Construction and analysis of a human hepatotoxicity database suitable for QSAR modeling using post-market safety data

Drug-induced liver injury (DILI) is one of the most common drug-induced adverse events (AEs) leading to life-threatening conditions such as acute liver failure. It has also been recognized as the single most common cause of safety-related post-market withdrawals or warnings. Efforts to develop new predictive methods to assess the likelihood of a drug being a hepatotoxicant have been challenging due to the complexity and idiosyncrasy of clinical manifestations of DILI. The FDA adverse event reporting system (AERS) contains post-market data that depict the morbidity of AEs. Here, we developed a scalable approach to construct a hepatotoxicity database using post-market data for the purpose of quantitative structure-activity relationship (QSAR) modeling. A set of 2029 unique and modelable drug entities with 13,555 drug-AE combinations was extracted from the AERS database using 37 hepatotoxicity-related query preferred terms (PTs). In order to determine the optimal classification scheme to partition positive from negative drugs, a manually-curated DILI calibration set composed of 105 negatives and 177 positives was developed based on the published literature. The final classification scheme combines hepatotoxicity-related PT data with supporting information that optimize the predictive performance across the calibration set. Data for other toxicological endpoints related to liver injury such as liver enzyme abnormalities, cholestasis, and bile duct disorders, were also extracted and classified. Collectively, these datasets can be used to generate a battery of QSAR models that assess a drug's potential to cause DILI.

Hopes and challenges in using miRNAs as translational biomarkers for drug-induced liver injury

There is a need for better biomarkers of drug-induced liver injury (DILI) to guide risk assessment and patient management. Over the past 3 years, both animal and clinical studies have provided proof-of-concept data showing that a subset of miRNAs appear to offer unique advantages over the conventional DILI biomarkers, such as enhanced sensitivity and specificity, reduced inter-individual variations, the potential to differentiate lethal and nonlethal liver injury, and the ability to reflect the patterns and even the etiology of liver injury. Notably, many studies have demonstrated that level of miR-122, a liver-enriched miRNA accounting for approximately 70% of total hepatic miRNAs, was increased many fold in the blood when DILI occurred. However, currently available data are predominantly based on animal models and not human samples. Due to the lack of a standard quantification method for miRNAs and confirmatory studies using a comprehensive list of drugs and patients, the true value of all reported miRNA biomarkers remains to be carefully assessed. An outstanding challenge is to examine if miRNAs are also useful for idiosyncratic DILI, which constitutes the major part of clinical DILI cases but generally cannot be recapitulated in traditional animal models or in clinical trials (the latter due to its relative rarity).

Use of PD biomarkers to drive dose selection and early clinical decision making

A major challenge facing the development of new therapies is the high level of compound attrition in late-stage clinical studies. A key factor in reducing these unsustainable levels of attrition is the successful evaluation of the level of drug effect on its target pathway in early development, otherwise known as testing the compound mechanism. Incorporation of PD biomarkers into Phase I/II trials to demonstrate compound binding to its molecular target and the subsequent modulation of downstream pathways enables early testing of compound mechanism and provides a data-driven framework for decisions on compound progression. This review will discuss the identification and validation of such 'fit-for-purpose' PD biomarkers, and case studies illustrating their use and value in dose selection and accelerating the clinical development of small-molecule drugs will be described.

Transcriptional profiling to identify biomarkers of disease and drug response

The discovery, biological qualification and analytical validation of genomic biomarkers requires extensive collaborations between individuals with expertise in biology, statistics, bioinformatics, chemistry, clinical medicine, regulatory science and so on. For clinical utility, blood-borne biomarkers (e.g., mRNA and miRNA) of organ damage, drug toxicity and/or response would be preferred to those that are tissue based. Currently used biomarkers such as serum creatinine (indicating renal dysfunction) denote organ damage whether caused by disease, physical injury or drugs. Therefore, it is anticipated that studies of disease will discover biomarkers that can also be used to identify drug-induced injury and vice versa. This article describes transcriptomic blood-borne biomarkers that have been reported to be connected with disease and drug toxicity. Much more qualification and validation needs to be carried out before many of these biomarkers can prove useful. Discussed here are some of the lessons learned and roadblocks to success.

Human drug hepatotoxicity: a contemporary clinical perspective

BACKGROUND

Drug-induced liver injury (DILI) constitutes a significant medical challenge. The rising number of marketed drugs, aging population and polypharmacy make it imperative to understand the clinical presentation of DILI and the processes used in the assessment of causality and early detection.

OBJECTIVE

This article reviews the current clinical understanding of DILI including presentation patterns, causality assessment, risk factor ascertainment and early detection strategies including liver test monitoring. Significant initiatives such as the Drug-Induced Liver Injury Network (DILIN) are also discussed.

METHODS

A narrative review of clinical studies of DILI, with emphasis on clinical features, causality and surveillance.

CONCLUSION

DILI remains a serious challenge in contemporary clinical practice. Further research and collaboration in the areas of epidemiology, causality and early detection are required to enhance the diagnosis and management of DILI.