Using chemical and biological data to predict drug toxicity

Various sources of information can be used to better understand and predict compound activity and safety-related endpoints, including biological data such as gene expression and cell morphology. In this review, we first intro-duce types of chemical, in vitro and in vivo information that can be used to describe compounds and adverse effects. We then explore how compound descriptors based on chemical structure or biological perturbation re-sponse can be used to predict safety-related endpoints, and how especially biological data can help us to better understand adverse effects mechanistically. Overall, the described applications demonstrate how large-scale bio-logical information presents new opportunities to anticipate and understand the biological effects of compounds, and how this can support predictive toxicology and drug discovery projects.

Automated summary

This review discusses various sources of information, including biological data such as gene expression and cell morphology, for better understanding and predicting compound activity and safety-related endpoints. It introduces different types of chemical, in vitro, and in vivo information that can describe compounds and adverse effects. The review explores how compound descriptors based on chemical structure or biological perturbation response can predict safety-related endpoints, and how biological data can enhance understanding of adverse effects mechanistically. These applications highlight the potential of large-scale biological information in predictive toxicology and drug discovery projects.