QSAR modeling for predicting drug-induced liver injury

Drug-induced liver injury (DILI) is an adverse drug reaction that may be caused by overdose or occur as an unpredictable idiosyncratic event, the mechanism of which remains loosely defined. DILI is also one of the most common causes of drug withdrawal from the market. To derisk DILI at the early stage of drug discovery, many efforts have been invested to develop DILI predictive models, including quantitative structure–activity relationship (QSAR) models. In this chapter, we focus on how machine learning and deep learning can assist QSAR modeling, as well as the recent development of DILI predictive models in the past 3 years.