exponential_disease_progression_model
[Generated automatically as a Tutorial summary]
Model Description
- Name:
dp_exponential
- Title:
exponential_disease_progression_model
- Author:
Andrew Cristinacce @ PoPy for PK/PD
- Abstract:
Specifies both the pop_gen and pop_fit subscripts.
A exponential 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 compartment increases exponentially over time, but is initially reduced by the drug concentration.
- Keywords:
PD; Pharmacodynamics; one compartment model; exponential disease progression
- Input Script:
- Diagram:
Comparison
True objective value
86.0288
Final fitted objective value
83.4329
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[ALPHA] |
0.1 |
0.0671 |
0.05 |
1.71e-02 |
34.30% |
f[BETA] |
0.2 |
0.354 |
0.3 |
5.43e-02 |
18.10% |
f[ANOISE] |
2 |
2 |
1 |
1.00e+00 |
100.00% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[DIS_BASE] |
250 |
201 |
200 |
7.66e-01 |
0.38% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[DIS_BASE] = 200.7663
f[ALPHA] = 0.0671
f[BETA] = 0.3543
f[ANOISE] = 2.0000
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: exponential_disease_progression_model (gen)
Fit: exponential_disease_progression_model (fit)
Inputs
True f[X] values (for simulation)
f[DIS_BASE] = 200.0000
f[ALPHA] = 0.0500
f[BETA] = 0.3000
f[ANOISE] = 1.0000
Starting f[X] values (before fitting)
f[DIS_BASE] = 250.0000
f[ALPHA] = 0.1000
f[BETA] = 0.2000
f[ANOISE] = 2.0000