- Language: en
Depot + One compartment PK with BLQ
[Generated automatically as a Tutorial summary]
Model Description
- Name:
blq_pk
- Title:
Depot + One compartment PK with BLQ
- Author:
PoPy for PK/PD
- Abstract:
- Keywords:
tutorial; pk; advan4; dep_two_cmp; blq
- Input Script:
- Diagram:
Comparison
True objective value
-781.3723
Final fitted objective value
-786.5417
Compare Main f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA] |
1 |
0.206 |
0.2 |
6.03e-03 |
3.02% |
f[CL] |
1 |
2… |
2 |
1.29e-03 |
0.06% |
f[V1] |
20 |
51 |
50 |
9.53e-01 |
1.91% |
Compare Noise f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[PNOISE] |
0.1 |
0.147 |
0.15 |
3.06e-03 |
2.04% |
Compare Variance f[X]
Name |
Initial |
Fitted |
True |
Abs. Error |
Prop. Error |
|---|---|---|---|---|---|
f[KA_isv] |
0.05 |
0.0532 |
0.1 |
4.68e-02 |
46.84% |
f[KA_isv;CL_isv] |
0.01 |
0.0111 |
0.02 |
8.87e-03 |
44.34% |
f[KA_isv;V1_isv] |
0.01 |
-0.0286 |
0.01 |
3.86e-02 |
386.23% |
f[CL_isv;KA_isv] |
0.01 |
0.0111 |
0.02 |
8.87e-03 |
44.34% |
f[CL_isv] |
0.05 |
0.0289 |
0.03 |
1.11e-03 |
3.70% |
f[CL_isv;V1_isv] |
0.01 |
0.0239 |
0.02 |
3.94e-03 |
19.69% |
f[V1_isv;KA_isv] |
0.01 |
-0.0286 |
0.01 |
3.86e-02 |
386.23% |
f[V1_isv;CL_isv] |
0.01 |
0.0239 |
0.02 |
3.94e-03 |
19.69% |
f[V1_isv] |
0.05 |
0.0642 |
0.09 |
2.58e-02 |
28.72% |
Outputs
Fitted f[X] values (after fitting)
f[KA] = 0.2060
f[CL] = 1.9987
f[V1] = 50.9527
f[KA_isv,CL_isv,V1_isv] = [
[ 0.0532, 0.0111, -0.0286 ],
[ 0.0111, 0.0289, 0.0239 ],
[ -0.0286, 0.0239, 0.0642 ],
]
f[PNOISE] = 0.1469
f[ANOISE] = 0.0100
Generated data .csv file
- Synthetic Data:
Gen and Fit Summaries
Gen: Depot + One compartment PK with BLQ (gen)
Fit: Depot + One compartment PK with BLQ (fit)
Inputs
True f[X] values (for simulation)
f[KA] = 0.2000
f[CL] = 2.0000
f[V1] = 50.0000
f[KA_isv,CL_isv,V1_isv] = [
[ 0.1000, 0.0200, 0.0100 ],
[ 0.0200, 0.0300, 0.0200 ],
[ 0.0100, 0.0200, 0.0900 ],
]
f[PNOISE] = 0.1500
f[ANOISE] = 0.0100
Starting f[X] values (before fitting)
f[KA] = 1.0000
f[CL] = 1.0000
f[V1] = 20.0000
f[KA_isv,CL_isv,V1_isv] = [
[ 0.0500, 0.0100, 0.0100 ],
[ 0.0100, 0.0500, 0.0100 ],
[ 0.0100, 0.0100, 0.0500 ],
]
f[PNOISE] = 0.1000
f[ANOISE] = 0.0100