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bmd: an R package for benchmark dose estimation.

Signe M Jensen¹, Felix M Kluxen², Jens C Streibig¹

¹Department of Plant and Environmental Sciences, University of Copenhagen, Taastrup, Denmark.

|December 28, 2020

Summary

This summary is machine-generated.

The R package bmd simplifies benchmark dose (BMD) estimation for toxicology risk assessment. It enables advanced statistical methods for various data types, integrating seamlessly within the R environment.

Keywords:

BMDL Hybrid approach Model averaging Risk assessment

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Area of Science:

Toxicology
Ecotoxicology
Statistical Modeling

Background:

The benchmark dose (BMD) methodology is crucial for hazard characterization in risk assessment.
Accurate BMD estimation requires robust statistical approaches and flexible software tools.

Purpose of the Study:

To introduce the R extension package 'bmd' for streamlined BMD and benchmark dose lower limit (BMDL) estimation.
To demonstrate the package's utility across diverse dose-response models and data types.

Main Methods:

Utilizes the 'drc' package in R for dose-response modeling.
Implements current statistical methods, including model averaging, for BMD estimation.
Supports binomial, continuous, and count data, including complex hierarchical designs.

Main Results:

The 'bmd' package provides an accessible interface for BMD and BMDL estimation within R.
Facilitates the application of advanced statistical techniques for toxicological risk assessment.
Demonstrated efficacy through four illustrative examples.

Conclusions:

The 'bmd' R package enhances the estimation of benchmark doses for risk assessment.
Offers a flexible and powerful tool for toxicologists and statisticians within the R ecosystem.
Enables rapid implementation of existing and novel statistical methods for BMD analysis.