Bayesian Benchmark Dose (BBMD) is a Python package for conducting benchmark dose-response modeling for continuous and dichotomous Bayesian models using the Stan probabilistic programming language. This repository includes source code for:
- statistical implementation of Bayesian benchmark dose analysis of dose-response datasets,
- estimation of benchmark dose values using central tendency and hybrid methods, and
- reporting of results in multiple formats (Microsoft Word, Excel, txt, and JSON).
Details on the BBMD modeling system, and performance comparison to other tools such as the US EPA Benchmark Dose Modeling Software (BMDS) is documented in a peer-reviewed publication coming soon [submitted; reference coming soon].
For more details on BBMD including installation, quickstart, and developer documentation, see the documentation section of the github repository. A companion project which wraps this software with a web-base graphical user-interface around the software is available in the bbmd-web repository.
Written by Kan Shao; implemented by Andy Shapiro.