• Language: en
  • Documentation version: 1.3.1

emax_marker_model

[Generated automatically as a Tutorial summary]

Model Description

Name:

emax_biomarker

Title:

emax_marker_model

Author:

PoPy for PK/PD

Abstract:

An emax 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 estimated for each individual.
The concentration in the central compartment influences the rate of removal of a biomarker (KOUT).
Keywords:

PD; Pharmacodynamics; one compartment model; KIN; KOUT; emax; biomarker

Input Script:

emax_biomarker.pyml

Diagram:

Comparison

True objective value

86.0288

Final fitted objective value

193.0522

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[KIN]

15

87.8

10

7.78e+01

778.47%

f[KOUT]

0.1

0.049

0.05

9.90e-04

1.98%

f[EMAX]

90

27.3

80

5.27e+01

65.84%

f[E50]

25

95.9

30

6.59e+01

219.82%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[ANOISE]

5

1.61

1

6.07e-01

60.65%

Compare Variance f[X]

No Variance f[X] values to compare.

Outputs

Fitted f[X] values (after fitting)

f[KIN] = 87.8471
f[KOUT] = 0.0490
f[EMAX] = 27.3312
f[E50] = 95.9468
f[ANOISE] = 1.6065

Generated data .csv file

Synthetic Data:

synthetic_data.csv

Gen and Fit Summaries

Inputs

True f[X] values (for simulation)

f[KIN] = 10.0000
f[KOUT] = 0.0500
f[EMAX] = 80.0000
f[E50] = 30.0000
f[ANOISE] = 1.0000

Starting f[X] values (before fitting)

f[KIN] = 15.0000
f[KOUT] = 0.1000
f[EMAX] = 90.0000
f[E50] = 25.0000
f[ANOISE] = 5.0000
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