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Direct PD Model

[Generated automatically as a Tutorial summary]

Model Description

Name:direct_pd
Title:Direct PD Model
Author:PoPy for PK/PD
Abstract:
A simple direct PD Model, based on the amount of drug in the body.
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_tut.pyml
Diagram:

Comparison

True objective value

-52.6006

Final fitted objective value

460.5766

Compare Main f[X]

Name Initial Fitted True Abs. Error Prop. Error
f[BASE] 500 800… 800 4.99e-02 0.01%
f[KOUT] 0.1 0.03… 0.03 5.52e-06 0.02%

Compare Noise f[X]

Name Initial Fitted True Abs. Error Prop. Error
f[ANOISE] 5 9.99 0.5 9.49e+00 1898.45%

Compare Variance f[X]

No Variance f[X] values to compare.

Outputs

Fitted f[X] values (after fitting)

f[BASE] = 800.0499
f[KOUT] = 0.0300
f[ANOISE] = 9.9922

Generated data .csv file

Synthetic Data:synthetic_data.csv

Gen and Fit Summaries

Inputs

True f[X] values (for simulation)

f[BASE] = 800.0000
f[KOUT] = 0.0300
f[ANOISE] = 0.5000

Starting f[X] values (before fitting)

f[BASE] = 500.0000
f[KOUT] = 0.1000
f[ANOISE] = 5.0000
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