:orphan: 





.. _emax_simple_tut:



Emax PD Model
#############

[Generated automatically as a Tutorial 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: :download:`emax_simple.pyml <emax_simple.pyml>`

:Diagram: 


.. thumbnail:: compartment_diagram.svg
    :width: 200px


Comparison
**********



True objective value
====================


.. code-block:: pyml

    169.1186



Final fitted objective value
============================


.. code-block:: pyml

    163.2858



Compare Main f[X]
=================


No Main f[X] values to compare.

Compare Noise f[X]
==================



.. csv-table:: 
    :file: fx_comp_noise.csv
    :header-rows: 1


Compare Variance f[X]
=====================


No Variance f[X] values to compare.

Outputs
*******



Fitted f[X] values (after fitting)
==================================


.. code-block:: pyml

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



Generated data .csv file
========================


:Synthetic Data: :download:`synthetic_data.csv <synthetic_data.csv>`


Gen and Fit Summaries
=====================


* Gen: :ref:`emax_simple_gen` (gen)
* Fit: :ref:`emax_simple_fit` (fit)

Inputs
******



True f[X] values (for simulation)
=================================

.. code-block:: pyml

    f[EMAX] = 80.0000
    f[E50] = 20.0000
    f[ANOISE] = 1.0000



Starting f[X] values (before fitting)
=====================================

.. code-block:: pyml

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

