In Silico Methods to Predict Relevant Toxicological Endpoints of Bioactive Substances

Abstract

Toxicity assessment is an essential step in the development of drugs, agrochemicals and other bioactive substances. In silico toxicity prediction, or computational toxicology, has been growing fast during the last years mainly due to advantageous cost and labor reduction, and avoidance of experiments using animals. Considering the vast number of software available for toxicity prediction, one should be aware to pick up the right software for the right task. Herein, we aim to describe the main software as well as corresponding methodologies behind them, that are able to provide reliable and accurate results for diverse toxicological endpoints. We give special emphasis to software based on quantitative structure–activity relationships, expert systems and machine learning methodologies. With this in mind, we hope that this chapter content may serve as a valuable guide to select toxicity prediction software, and also to reinforce their usefulness towards researches concerning the development of bioactive substances.