tumour_growth_model
[Generated automatically as a Tutorial summary]
Model Description
- Name:
dp_tumour
- Title:
tumour_growth_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; absorption; tumour growth
- Input Script:
- Diagram:
Comparison
True objective value
-53.0825
Final fitted objective value
-55.1167
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KIN] |
0.05 |
0.0246 |
0.02 |
4.56e-03 |
22.80% |
f[KOUT] |
0.1 |
0.0529 |
0.05 |
2.88e-03 |
5.75% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[ANOISE] |
0.2 |
0.46 |
0.5 |
3.96e-02 |
7.92% |
Compare Variance f[X]
No Variance f[X] values to compare.
Outputs
Fitted f[X] values (after fitting)
f[KIN] = 0.0246
f[KOUT] = 0.0529
f[ANOISE] = 0.4604
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: tumour_growth_model (gen)
Fit: tumour_growth_model (fit)
Inputs
True f[X] values (for simulation)
f[KIN] = 0.0200
f[KOUT] = 0.0500
f[ANOISE] = 0.5000
Starting f[X] values (before fitting)
f[KIN] = 0.0500
f[KOUT] = 0.1000
f[ANOISE] = 0.2000