- Language: en
Direct PD Model¶
[Generated automatically as a Tutorial summary]
Inputs¶
Description¶
Name: | direct_pd |
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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 |
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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 |
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Generating and Fitting Summaries¶
- Gen: Direct PD Model (gen)
- Fit: Direct PD Model (fit)
Fitted f[X] values¶
f[BASE] = 800.0443
f[KOUT] = 0.0300
f[ANOISE] = 10.0000
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.