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Body Weight Covariate

[Generated automatically as a Generation summary]

Model Description

Name:weight_covariate
Title:Body Weight Covariate
Author:PoPy for PK/PD
Abstract:
One compartment model with absorption compartment and CL/V parametrisation.
There are no random effects here. Each individual just has a different weight.
The weight is a covariate for the m[CL] clearance parameter for each individual.
Only the f[WT_EFFECT] and f[V] fixed effect parameters are estimated, other f[X] are fixed.
Keywords:one compartment model; dep_one_cmp_cl; weight; covariate effect
Input Script:weight_covariate_gen.pyml
Diagram:

Outputs

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

allOBS_vs_TIME

Generated parameter .csv files

Fixed Effects:fx_params.csv (gen)
Random Effects:rx_params.csv (gen)
Model params:mx_params.csv (gen)
State values:sx_params.csv (gen)
Predictions:px_params.csv (gen)
Observations:synthetic_data.csv (gen)

Inputs

True f[X] values (for simulation)

f[KA] = 0.3000
f[CL] = 3.0000
f[V] = 20.0000
f[PNOISE] = 0.1000
f[ANOISE] = 0.0500
f[WT_EFFECT] = 0.7500
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