Detection, Elimination, Mitigation, and Prediction of Drug-Induced Liver Injury in Drug Discovery

Despite being among the most efficiently detected and managed toxicity during preclinical drug development, drug-induced liver injury (DILI) remains a major hurdle and is recognized to be a major cause of drug attrition and market withdrawal. DILI impacts many different sectors of society including patients, public health systems, health insurers and the pharmaceutical industry. Animal models are very efficient at detecting direct, dose-dependent and species-independent toxicity to the liver, the so-called intrinsic DILI. Compounds inducing mild liver signals can be developed as drugs if they exhibit a positive therapeutic benefit and are deemed to be superior to the currently available standard of care/medications. These cases are well managed as opposed to the unpredictable, dose-independent, individual-specific idiosyncratic toxicities, which are typically not detected in preclinical phases of drug development. Considerable efforts are dedicated to the detection and understanding of idiosyncratic DILI, and to the prediction of intrinsic DILI. Ever more complex and biologically relevant in vitro models are emerging for compound prescreening purposes. These data are also being used to the development of in silico algorithms which, when combined with compound chemical properties, in vivo observations and human-based post-marketing data, yield analytical and potentially predictive systems. In addition, the recent emergence of viable humanized liver animal models should bring forth a new battery of assays for accurately predicting compound-induced intrinsic liver toxicity in patients, and may also pave the way toward a better understanding of idiosyncratic DILI reactions.