:orphan: 





.. _dp_iov_gen:



Disease progression with inter-occasional variance
##################################################

[Generated automatically as a Generation summary]

Model Description
*****************


:Name: dp_iov

:Title: Disease progression with inter-occasional variance

:Author: Andrew Cristinacce @ PoPy for PK/PD

:Abstract: 

| Specifies both the pop_gen and pop_fit subscripts.
| Drug concentration defined by one compartment model with first order absorption, using pre-defined PK parameters.
| Individuals are split into four dose groups.
| The concentration in the CENTRAL compartment affects the drug effect, which is an emax model.
| The disease progression model is affected by the concentration. Higher concentrations reduce the disease status
| Inter-occasional variance is included in the LEVEL_PARAMS section and includes 3 occasions.

:Keywords: one compartment model; iov; inter occasional variance; emax; absorption

:Input Script: :download:`dp_iov_gen.pyml <dp_iov_gen.pyml>`

:Diagram: 


.. thumbnail:: dp_iov_gen.pyml_output/compartment_diagram.svg
    :width: 200px


Outputs
*******



Individual simulated (sim) plots
================================



.. thumbnail:: images/gen_sim_grph_outputs/indOBS_vs_TIME/000001.svg
    :width: 200px


.. thumbnail:: images/gen_sim_grph_outputs/indOBS_vs_TIME/000002.svg
    :width: 200px


.. thumbnail:: images/gen_sim_grph_outputs/indOBS_vs_TIME/000003.svg
    :width: 200px


Alternatively see :ref:`dp_iov_simulated_sim_plots`

Population simulated (sim) plots
================================


(No population graphs were requested.)

Generated parameter .csv files
==============================


:Fixed Effects: :download:`fx_params.csv (gen) <dp_iov_gen.pyml_output/fx_params.csv>`

:Random Effects: :download:`rx_params.csv (gen) <dp_iov_gen.pyml_output/rx_params.csv>`

:Model params: :download:`mx_params.csv (gen) <dp_iov_gen.pyml_output/mx_params.csv>`

:State values: :download:`sx_params.csv (gen) <dp_iov_gen.pyml_output/sx_params.csv>`

:Predictions: :download:`px_params.csv (gen) <dp_iov_gen.pyml_output/px_params.csv>`


:Observations: :download:`synthetic_data.csv (gen) <synthetic_data.csv>`


Inputs
******



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


.. code-block:: pyml

    f[BASE] = 400.0000
    f[ALPHA] = 0.0250
    f[EMAX] = 0.4000
    f[EC50] = 1.8000
    f[ANOISE] = 0.1000
    f[BASE_isv,ALPHA_isv,EC50_isv] = [
        [ 0.1000, 0.0000, 0.0000 ],
        [ 0.0000, 0.0500, 0.0000 ],
        [ 0.0000, 0.0000, 0.9000 ],
    ]
    f[BASE_iov,ALPHA_iov] = [
        [ 0.0300, 0.0000 ],
        [ 0.0000, 0.0200 ],
    ]

