Bioavailability and Lag

[Generated automatically as a Fitting summary]

Model Description

Name:

biolag_base

Title:

Bioavailability and Lag

Author:

PoPy for PK/PD

Abstract:

One compartment model with bioavailability and lag parameters.

Keywords:

identifiability; bioavailability; lag; iv_one_cmp_cl

Input Script:

biolag_base_fit.pyml

Diagram:

Comparison

Compare Main f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[CL]	1.0000	2.0846	1.0846	1.0846
f[V]	15.0000	11.2540	3.7460	0.2497
f[BIO]	0.8000	0.7998	0.0002	0.0003
f[LAG]	1.0000	0.0204	0.9796	0.9796

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[ANOISE_STD]	5.0000	0.9211	4.0789	0.8158

Compare Variance f[X]

Population simulated (sim) plots

indOBS_vs_TIME

Outputs

Final objective value

83.5562

which required 1.12 iterations and took 10.76 seconds

Fitted f[X] values (after fitting)

f[CL] = 2.0846
f[V] = 11.2540
f[ANOISE_STD] = 0.9211
f[BIO] = 0.7998
f[LAG] = 0.0204

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