• Language: en
  • Documentation version: 1.3.1

Indirect PKPD Model

[Generated automatically as a Generation summary]

Model Description

Name:

indirect_pd

Title:

Indirect PKPD Model

Author:

PoPy for PK/PD

Abstract:

A indirect 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_gen.pyml

Diagram:

Outputs

Population simulated (sim) plots

indOBS_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[BASE] = 800.0000
f[KOUT] = 0.0300
f[ANOISE] = 0.5000
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