linear_disease_progression_model
[Generated automatically as a Tutorial summary]
Model Description
- Name:
dp_linear
- Title:
linear_disease_progression_model
- Author:
Andrew Cristinacce @ PoPy for PK/PD
- Abstract:
Specifies both the pop_gen and pop_fit subscripts.
A disease progression model, based on the concentration of drug in the central compartment.
The amount in the central compartment is determined by CL/V, which has been previously estimated for each individual.
The disease increases linearly over time, but is initially reduced by the drug concentration.
- Keywords:
PD; Pharmacodynamics; one compartment model; linear disease progression
- Input Script:
- Diagram:
Comparison
True objective value
86.0288
Final fitted objective value
85.3044
Compare Main f[X]
No Main f[X] values to compare.
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[ALPHA] |
0.2 |
0.301 |
0.3 |
1.40e-03 |
0.47% |
f[BETA] |
0.5 |
0.729 |
0.8 |
7.07e-02 |
8.83% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[ALPHA] = 0.3014
f[BETA] = 0.7293
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: linear_disease_progression_model (gen)
Fit: linear_disease_progression_model (fit)
Inputs
True f[X] values (for simulation)
f[ALPHA] = 0.3000
f[BETA] = 0.8000
Starting f[X] values (before fitting)
f[ALPHA] = 0.2000
f[BETA] = 0.5000