- Language: en
Direct PD Model¶
[Generated automatically as a Fitting 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_fit.pyml |
| Input Data: | synthetic_data.csv |
| Diagram: |
Initial fixed effect estimates¶
f[BASE] = 500
f[KOUT] = 0.1
f[ANOISE] = 5
Outputs¶
Final fitted fixed effects¶
f[BASE] = 800.04
f[KOUT] = 0.030005
f[ANOISE] = 0.4559
Fitted parameter .csv files¶
| Fixed Effects: | fx_params.csv (fit) |
|---|---|
| Random Effects: | rx_params.csv (fit) |
| Model params: | mx_params.csv (fit) |
| State values: | sx_params.csv (fit) |
| Predictions: | px_params.csv (fit) |
Plots¶
Comparison¶
Compare Main f[X]¶
| Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[BASE] | 800.044 | 500 | 0.600087 | 300.044 |
| f[KOUT] | 0.0300054 | 0.1 | 0.699946 | 0.0699946 |
Compare Noise f[X]¶
| Variable Name | Fitted Value | Starting Value | Prop Change | Abs Change |
|---|---|---|---|---|
| f[ANOISE] | 0.455905 | 5 | 0.908819 | 4.5441 |