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¶
-693.2829
Final fitted objective value¶
-701.3736
Compare Main f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[KA] | 1 | 0.21 | 0.2 | 1.04e-02 | 5.20% |
| f[CL] | 1 | 2.06 | 2 | 6.01e-02 | 3.00% |
| f[V1] | 20 | 47.8 | 50 | 2.16e+00 | 4.32% |
Compare Noise f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[PNOISE] | 0.1 | 0.151 | 0.15 | 1.28e-03 | 0.85% |
Compare Variance f[X]¶
| Name | Initial | Fitted | True | Abs. Error | Prop. Error |
|---|---|---|---|---|---|
| f[KA_isv] | 0.05 | 0.0597 | 0.1 | 4.03e-02 | 40.28% |
| f[KA_isv;CL_isv] | 0.01 | 0.00327 | 0.02 | 1.67e-02 | 83.65% |
| f[KA_isv;V1_isv] | 0.01 | 0.0142 | 0.01 | 4.18e-03 | 41.77% |
| f[CL_isv;KA_isv] | 0.01 | 0.00327 | 0.02 | 1.67e-02 | 83.65% |
| f[CL_isv] | 0.05 | 0.0319 | 0.03 | 1.93e-03 | 6.44% |
| f[CL_isv;V1_isv] | 0.01 | 0.00934 | 0.02 | 1.07e-02 | 53.32% |
| f[V1_isv;KA_isv] | 0.01 | 0.0142 | 0.01 | 4.18e-03 | 41.77% |
| f[V1_isv;CL_isv] | 0.01 | 0.00934 | 0.02 | 1.07e-02 | 53.32% |
| f[V1_isv] | 0.05 | 0.111 | 0.09 | 2.06e-02 | 22.90% |
Outputs¶
Fitted f[X] values (after fitting)¶
f[KA] = 0.2104
f[CL] = 2.0601
f[V1] = 47.8386
f[KA_isv,CL_isv,V1_isv] = [
[ 0.0597, 0.0033, 0.0142 ],
[ 0.0033, 0.0319, 0.0093 ],
[ 0.0142, 0.0093, 0.1106 ],
]
f[PNOISE] = 0.1513
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