Indirect_PKPD_model

[Generated automatically as a Generation summary]

Model Description

Name:: indirect_pd_pop
Title:: Indirect_PKPD_model
Author:: PoPy for PK/PD
Abstract:

A indirect (i.e. uses delay compartments) PD Model, based on the amount of drug in the body, delayed by two lag compartments
The amount in the central compartment is determined by K, which has been estimated for each individual.
The amount in the central compartment influences the rate of removal of a biomarker (KOUT).

Keywords:: pd; one compartment model; indirect; delay compartment
Input Script:: indirect_pd_pop_gen.pyml
Diagram:

Outputs

Individual simulated (sim) plots

Alternatively see All simulated_sim graph plots

Population simulated (sim) plots

(No population graphs were requested.)

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[BASE] = 800.0000
f[KOUT] = 0.0300
f[PNOISE] = 0.1000
f[ANOISE] = 0.5000
f[BASE_isv,KOUT_isv] = [
    [ 0.0500, 0.0000 ],
    [ 0.0000, 0.0100 ],
]