In silico toxicology, a robust approach for decision-making in the context of next-generation risk assessment

Abstract The current conceptual model of toxicity assessment based on animal testing is gradually moving toward systems biology approaches that integrate multiple data streams from diverse experimental systems into a unified risk assessment paradigm. These novel approaches not only provide improved predictions of toxicity, but also enable mechanistic interpretations of the molecular mechanisms underlying toxicity. On that account, fast and inexpensive computer-based models can be developed for a better prediction, interpretation, and understanding of toxicological effects of drugs, food, and environmental chemicals on humans and the environment. This chapter presents basic concepts and methods that link toxicology with computational sciences for high-throughput safety assessment of the large number of chemicals. The chapter covers different aspects of in silico toxicology that complement current in vitro and/or in vivo toxicity testing to predict toxicity and prioritize chemicals or drugs to ultimately minimize harmful effects on humans.