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Chi is an open source Python package for pharmacokinetic and pharmacodynamic (PKPD) modelling.
All features of the software are described in detail in the full API documentation.
- Install sundials
Chi uses the open source package Myokit to solve ordinary differential equations and compute their sensitivities efficiently. Myokit does this using sundials' CVODESS, which needs to be installed with:
- On Ubuntu:
apt-get install libsundials-dev- On MacOS:
brew install sundials- On Windows: No action required. Myokit will install sundial automatically.
- Install chi
pip install chi-drmYou can now use chi's functionality by importing it
import chiTutorials and more detailed explanations on how to use chi can be found in the documentation's getting started section.
If you use this software in your work, please cite it using the following metadata:
Augustin, D., (2024). Chi: A Python package for treatment response modelling. Journal of Open Source Software, 9(94), 5925, https://doi.org/10.21105/joss.05925
@article{
Augustin2024,
doi = {10.21105/joss.05925},
url = {https://doi.org/10.21105/joss.05925},
year = {2024},
publisher = {The Open Journal},
volume = {9},
number = {94},
pages = {5925},
author = {David Augustin},
title = {Chi: A Python package for treatment response modelling},
journal = {Journal of Open Source Software}
}
There are lots of ways how you can contribute to Chi's development, and you are welcome to join in! For example, you can report problems or make feature requests on the issues pages.
Similarly, if you would like to contribute documentation or code you can create and issue, and then provide a pull request for review. To facilitate contributions, we have written extensive contribution guidelines to help you navigate the code.