• Language: en

Direct PD Model

[Generated automatically as a Tutorial summary]

Inputs

Description

Name:direct_pd
Title:Direct PD Model
Author:Wright Dose Ltd
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:

True f[X] values

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

Starting f[X] values

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

Outputs

Generated data .csv file

Synthetic Data:synthetic_data.csv

Generating and Fitting Summaries

Fitted f[X] values

f[BASE] = 800.0443
f[KOUT] = 0.0300
f[ANOISE] = 10.0000

Plots

Dense comp plots

Alternatively see All dense_comp graph plots

Comparison

True objective value

-52.6006

Final fitted objective value

460.7314

Compare Main f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[BASE] 500 800… 800 0.01% 4.43e-02
f[KOUT] 0.1 0.03… 0.03 0.02% 5.70e-06

Compare Noise f[X]

Name Initial Fitted True Prop. Error Abs. Error
f[ANOISE] 5 10 0.5 1900.00% 9.50e+00

Compare Variance f[X]

No Variance f[X] values to compare.

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