This Title All WIREs
How to cite this WIREs title:
WIREs Comput Mol Sci
Impact Factor: 16.778

Toxicity prediction based on artificial intelligence: A multidisciplinary overview

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract The use and production of chemical compounds are subjected to strong legislative pressure. Chemical toxicity and adverse effects derived from exposure to chemicals are key regulatory aspects for a multitude of industries, such as chemical, pharmaceutical, or food, due to direct harm to humans, animals, plants, or the environment. Simultaneously, there are growing demands on the authorities to replace traditional in vivo toxicity tests carried out on laboratory animals (e.g., European Union REACH/3R principles, Tox21 and ToxCast by the U.S. government, etc.) with in silica computational models. This is not only for ethical aspects, but also because of its greater economic and time efficiency, as well as more recently because of their superior reliability and robustness than in vivo tests, mainly since the entry into the scene of artificial intelligence (AI)‐based models, promoting and setting the necessary requirements that these new in silico methodologies must meet. This review offers a multidisciplinary overview of the state of the art in the application of AI‐based methodologies for the fulfillment of regulatory‐related toxicological issues. This article is categorized under: Data Science > Chemoinformatics Data Science > Artificial Intelligence/Machine Learning
(a,b) Timeline of main directives and organizations involved in the regulation of animal experimentation
[ Normal View | Magnified View ]
Stages making up in silico toxicology
[ Normal View | Magnified View ]
Perspective of artificial intelligence‐based methodologies applied to chemical toxicology
[ Normal View | Magnified View ]

Browse by Topic

Computer and Information Science > Visualization
Computer and Information Science > Chemoinformatics

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts