Bioavailability and Lag

[Generated automatically as a Fitting summary]

Inputs

Description

Name:biolag_abs_lag
Title:Bioavailability and Lag
Author:Wright Dose Ltd
Abstract:
One compartment model absorption dosing with bioavailability and lag parameters.
Keywords:identifiability; bioavailability; lag; dep_one_cmp_cl
Input Script:biolag_abs_lag_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] = 1.0000
f[LAG] = 1.0000

Outputs

Final objective value

38.5225

which required 7 iterations and took 0.86 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 3.2273
f[V] = 22.5113
f[ANOISE_STD] = 0.8915
f[BIO] = 1.0000
f[LAG] = 8.6654

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] 3.2273 1.0000 2.2273 2.2273
f[V] 22.5113 15.0000 0.5008 7.5113
f[BIO] 1.0000 1.0000 0.0000 0.0000
f[LAG] 8.6654 1.0000 7.6654 7.6654

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE_STD] 0.8915 5.0000 0.8217 4.1085

Compare Variance f[X]