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

61.1870

which required N. iterations and took 0.71 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 7.9400
f[V] = 88.2319
f[ANOISE_STD] = 1.1184
f[BIO] = 0.0000
f[LAG] = 339054187219277810501679236148306104705480707394240512.0000

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] 7.9400 1.0000 6.9400 6.9400
f[V] 88.2319 15.0000 4.8821 73.2319
f[BIO] 0.0000 0.8000 1.0000 0.8000
f[LAG] 339054187219000012484384155010196192260338597620613120.0000 1.0000 339054187219000012484384155010196192260338597620613120.0000 339054187219000012484384155010196192260338597620613120.0000

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE_STD] 1.1184 5.0000 0.7763 3.8816

Compare Variance f[X]