In silico prediction of drug-induced liver injury: Quo vadis?

Abstract Drug-induced liver injury (DILI) with high incidence and prevalence rates is a potentially severe adverse drug reaction (ADR) especially in susceptible patients, and is concomitantly challenging for drug development, clinical practice, and regulation. Nonetheless, there are no sensitive or specific parameters to detecting DILI. The ADRs, particularly those that result in life-threating DILI, are a major cause of drug failure in clinical trials and drug withdrawals. The currently annotated serum and new emerging biomarkers can be used to identify hepatotoxicity in general and provide, to a certain extent, a tool for mechanistic distinction. New biomarkers to diagnose and predict DILI evolution are under study and hopefully gain the benefits from these novel tools in the near future. The facility of more advanced scientific and regulatory guidance for liver safety assessment will depend on validating the new diagnostic markers in the ongoing DILI registries, biobanks and public-private partnerships. The limited predictive model of in silico models can be mostly attributed to the complex nature of DILI, various molecular mechanisms underlying DILI, poor in vitro–in vivo correlation, a scarcity of human DILI data in addition to numerous additional factors contributing to DILI, namely dosage, administration duration, drug interactions, pharmacokinetics profile, age, gender, pre-existing disease, disease state, polymorphism, environmental factors and exposure to other foreign compounds, environmental factors, exposure to other foreign compounds. As such, it is not surprising that DILI prediction is extremely difficult if not entirely impossible. Despite those difficulties, there have been efforts to develop in silico models to predict hepatotoxicity in the last decade. This chapter is not intended to comprehensively cover every published in silico DILI models. Instead, a number of DILI predictive models in every aspect are briefly described.