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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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