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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
f[INT] = 16
f[KOUT] = 0.1
f[ANOISE] = 5

Outputs

Final objective value

812.580774422

which required N. iterations and took 907.43 seconds

Final fitted fixed effects

f[AMP] = 1.9959
f[INT] = 19.845
f[KOUT] = 0.049823
f[ANOISE] = 2.9042

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] 1.99585 3 0.334716 1.00415
f[INT] 19.845 16 0.240312 3.84499
f[KOUT] 0.0498227 0.1 0.501773 0.0501773

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE] 2.90424 5 0.419152 2.09576

Compare Variance f[X]

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