- Language: en
Sine circadian model¶
[Generated automatically as a Fitting summary]
Model Description¶
| Name: | circ_sin |
|---|---|
| Title: | Sine circadian model |
| Author: | PoPy for PK/PD |
| 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 |
| Diagram: |
Comparison¶
Compare Main f[X]¶
| Variable Name | Starting Value | Fitted Value | Abs Change | Prop Change |
|---|---|---|---|---|
| f[AMP] | 3.0000 | 2.0021 | 0.9979 | 0.3326 |
| f[INT] | 16.0000 | 7.8694 | 8.1306 | 0.5082 |
| f[KOUT] | 0.1000 | 0.0500 | 0.0500 | 0.5001 |
Compare Noise f[X]¶
| Variable Name | Starting Value | Fitted Value | Abs Change | Prop Change |
|---|---|---|---|---|
| f[ANOISE] | 5.0000 | 3.0706 | 1.9294 | 0.3859 |
Compare Variance f[X]¶
Population simulated (sim) plots¶
|
indOBS_vs_TIME |
Outputs¶
Fitted f[X] values (after fitting)¶
f[AMP] = 2.0021
f[INT] = 7.8694
f[KOUT] = 0.0500
f[ANOISE] = 3.0706
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) |
| Likelihoods: | lx_params.csv (fit) |
Inputs¶
| Input Data: | cx_obs_params.csv |
|---|
Starting f[X] values (before fitting)¶
f[AMP] = 3.0000
f[INT] = 16.0000
f[KOUT] = 0.1000
f[ANOISE] = 5.0000