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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

Generated data .csv file

Synthetic Data:synthetic_data.csv

Fitted f[X] values

f[KA] = 0.1209
f[CL] = 1.5555
f[V1] = 33.9425
f[Q] = 2.2223
f[V2] = 119.5563
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.0564, 0.0202, 0.0672, -0.0035, 0.0082 ],
    [ 0.0202, 0.1257, 0.1163, -0.0664, -0.2501 ],
    [ 0.0672, 0.1163, 0.2004, -0.0317, -0.1448 ],
    [ -0.0035, -0.0664, -0.0317, 0.0584, 0.2049 ],
    [ 0.0082, -0.2501, -0.1448, 0.2049, 0.7798 ],
]
f[PNOISE] = 0.1480

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-873.4691

Final fitted objective value

-887.8029

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA] 1 0.121 0.2 39.56% 7.91e-02
f[CL] 1 1.56 2 22.22% 4.44e-01
f[V1] 20 33.9 50 32.12% 1.61e+01
f[Q] 0.5 2.22 1 122.23% 1.22e+00
f[V2] 100 120 80 49.45% 3.96e+01

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[PNOISE] 0.1 0.148 0.15 1.37% 2.05e-03

Compare Variance f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[KA_isv] 0.05 0.0564 0.1 43.63% 4.36e-02
f[KA_isv;CL_isv] 0.01 0.0202 0.01 102.06% 1.02e-02
f[KA_isv;V1_isv] 0.01 0.0672 0.01 572.04% 5.72e-02
f[KA_isv;Q_isv] 0.01 -0.00347 0.01 134.71% 1.35e-02
f[KA_isv;V2_isv] 0.01 0.00815 0.01 18.48% 1.85e-03
f[CL_isv;KA_isv] 0.01 0.0202 0.01 102.06% 1.02e-02
f[CL_isv] 0.05 0.126 0.03 319.06% 9.57e-02
f[CL_isv;V1_isv] 0.01 0.116 -0.01 1262.61% 1.26e-01
f[CL_isv;Q_isv] 0.01 -0.0664 0.02 431.93% 8.64e-02
f[CL_isv;V2_isv] 0.01 -0.25 0.02 1350.57% 2.70e-01
f[V1_isv;KA_isv] 0.01 0.0672 0.01 572.04% 5.72e-02
f[V1_isv;CL_isv] 0.01 0.116 -0.01 1262.61% 1.26e-01
f[V1_isv] 0.05 0.2 0.09 122.68% 1.10e-01
f[V1_isv;Q_isv] 0.01 -0.0317 0.01 417.25% 4.17e-02
f[V1_isv;V2_isv] 0.01 -0.145 0.01 1547.50% 1.55e-01
f[Q_isv;KA_isv] 0.01 -0.00347 0.01 134.71% 1.35e-02
f[Q_isv;CL_isv] 0.01 -0.0664 0.02 431.93% 8.64e-02
f[Q_isv;V1_isv] 0.01 -0.0317 0.01 417.25% 4.17e-02
f[Q_isv] 0.05 0.0584 0.07 16.53% 1.16e-02
f[Q_isv;V2_isv] 0.01 0.205 0.01 1949.01% 1.95e-01
f[V2_isv;KA_isv] 0.01 0.00815 0.01 18.48% 1.85e-03
f[V2_isv;CL_isv] 0.01 -0.25 0.02 1350.57% 2.70e-01
f[V2_isv;V1_isv] 0.01 -0.145 0.01 1547.50% 1.55e-01
f[V2_isv;Q_isv] 0.01 0.205 0.01 1949.01% 1.95e-01
f[V2_isv] 0.05 0.78 0.05 1459.52% 7.30e-01
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