pharmpy-core

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.. _README:

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Pharmpy is an open-source software package for pharmacometric modeling. It has functionality ranging from reading and manipulating model files and datasets to full tools where subsequent results are collected and presented.

Features include:

• A model abstraction which splits a model into core components which Pharmpy understands and can manipulate: parameters, random variables, statements (including ODE system), dataset, and execution steps
• An abstraction for modelfit results which splits a parsed results into core components: e.g. OFV, parameter estimates, relative standard errors (RSEs), residuals, predictions
• Functions for manipulation of models and datasets in the modeling-module: e.g. change structural model, add time-after-dose column, deidentify dataset
• Tools to aid model development in the tools-module: execution of models within Python/R scripts, automatic development of models (e.g. AMD, IIVSearch, RUVSearch), comparison of estimation methods
• Support for multiple estimation tools: parse NONMEM models, execute NONMEM, nlmixr2, and rxODE2 models, run all Pharmpy tools with NONMEM and some with nlmixr2

For more comprehensive information and documentation, see: https://pharmpy.github.io

Pharmpy can be used as a regular Python package, in R via the pharmr <https://github.com/pharmpy/pharmr>_ package, or via its built in command line interface.

Getting started

The sections below are intended as first steps, please check our website <https://pharmpy.github.io>_ website for more comprehensive documentation, such as user guides and API references.

Installation

For installation in R, see pharmr <https://github.com/pharmpy/pharmr>_.

Install the latest stable version from PyPI:

pip install pharmpy-core    # or 'pip3 install' if that is your default python3 pip

Python Example

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from pharmpy.modeling import read_model from pharmpy.tools import load_example_modelfit_results model = load_example_model("pheno") model.parameters value lower upper fix POP_CL 0.004693 0.00 ∞ False POP_VC 1.009160 0.00 ∞ False COVAPGR 0.100000 -0.99 ∞ False IIV_CL 0.030963 0.00 ∞ False IIV_VC 0.031128 0.00 ∞ False SIGMA 0.013086 0.00 ∞ False res = load_example_modelfit_results("pheno") res.parameter_estimates POP_CL 0.004696 POP_VC 0.984258 COVAPGR 0.158920 IIV_CL 0.029351 IIV_VC 0.027906 SIGMA 0.013241 Name: estimates, dtype: float64

CLI Example

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# Get help
pharmpy -h

# Remove first ID from dataset and save new model using new dataset
pharmpy data filter run1.mod 'ID!=1'

# Run tool for selecting IIV structure
pharmpy run iivsearch run1.mod

Contact

This is the team behind Pharmpy <https://pharmpy.github.io/latest/contributors.html>_

Please ask a question in an issue or contact one of the maintainers if you have any questions.

Contributing

If you interested in contributing to Pharmpy, you can find more information under Contribute <https://pharmpy.github.io/latest/contribute.html#contribute>_.