# 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

    811.9734

which required 1.24 iterations and took 14.40 seconds

### Final fitted fixed effects

    f[AMP] = 2.0055
    f[INT] = 7.8725
    f[KOUT] = 0.0501
    f[ANOISE] = 3.0838

### 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 | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[AMP] | 3.0000 | 2.0055 | 0.3315 | 0.9945
f[INT] | 16.0000 | 7.8725 | 0.5080 | 8.1275
f[KOUT] | 0.1000 | 0.0501 | 0.4989 | 0.0499

### Compare Noise f[X]

Variable Name | Starting Value | Fitted Value | Prop Change | Abs Change
--- | --- | --- | --- | ---
f[ANOISE] | 5.0000 | 3.0838 | 0.3832 | 1.9162

### Compare Variance f[X]