Quantitative Systems Toxicology

This chapter delves into the emerging techniques of quantitative systems toxicology (QST) approaches, which are considered computational modelling approaches to toxicokinetics, toxicodynamics, and combination terms, and aims at integrating both knowledge and data to offer mechanistic insights and predictive capabilities, thereby mitigating risks in drug development processes. Within this domain, the chapter introduces fundamental elements, including data, algorithms, and available BioSimulation software platforms. Through a comprehensive review, it highlights examples of QST applications across various stages, from preclinical to clinical phases, while also considering other dynamically evolving approaches in drug safety assessment. Additionally, the chapter explores the potential regulatory acceptance of QST-driven developments for safer drugs and identifies challenges for further advancements in QST models. Lastly, it discusses the promising prospects, including consideration of Artificial Intelligence (AI) era, particularly in integrating AI-aided systems modelling to expedite the development of toxicological models in both preclinical and clinical settings toward next-generation risk assessment of new drugs.