Cosine circadian model

[Generated automatically as a Tutorial summary]

Model Description

Name:

circ_cos

Title:

Cosine circadian model

Author:

PoPy for PK/PD

Abstract:

A PD Model based on the concentration of drug in the body.
The PD model uses a cosine function which simulates a circadian rhythm for the generation of a biomarker.
The amount in the central compartment is determined by CL and V, PK parameters, which have been estimated for each individual.
The concentration in the central compartment influences the rate of removal of a biomarker (KOUT).
Keywords:

PD; Pharmacodynamics; cosine function; Circadian rhythm

Input Script:

circ_cos_tut.pyml

Diagram:

Comparison

True objective value

815.0562

Final fitted objective value

813.7698

Compare Main f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[AMP]

3

2.01

2

7.66e-03

0.38%

f[INT]

16

20

8

1.20e+01

150.46%

f[KOUT]

0.1

0.0502

0.05

1.52e-04

0.30%

Compare Noise f[X]

Name

Initial

Fitted

True

Abs. Error

Prop. Error

f[ANOISE]

5

3.09

3

8.88e-02

2.96%

Compare Variance f[X]

No Variance f[X] values to compare.

Outputs

Fitted f[X] values (after fitting)

f[AMP] = 2.0077
f[INT] = 20.0368
f[KOUT] = 0.0502
f[ANOISE] = 3.0888

Generated data .csv file

Synthetic Data:

synthetic_data.csv

Gen and Fit Summaries

Inputs

True f[X] values (for simulation)

f[AMP] = 2.0000
f[INT] = 8.0000
f[KOUT] = 0.0500
f[ANOISE] = 3.0000

Starting f[X] values (before fitting)

f[AMP] = 3.0000
f[INT] = 16.0000
f[KOUT] = 0.1000
f[ANOISE] = 5.0000