Abstract
The science of toxicology is the science of the system. Toxicologists aim to understand and predict the adverse effects of chemicals on biological systems. As biological systems are extremely complex, the challenge of predicting human toxicity early in the drug discovery process is immense. In the past decades, a huge effort has been undertaken to characterise the impact of chemicals on biological systems using in vitro, pre-clinical and clinical approaches. This has led to a vast amount of knowledge on the biology of systems, especially as a result of the data deluge from -omic level investigations. However, a lack of robust and comprehensive integration has meant that this wealth of data has still not led to accurate prediction of toxicity in a single system, or the ability to extrapolate robustly between systems. The new discipline of systems toxicology aims to take the computational approaches developed in systems biology and apply them to toxicology-related questions. This review will examine approaches ranging from relational databases that are both repositories for curated information and screening tools in their own right, to the potential of digital organisms in systems toxicology. Both the basic methodologies and how best they may be applied to safety assessment of chemicals will be covered. This integrated examination of toxicological data is predicted to herald a step-change in our ability to both understand and predict adverse effects of chemicals. This journal is