Current challenges and controversies in drug-induced liver injury.

Current key challenges and controversies encountered in the identification of potentially hepatotoxic drugs and the assessment of drug-induced liver injury (DILI) are covered in this article. There is substantial debate over the classification of DILI itself, including the definition and validity of terms such as 'intrinsic' and 'idiosyncratic'. So-called idiosyncratic DILI is typically rare and requires one or more susceptibility factors in individuals. Consequently, it has been difficult to reproduce in animal models, which has limited the understanding of its underlying mechanisms despite numerous hypotheses. Advances in predictive models would also help to enable preclinical elimination of drug candidates and development of novel biomarkers. A small number of liver laboratory tests have been routinely used to help identify DILI, but their interpretation can be limited and confounded by multiple factors. Improved preclinical and clinical biomarkers are therefore needed to accurately detect early signals of liver injury, distinguish drug hepatotoxicity from other forms of liver injury, and differentiate mild from clinically important liver injury. A range of potentially useful biomarkers are emerging, although so far most have only been used preclinically, with only a few validated and used in the clinic for specific circumstances. Advances in the development of genomic biomarkers will improve the prediction and detection of hepatic injury in future. Establishing a definitive clinical diagnosis of DILI can be difficult, since it is based on circumstantial evidence by excluding other aetiologies and, when possible, identifying a drug-specific signature. DILI signals based on standard liver test abnormalities may be affected by underlying diseases such as hepatitis B and C, HIV and cancer, as well as the concomitant use of hepatotoxic drugs to treat some of these conditions. Therefore, a modified approach to DILI assessment is justified in these special populations and a suggested framework is presented that takes into account underlying disease when evaluating DILI signals in individuals. Detection of idiosyncratic DILI should, in some respects, be easier in the postmarketing setting compared with the clinical development programme, since there is a much larger and more varied patient population exposure over longer timeframes. However, postmarketing safety surveillance is currently limited by the quantity and quality of information available to make an accurate diagnosis, the lack of a control group and the rarity of cases. The pooling of multiple healthcare databases, which could potentially contain different types of patient data, is advised to address some of these deficiencies.