Idiosyncratic drug-induced liver injury (DILI) is a common cause for drug withdrawal from the market and although infrequent, DILI can result in serious clinical outcomes including acute liver failure and the need for liver transplantation. Eliminating the iatrogenic "harm" caused by a therapeutic intent is a priority in patient care. However, identifying culprit drugs and individuals at risk for DILI remains challenging. Apart from genetic factors predisposing individuals at risk, the role of the drugs' physicochemical and toxicological properties and their interactions with host and environmental factors need to be considered. The influence of these factors on mechanisms involved in DILI is multi-layered. In this review, we summarize current knowledge on 1) drug properties associated with hepatotoxicity, 2) host factors considered to modify an individuals' risk for DILI and clinical phenotypes, and 3) drug-host interactions. We aim at clarifying knowledge gaps needed to be filled in as to improve risk stratification in patient care. We therefore broadly discuss relevant areas of future research. Emerging insight will stimulate new investigational approaches to facilitate the discovery of clinical DILI risk modifiers in the context of disease complexity and associated interactions with drug properties, and hence will be able to move towards safety personalized medicine.

Drug-induced liver injury (DILI) is a leading cause of drug failure in clinical trials and a major reason for drug withdrawals from the market. Although there is evidence that dosages of ≥100 mg/day are associated with increased risk for hepatotoxicity, many drugs are safe at such dosages. There is an unmet need to predict risk for DILI more reliably, and lipophilicity might be a contributing factor. We analyzed the combined factors of daily dose and lipophilicity for 164 US Food and Drug Administration–approved oral medications and observed high risk for hepatotoxicity (odds ratio [OR], 14.05; P < 0.001) for drugs given at dosages ≥100 mg/day and octanol-water partition coefficient (logP) ≥3. This defined the “rule-of-two.” Similar results were obtained for an independent set of 179 oral medications with 85% of the rule-of-two positives being associated with hepatotoxicity (OR, 3.89; P < 0.01). Using the World Health Organization's Anatomical Therapeutic Chemical classification system, the rule-of-two performed best in predicting DILI in seven therapeutic categories. Among 15 rule-of-two positives, 14 were withdrawn from hepatotoxic drugs, and one was over-the-counter medication labeled for liver injury. We additionally examined drug pairs that have similar chemical structures and act on the same molecular target but differ in their potential for DILI. Again, the rule-of-two predicted hepatotoxicity reliably. Finally, the rule-of-two was applied to clinical case studies to identify hepatotoxic drugs in complex comedication regimes to further demonstrate its use. Conclusion: Apart from dose, lipophilicity contributes significantly to risk for hepatotoxicity. Applying the rule-of-two is an appropriate means of estimating risk for DILI compared with dose alone. (HEPATOLOGY 2013)

Toxicogenomics enjoyed considerable attention as a ground-breaking addition to conventional toxicology assays at its inception. However, the pace at which toxicogenomics was expected to perform has been tempered in recent years. Next to cost, the lack of advanced knowledge discovery and data mining tools significantly hampered progress in this new field of toxicological sciences. Recently, two of the largest toxicogenomics databases were made freely available to the public. These comprehensive studies are expected to stimulate knowledge discovery and development of novel data mining tools, which are essential to advance this field. In this review, we provide a concise summary of each of these two databases with a brief discussion on the commonalities and differences between them. We place our emphasis on some key questions in toxicogenomics and how these questions can be appropriately addressed with the two databases. Finally, we provide a perspective on the future direction of toxicogenomics and how new technologies such as RNA-Seq may impact this field.