.. _indiv_pkpd_index:

Principles of Pharmacokinetics
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Pharmacokinetics is the study of the time profile of drugs and metabolites in a physiological organism. It is often described as "what the body does to the drug". Generally, our goal is to predict a time course of drug concentration that resembles the observations we have collected from an individual. (Observations from a population are covered in :ref:`pop_pkpd_index`.)


.. comment
    and pharmacodynamics - "what the drug does to the body" - is covered in :ref:`indiv_pd_index`.

To make these predictions we build a mathematical model that, for an individual, has two main components: 

#. A deterministic structural model with parameters that define the shape of the time course
#. A stochastic residual error model that specifies how observations deviate from the deterministic predictions

* [MouldUpton2012]_
* [MouldUpton2013]_
* [UptonMould2013]_
* [RowlandTozer2012]_

This part of the book provides a detailed description of how various pharmacokinetic (PK) models are implemented in PoPy. It assumes no prior knowledge of PK, hence experienced modellers may be tempted to skip this section. It is, however, probably valuable to look at the syntax for absorption models, particular the Weibull model, which is not available in other population modelling software.

.. toctree::
    :maxdepth: 1

    elimination
    compartment_models
    dosing_examples
    error_models

    computational_considerations
    uncertainty

.. comment
    identifiability        
