DILIrank dataset for QSAR modeling of drug-induced liver injury

Drug-induced liver injury (DILI) is a major drug safety concern for clinicians, drug developers, and regulators. New tools and approaches to better predict DILI risk in humans, especially at the early stages of drug development, are still urgently needed. The development of predictive models requires a drug reference list with an accurate annotation of DILI risk in humans. Here, we summarized previously developed schema for annotating a drug's potential to cause DILI in humans. This effort utilized a drug labeling–based approach by weighing the causality assessment in literature. A large dataset, namely DILIrank, was published in which 1036 drugs were classified into three verified DILI groups (i.e., Most-, Less-, or No-DILI-concern) or a group of “ambiguous DILI” drugs without causality verification. This large dataset has been widely used to support the development of quantitative structure–activity relationships and other predictive models.