• 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] = 0.1019
f[CL] = 2.1528
f[V1] = 24.1372
f[Q] = 1.9547
f[V2] = 61.7683
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.0322, 0.0145, 0.0383, -0.0011, -0.0925 ],
    [ 0.0145, 0.0165, 0.0431, -0.0013, -0.0482 ],
    [ 0.0383, 0.0431, 0.3030, 0.0110, -0.3540 ],
    [ -0.0011, -0.0013, 0.0110, 0.0040, 0.0023 ],
    [ -0.0925, -0.0482, -0.3540, 0.0023, 0.7273 ],
]
f[PNOISE] = 0.1399

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-881.0061

Final fitted objective value

-912.2423

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 1 0.102 0.2 49.03% 9.81e-02
f[CL] 1 2.15 2 7.64% 1.53e-01
f[V1] 20 24.1 50 51.73% 2.59e+01
f[Q] 0.5 1.95 1 95.47% 9.55e-01
f[V2] 100 61.8 80 22.79% 1.82e+01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE] 0.1 0.14 0.15 6.75% 1.01e-02

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA_isv] 0.05 0.0322 0.1 67.82% 6.78e-02
f[KA_isv;CL_isv] 0.01 0.0145 0.01 44.70% 4.47e-03
f[KA_isv;V1_isv] 0.01 0.0383 0.01 282.65% 2.83e-02
f[KA_isv;Q_isv] 0.01 -0.00113 0.01 111.27% 1.11e-02
f[KA_isv;V2_isv] 0.01 -0.0925 0.01 1024.60% 1.02e-01
f[CL_isv;KA_isv] 0.01 0.0145 0.01 44.70% 4.47e-03
f[CL_isv] 0.05 0.0165 0.03 45.11% 1.35e-02
f[CL_isv;V1_isv] 0.01 0.0431 -0.01 531.18% 5.31e-02
f[CL_isv;Q_isv] 0.01 -0.00129 0.02 106.45% 2.13e-02
f[CL_isv;V2_isv] 0.01 -0.0482 0.02 341.00% 6.82e-02
f[V1_isv;KA_isv] 0.01 0.0383 0.01 282.65% 2.83e-02
f[V1_isv;CL_isv] 0.01 0.0431 -0.01 531.18% 5.31e-02
f[V1_isv] 0.05 0.303 0.09 236.64% 2.13e-01
f[V1_isv;Q_isv] 0.01 0.011 0.01 9.74% 9.74e-04
f[V1_isv;V2_isv] 0.01 -0.354 0.01 3639.98% 3.64e-01
f[Q_isv;KA_isv] 0.01 -0.00113 0.01 111.27% 1.11e-02
f[Q_isv;CL_isv] 0.01 -0.00129 0.02 106.45% 2.13e-02
f[Q_isv;V1_isv] 0.01 0.011 0.01 9.74% 9.74e-04
f[Q_isv] 0.05 0.00401 0.07 94.27% 6.60e-02
f[Q_isv;V2_isv] 0.01 0.00233 0.01 76.75% 7.67e-03
f[V2_isv;KA_isv] 0.01 -0.0925 0.01 1024.60% 1.02e-01
f[V2_isv;CL_isv] 0.01 -0.0482 0.02 341.00% 6.82e-02
f[V2_isv;V1_isv] 0.01 -0.354 0.01 3639.98% 3.64e-01
f[V2_isv;Q_isv] 0.01 0.00233 0.01 76.75% 7.67e-03
f[V2_isv] 0.05 0.727 0.05 1354.52% 6.77e-01
Back to Top