Abstract

Drug-induced liver injury (DILI) is a major cause of acute liver dysfunction and remains one of the most challenging adverse drug reactions encountered in clinical practice. Epidemiologic studies estimate an annual incidence of 14–19 cases per 100,000 individuals, with DILI accounting for approximately 10% of acute hepatitis presentations and a substantial proportion of acute liver failure in Western countries. (1, 2) Clinical manifestations range from asymptomatic elevations in aminotransferases to fulminant hepatic failure, and the unpredictable nature of idiosyncratic reactions continues to complicate diagnosis and risk assessment. (1) The severity and continually evolving nature of DILI has pushed the field toward developing predictive approaches that can improve patient safety, avoid late-stage development failures, and prevent costly postmarket withdrawals. This theme was highlighted at the “Predicting Drug-Induced Liver Injury” symposium at the ACS Fall 2025 conference, where the discussions centered on how traditional in vivo and in vitro toxicology methods can be integrated with modern in silico tools. Together, these complementary strategies underscore the growing emphasis on building more reliable and mechanistically informed DILI prediction frameworks.

By Don Pivithuru Liyanarachchi