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: |
Depot One Comp PK model, with BLQ (below level of quantification) observations.
| Keywords: | tutorial; pk; advan4; dep_two_cmp; blq |
|---|---|
| Input Script: | blq_pk_tut.pyml |
| Diagram: |
Comparison¶
True objective value¶
-756.5645
Final fitted objective value¶
-763.9922
Compare Main f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[KA] | 1 | 0.195 | 0.2 | 4.50e-03 | 2.25% |
| f[CL] | 1 | 2.02 | 2 | 2.48e-02 | 1.24% |
| f[V1] | 20 | 47 | 50 | 3.03e+00 | 6.06% |
Compare Noise f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[PNOISE] | 0.1 | 0.139 | 0.15 | 1.11e-02 | 7.41% |
Compare Variance f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[KA_isv] | 0.05 | 0.137 | 0.1 | 3.74e-02 | 37.35% |
| f[KA_isv;CL_isv] | 0.01 | 0.0156 | 0.02 | 4.45e-03 | 22.23% |
| f[KA_isv;V1_isv] | 0.01 | 0.0621 | 0.01 | 5.21e-02 | 520.97% |
| f[CL_isv;KA_isv] | 0.01 | 0.0156 | 0.02 | 4.45e-03 | 22.23% |
| f[CL_isv] | 0.05 | 0.0392 | 0.03 | 9.16e-03 | 30.52% |
| f[CL_isv;V1_isv] | 0.01 | 0.0199 | 0.02 | 1.34e-04 | 0.67% |
| f[V1_isv;KA_isv] | 0.01 | 0.0621 | 0.01 | 5.21e-02 | 520.97% |
| f[V1_isv;CL_isv] | 0.01 | 0.0199 | 0.02 | 1.34e-04 | 0.67% |
| f[V1_isv] | 0.05 | 0.126 | 0.09 | 3.55e-02 | 39.50% |
Outputs¶
Fitted f[X] values (after fitting)¶
f[KA] = 0.1955
f[CL] = 2.0248
f[V1] = 46.9689
f[KA_isv,CL_isv,V1_isv] = [
[ 0.1374, 0.0156, 0.0621 ],
[ 0.0156, 0.0392, 0.0199 ],
[ 0.0621, 0.0199, 0.1255 ],
]
f[PNOISE] = 0.1389
f[ANOISE] = 0.0100
Generated data .csv file¶
| Synthetic Data: | synthetic_data.csv |
|---|
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