.0551 0.01 651.13% 6.51e-02
f[KA_isv;Q_isv] 0.01 0.0615 0.01 515.16% 5.15e-02
f[KA_isv;V2_isv] 0.01 -0.0371 0.01 471.17% 4.71e-02
f[CL_isv;KA_isv] 0.01 0.0156 0.01 55.61% 5.56e-03
f[CL_isv] 0.05 0.0658 0.03 119.22% 3.58e-02
f[CL_isv;V1_isv] 0.01 0.00539 -0.01 153.88% 1.54e-02
f[CL_isv;Q_isv] 0.01 -0.0648 0.02 424.17% 8.48e-02
f[CL_isv;V2_isv] 0.01 -0.0879 0.02 539.42% 1.08e-01
f[V1_isv;KA_isv] 0.01 -0.0551 0.01 651.13% 6.51e-02
f[V1_isv;CL_isv] 0.01 0.00539 -0.01 153.88% 1.54e-02
f[V1_isv] 0.05 0.0535 0.09 40.51% 3.65e-02
f[V1_isv;Q_isv] 0.01 -0.061 0.01 710.03% 7.10e-02
f[V1_isv;V2_isv] 0.01 0.0215 0.01 115.32% 1.15e-02
f[Q_isv;KA_isv] 0.01 0.0615 0.01 515.16% 5.15e-02
f[Q_isv;CL_isv] 0.01 -0.0648 0.02 424.17% 8.48e-02
f[Q_isv;V1_isv] 0.01 -0.061 0.01 710.03% 7.10e-02
f[Q_isv] 0.05 0.349 0.07 399.22% 2.79e-01
f[Q_isv;V2_isv] 0.01 0.0985 0.01 884.73% 8.85e-02
f[V2_isv;KA_isv] 0.01 -0.0371 0.01 471.17% 4.71e-02
f[V2_isv;CL_isv] 0.01 -0.0879 0.02 539.42% 1.08e-01
f[V2_isv;V1_isv] 0.01 0.0215 0.01 115.32% 1.15e-02
f[V2_isv;Q_isv] 0.01 0.0985 0.01 884.73% 8.85e-02
f[V2_isv] 0.05 0.186 0.05 271.41% 1.36e-01
Back to Top