Chapter 5.3 - Computational Methods to Predict Toxicity

Abstract

Going back to the 19th century, there is a long history of developing an understanding of how the physicochemical properties and chemical structure of a molecule affect its biological activity. Such approaches, commonly now referred to as being in silico, are formalised into (quantitative) structure–activity relationships ((Q)SARs) and read-across to predict toxicity and Physiologically-Based Pharmacokinetic models, to predict the distribution of chemicals in vivo and to allow for the extrapolation from in vitro effects. There have been many drivers for the development of in silico approaches to predict toxicity, fate and distribution. Notable among these have been the needs of various industrial sectors to assess the hazard of chemicals rapidly and efficiently, in terms of cost and animal use. These needs have been amplified globally by legislation aiming to improve animal welfare, and to respond to ethical concerns, as well as to regulate new and existing chemicals. In addition, key advances in chemoinformatics, computational power, and the connectivity of the internet have all played a role in the advancement of in silico approaches.