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Sine circadian model

[Generated automatically as a Fitting summary]

Inputs

Description

Name:circ_sin
Title:Sine circadian model
Author:Wright Dose Ltd
Abstract:
A PD Model based on the amount of drug in the body.
The PD model uses a sine 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 patameters , which have been previosly estimated for each individual.
The amount in the central compartment influences the rate of production of a biomarker.
Keywords:PD; Pharmacodynamics; sine function; Circadian rhythm
Input Script:circ_sin_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

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

Outputs

Final objective value

1174.9538

which required N. iterations and took 5.98 seconds

Final fitted fixed effects

f[AMP] = 2.0017
f[INT] = 19.8701
f[KOUT] = 0.0500
f[ANOISE] = 10.0000

Fitted parameter .csv files

Fixed Effects:fx_params.csv (fit)
Random Effects:rx_params.csv (fit)
Model params:mx_params.csv (fit)
State values:sx_params.csv (fit)
Predictions:px_params.csv (fit)

Plots

Dense sim plots

Alternatively see All dense_sim graph plots

Comparison

Compare Main f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[AMP] 2.0017 3.0000 0.3328 0.9983
f[INT] 19.8701 16.0000 0.2419 3.8701
f[KOUT] 0.0500 0.1000 0.5001 0.0500

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE] 10.0000 5.0000 1.0000 5.0000

Compare Variance f[X]

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