Bioavailability and Lag

[Generated automatically as a Fitting summary]

Inputs

Description

Name:biolag_abs_bio
Title:Bioavailability and Lag
Author:Wright Dose Ltd
Abstract:
One compartment model absorption dosing with bioavailability and lag parameters.
Keywords:identifiability; bioavailability; lag
Input Script:biolag_abs_bio_fit.pyml
Input Data:synthetic_data.csv
Diagram:

Initial fixed effect estimates

f[KA] = 0.5000
f[CL] = 1.0000
f[V] = 15.0000
f[ANOISE_STD] = 5.0000
f[BIO] = 0.8000
f[LAG] = 1.0000

Outputs

Final objective value

61.1707

which required N. iterations and took 0.72 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 7.9815
f[V] = 88.3378
f[ANOISE_STD] = 1.1181
f[BIO] = 0.0000
f[LAG] = 556991931180618173920440774875204562471103574122168320.0000

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[KA] 1.0000 0.5000 1.0000 0.5000
f[CL] 7.9815 1.0000 6.9815 6.9815
f[V] 88.3378 15.0000 4.8892 73.3378
f[BIO] 0.0000 0.8000 1.0000 0.8000
f[LAG] 556991931180999970736126067831210468780642018055421952.0000 1.0000 556991931180999970736126067831210468780642018055421952.0000 556991931180999970736126067831210468780642018055421952.0000

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE_STD] 1.1181 5.0000 0.7764 3.8819

Compare Variance f[X]