Recently, research on the development of artificial intelligence (AI)-based computational
toxicology models that predict toxicity without the use of animal testing has emerged …

Various sources of information can be used to better understand and predict compound
activity and safety-related endpoints, including biological data such as gene expression and …

Distribution shifts—where the training distribution differs from the test distribution—can
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild …

The first edition of Bioanalytical Tools in Water Quality Assessment was released in 2012.
The field has exploded since and the second edition updates and reviews the application of …

New approach methodologies (NAMs) that efficiently provide information about chemical
hazard without using whole animals are needed to accelerate the pace of chemical risk …

An important question in toxicological risk assessment is whether non-animal new approach
methodologies (NAMs) can be used to make safety decisions that are protective of human …

The present study adapted an existing high content imaging-based high-throughput
phenotypic profiling (HTPP) assay known as “Cell Painting” for bioactivity screening of …

For the past six decades, human health risk assessment of chemicals has relied on in vivo
data from human epidemiological and experimental animal toxicological studies to inform …

Humans are involuntarily exposed to hundreds of chemicals that either contaminate our
environment and food or are added intentionally to our daily products. These complex …

New approach methodologies (NAMs) that do not use experimental animals are, in certain
settings, entirely appropriate for assuring the safety of chemical ingredients, although …