Mixture toxicity assessment is indeed necessary for humans and ecosystems that are contin ually exposed to a variety of chemical mixtures. This paper describes an R package, called mixtox, which offers a general framework of curve fitting, mixture experimental design, and mixture toxicity prediction for practitioners in toxicology. The unique features of mixtox include: (1) constructing a uniform table for mixture experimental design; and (2) predicting toxicity of a mixture with multiple components based on reference models such as concentration addition, independent action, and generalized concentration addition. We describe the various functions of the package and provide examples to illustrate their use and show the collaboration of mixtox with other existing packages (e.g., drc) in predicting toxicity of chemical mixtures.
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Zhu & Chen, "The R Journal: mixtox: An R Package for Mixture Toxicity Assessment", The R Journal, 2016
BibTeX citation
@article{RJ-2016-056,
author = {Zhu, Xiang-Wei and Chen, Jian-Yi},
title = {The R Journal: mixtox: An R Package for Mixture Toxicity Assessment},
journal = {The R Journal},
year = {2016},
note = {https://doi.org/10.32614/RJ-2016-056},
doi = {10.32614/RJ-2016-056},
volume = {8},
issue = {2},
issn = {2073-4859},
pages = {421-433}
}