Abstract

Toxicology aims to comprehend and envisage the adverse outcomes of chemicals and xenobiotics on the biological system. Predicting toxicity on the biological system is a complex and immense process. In-vivo, in-vitro, pre-, clinical and –omics level experimental approaches have been utilized to describe the toxicological impact of these chemicals and this has generated a vast wealth of data. Hence, there now exist a need for a system that can interrelate and provide accurate and robust extrapolation of these data across various systems. Therefore, it is essential to re-shift our notion from empirical, animal-based testing to a mechanistic understanding. Systems biology is one such system that can extrapolate and interrelate these vast biological system data. Systems biology is a computational and mathematical modelling approach developed to understand interrelationships between networks of biological systems. The use of systems biology to answer toxicology-related questions is termed as systems toxicology. In this review we will look at the standard and classical toxicology experimentations and how we can use mechanistic data (systems biology) to answer toxicology-related questions using systems toxicology and what are the future opportunities in systems toxicology. The advancement of systems toxicology heralds new dawn of technologies that will aid in our quest to better comprehend and envisage the adverse outcomes of chemicals and xenobiotics on the biological system.