Emax PD Model

[Generated automatically as a Fitting summary]

Model Description

Name:: emax_simple
Title:: Emax PD Model
Author:: PoPy for PK/PD
Abstract:

A simple emax PKPD Model, based on the amount of drug in the body.
The two compartment PK model uses previously estimated values of K, K21 and K12 for each individual
The amount in the central compartment influences the effect compartment along with EMAX (the maximum effect) and EC50 (the amount at which the effect is half the maximum)

Keywords:: PD; Pharmacodynamics; two compartment model; emax; EC50
Input Script:: emax_simple_fit.pyml
Diagram:

Comparison

Compare Main f[X]

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[EMAX]	100.0000	81.8815	18.1185	0.1812
f[E50]	50.0000	20.7067	29.2933	0.5859
f[ANOISE]	5.0000	0.9123	4.0877	0.8175

Compare Variance f[X]

Population simulated (sim) plots

indOBS_vs_TIME

Outputs

Final objective value

163.2858

which required 1.13 iterations and took 11.72 seconds

Fitted f[X] values (after fitting)

f[EMAX] = 81.8815
f[E50] = 20.7067
f[ANOISE] = 0.9123

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[EMAX] = 100.0000
f[E50] = 50.0000
f[ANOISE] = 5.0000