Unraveling Drug-Induced Hepatotoxicity: Roles of Oxidative Stress, Biomarker Discovery, and Translational Advances

The liver is a vital organ that supports numerous bodily functions, including digestion, detoxification, metabolism, immunity, and vitamin storage.It accounts for approximately 2% of an adult's body weight.The liver is unique because it receives blood from both the portal vein (about 75%) and the hepatic artery (approximately 25%).Hepatotoxicity remains a critical concern in pharmacology and toxicology due to the liver's central role in metabolism, detoxification, and drug biotransformation.A typical adverse effect of several drug classes, drug-induced liver damage (DILI), is usually moderate and goes away quickly upon stopping the drug.Individual susceptibility may be increased by underlying hepatic problems and genetic predisposition.DILI is expected to occur at a rate of 13.9-24.0cases per 100,000 people worldwide per year.In the United States, DILI is one of the main causes of acute liver failure.The estimated yearly incidence of cases admitted to university hospitals in Korea is 12/100,000 people.Through oxidative stress, mitochondrial dysfunction, inflammation (e.g., TNF-, IL-6), and metabolic disturbance, xenobiotics, medications, and pollutants can harm the liver.These processes contribute to hepatocellular damage and the advancement of liver disease by causing lipid peroxidation, energy deficit, and fibrosis.Limitations of animal models on account of ethical, translational, and interspecies variability have driven the development of alternative systems.Emerging in vitro platforms, including 3D liver organoids, stem cell-derived hepatocytes, and organ-on-chip systems, provide physiologically relevant systems for hepatotoxicity testing.Augmenting computational tools, such as AI-based models, quantitative structure-activity relationships (QSAR), and physiologically based pharmacokinetic (PBPK) simulations, enhances predictive ability with reduced reliance on animal testing.This review combines up-to-date mechanistic understanding and model developments with an emphasis on integrating molecular data with next-generation strategies to improve hepatotoxicity prediction and human disease relevance.