Direct Effect Emax PD Model

[Generated automatically as a Fitting summary]

Model Description

Name:

emax_nondiff

Title:

Direct Effect Emax PD Model

Author:

PoPy for PK/PD

Abstract:

A direct effect emax PK/PD Model, based on the concentration of drug in the body.

The one compartment PK model uses previously estimated values of CL and V for each individual

The concentration in the central compartment influences the effect.

The effect is not a compartment and so does not increase over time. It is dependent on the baseline effect, the concentration in the central compartment, the maximum effect (emax) and concentration at which the effect is half the maximum (EC50).

Keywords:

PD; Pharmacodynamics; one compartment model; emax; EC50; baseline effect

Input Script:

emax_nondiff_fit.pyml

Diagram:

Comparison

Compare Main f[X]

Compare Noise f[X]

Variable Name	Starting Value	Fitted Value	Abs Change	Prop Change
f[EMAX]	80.0000	522.6699	442.6699	5.5334
f[E50]	50.0000	322.8391	272.8391	5.4568
f[EBASE]	5.0000	10.0149	5.0149	1.0030
f[ANOISE]	2.0000	0.4602	1.5398	0.7699

Compare Variance f[X]

Population simulated (sim) plots

indOBS_vs_TIME

Outputs

Final objective value

-54.8713

which required 1.30 iterations and took 11.02 seconds

Fitted f[X] values (after fitting)

f[EMAX] = 522.6699
f[E50] = 322.8391
f[EBASE] = 10.0149
f[ANOISE] = 0.4602

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] = 80.0000
f[E50] = 50.0000
f[EBASE] = 5.0000
f[ANOISE] = 2.0000