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Direct PD Model Simultaneous PK/PD Parameter fit

[Generated automatically as a Tutorial summary]

Model Description

Name:

direct_pd_simul

Title:

Direct PD Model Simultaneous PK/PD Parameter fit

Author:

PoPy for PK/PD

Abstract:

A simple direct PD Model, based on the amount of drug in the body. That simultaneously fits PK and PD parameters.
The amount in the central compartment is determined by K, which has been previously estimated for each individual.
The amount in the central compartment influences the rate of removal of a biomarker (KOUT).
Keywords:

pd; one compartment model; direct

Input Script:

direct_pd_simul_tut.pyml

Diagram:

Comparison

True objective value

-203.7595

Final fitted objective value

386.6144

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[CL]

5

2…

2

1.94e-03

0.10%

f[V]

15

48.1

50

1.91e+00

3.81%

f[BASE]

500

799

800

7.71e-01

0.10%

f[KOUT]

0.1

0.0288

0.03

1.23e-03

4.10%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[PK_ANOISE]

5

0.51

0.5

1.02e-02

2.05%

f[PD_ANOISE]

5

8.23

0.3

7.93e+00

2641.77%

Compare Variance f[X]

No Variance f[X] values to compare.

Outputs

Fitted f[X] values (after fitting)

f[CL] = 2.0019
f[V] = 48.0926
f[BASE] = 799.2292
f[KOUT] = 0.0288
f[PK_ANOISE] = 0.5102
f[PD_ANOISE] = 8.2253

Generated data .csv file

Synthetic Data:

synthetic_data.csv

Gen and Fit Summaries

Inputs

True f[X] values (for simulation)

f[CL] = 2.0000
f[V] = 50.0000
f[BASE] = 800.0000
f[KOUT] = 0.0300
f[PK_ANOISE] = 0.5000
f[PD_ANOISE] = 0.3000

Starting f[X] values (before fitting)

f[CL] = 5.0000
f[V] = 15.0000
f[BASE] = 500.0000
f[KOUT] = 0.1000
f[PK_ANOISE] = 5.0000
f[PD_ANOISE] = 5.0000
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