Bioavailability and Lag

[Generated automatically as a Fitting summary]

Inputs

Description

Name:biolag_abs_both
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_both_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

77.0130

which required 7 iterations and took 0.33 seconds

Final fitted fixed effects

f[KA] = 1.0000
f[CL] = 9.8758
f[V] = 99.3712
f[ANOISE_STD] = 1.3101
f[BIO] = 1.0000
f[LAG] = 16115163387053897220730226759446954961843257344.0000

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] 9.8758 1.0000 8.8758 8.8758
f[V] 99.3712 15.0000 5.6247 84.3712
f[BIO] 1.0000 1.0000 0.0000 0.0000
f[LAG] 16115163387099999137759327006320587064016371712.0000 1.0000 16115163387099999137759327006320587064016371712.0000 16115163387099999137759327006320587064016371712.0000

Compare Noise f[X]

Variable Name Fitted Value Starting Value Prop Change Abs Change
f[ANOISE_STD] 1.3101 5.0000 0.7380 3.6899

Compare Variance f[X]