First order absorption model with peripheral compartment

[Generated automatically as a Tutorial summary]

Model Description

Name:: builtin_tut_example
Title:: First order absorption model with peripheral compartment
Author:: PoPy for PK/PD
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:

Comparison

True objective value

-847.4635

Final fitted objective value

-863.1496

Compare Main f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KA]	1	0.215	0.2	1.48e-02	7.41%
f[CL]	1	1.79	2	2.10e-01	10.52%
f[V1]	20	55.5	50	5.46e+00	10.92%
f[Q]	0.5	1.06	1	5.64e-02	5.64%
f[V2]	100	487	80	4.07e+02	508.21%

Compare Noise f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[PNOISE]	0.1	0.142	0.15	8.50e-03	5.67%

Compare Variance f[X]

Name	Initial	Fitted	True	Abs. Error	Prop. Error
f[KA_isv]	0.05	0.139	0.1	3.93e-02	39.25%
f[KA_isv;CL_isv]	0.01	-0.0553	0.01	6.53e-02	653.38%
f[KA_isv;V1_isv]	0.01	0.0414	0.01	3.14e-02	314.14%
f[KA_isv;Q_isv]	0.01	-0.0256	0.01	3.56e-02	356.13%
f[KA_isv;V2_isv]	0.01	0.122	0.01	1.12e-01	1116.86%
f[CL_isv;KA_isv]	0.01	-0.0553	0.01	6.53e-02	653.38%
f[CL_isv]	0.05	0.0808	0.03	5.08e-02	169.21%
f[CL_isv;V1_isv]	0.01	-0.00702	-0.01	2.98e-03	29.83%
f[CL_isv;Q_isv]	0.01	-0.00606	0.02	2.61e-02	130.30%
f[CL_isv;V2_isv]	0.01	-0.178	0.02	1.98e-01	992.15%
f[V1_isv;KA_isv]	0.01	0.0414	0.01	3.14e-02	314.14%
f[V1_isv;CL_isv]	0.01	-0.00702	-0.01	2.98e-03	29.83%
f[V1_isv]	0.05	0.11	0.09	1.98e-02	21.97%
f[V1_isv;Q_isv]	0.01	-0.0827	0.01	9.27e-02	927.02%
f[V1_isv;V2_isv]	0.01	0.214	0.01	2.04e-01	2039.38%
f[Q_isv;KA_isv]	0.01	-0.0256	0.01	3.56e-02	356.13%
f[Q_isv;CL_isv]	0.01	-0.00606	0.02	2.61e-02	130.30%
f[Q_isv;V1_isv]	0.01	-0.0827	0.01	9.27e-02	927.02%
f[Q_isv]	0.05	0.317	0.07	2.47e-01	353.28%
f[Q_isv;V2_isv]	0.01	-0.324	0.01	3.34e-01	3339.14%
f[V2_isv;KA_isv]	0.01	0.122	0.01	1.12e-01	1116.86%
f[V2_isv;CL_isv]	0.01	-0.178	0.02	1.98e-01	992.15%
f[V2_isv;V1_isv]	0.01	0.214	0.01	2.04e-01	2039.38%
f[V2_isv;Q_isv]	0.01	-0.324	0.01	3.34e-01	3339.14%
f[V2_isv]	0.05	0.944	0.05	8.94e-01	1788.59%

Outputs

Fitted f[X] values (after fitting)

f[KA] = 0.2148
f[CL] = 1.7896
f[V1] = 55.4580
f[Q] = 1.0564
f[V2] = 486.5705
f[KA_isv,CL_isv,V1_isv,Q_isv,V2_isv] = [
    [ 0.1393, -0.0553, 0.0414, -0.0256, 0.1217 ],
    [ -0.0553, 0.0808, -0.0070, -0.0061, -0.1784 ],
    [ 0.0414, -0.0070, 0.1098, -0.0827, 0.2139 ],
    [ -0.0256, -0.0061, -0.0827, 0.3173, -0.3239 ],
    [ 0.1217, -0.1784, 0.2139, -0.3239, 0.9443 ],
]
f[PNOISE] = 0.1415

Generated data .csv file

Synthetic Data:: synthetic_data.csv

Gen and Fit Summaries

Gen: First order absorption model with peripheral compartment (gen)
Fit: First order absorption model with peripheral compartment (fit)

Inputs

True f[X] values (for simulation)

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 (before fitting)

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