An integrated, multidisciplinary approach for drug safety assessment

Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. Well-defined clinical diagnostic criteria and risk factors are also missing. This paper summarizes key data interpretation challenges, practical considerations, model limitations, and the need for an integrated risk assessment. As demonstrated through selected initiatives to address other types of toxicities, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. Perspectives on the incorporation of newer technologies and the value of precompetitive consortia to identify useful practices are also discussed.

Characteristic molecular and proteomic signatures of drug-induced liver injury in a rat model

Drug-induced liver injury (DILI) is a major safety concern during drug development and remains one of the main reasons for withdrawal of drugs from the market. Although it is crucial to develop methods that will detect potential hepatotoxicity of drug candidates as early and as quickly as possible, there is still a lack of sensitive and specific biomarkers for DILI that consequently leads to a scarcity of reliable hepatotoxic data. Hence, in this study, we assessed characteristic molecular signatures in rat liver treated with drugs (pyrazinamide, ranitidine, enalapril, carbamazepine and chlorpromazine) that are known to cause DILI in humans. Unsupervised hierarchical clustering analysis of transcriptome changes induced by DILI-causing drugs resulted in three different subclusters on dendrogram, i.e., hepatocellular, cholestatic and mixed type of DILI at early time points (2 days), and multiclassification analysis suggested 31 genes as discernible markers for each DILI pattern. Further analysis for characteristic molecular signature of each DILI pattern provided a molecular basis for different modes of DILI action. A proteomics study of the same rat livers was used to confirm the results, and the two sets of data showed 60 matching classifiers. In conclusion, the data of different DILI-causing drug treatments from genomic analysis in a rat model suggest that DILI-specific molecular signatures can discriminate different patterns of DILI at an early exposure time point, and that they provide useful information for mechanistic studies that may lead to a better understanding of the molecular basis of DILI.

In silico models for drug-induced liver injury--current status

INTRODUCTION

Drug-induced liver injury (DILI) is one of the most important reasons for drug attrition at both pre-approval and post-approval stages. Therefore, it is crucial to develop methods that will detect potential hepatotoxicity among drug candidates as early and quickly as possible. However, the complexity of hepatotoxicity endpoint makes it very difficult to predict. In addition, there is still a lack of sensitive and specific biomarkers for DILI that consequently leads to a scarcity of reliable hepatotoxic data, which are the key to any modelling approach.

AREAS COVERED

This review explores the current status of existing in silico models predicting hepatotoxicity. Over the past decade, attempts have been made to compile hepatotoxicity data and develop in silico models, which can be used as a first-line screening of drug candidates for further testing.

EXPERT OPINION

Most of the predictive methods discussed in this review are based on the structural properties of chemicals and do not take into account genetic and environmental factors; therefore, their predictions are still uncertain. To improve the predictability of in silico models for DILI, it is essential to better understand its mechanisms as well as to develop sensitive toxicogenomics biomarkers, which show relatively good differentiation between hepatotoxins and non-hepatotoxins.

Safety of chronic obstructive pulmonary disease medications: a primary care perspective

Chronic obstructive pulmonary disease (COPD), which affects > 210 million individuals worldwide, places primary care practitioners at the forefront of diagnosing and managing COPD, and preventing adverse drug reactions (ADRs) associated with COPD medications. Therefore, it is essential that practitioners understand the safety profiles of these medications. They should also be aware of the host factors and any preexisting comorbidities in their patients that may impact the safety and efficacy of the prescribed therapy. Drug safety information obtained from randomized controlled trials, observational studies, and meta-analyses should be analyzed to assess the risk-benefit to a patient, since the majority of ADRs associated with COPD medications are predictable, and are avoidable with judicious use of these drugs. This article discusses the different medications available for COPD management and the factors affecting their safety based on current evidence.

Developing structure-activity relationships for the prediction of hepatotoxicity

Drug-induced liver injury is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use of existing toxicity data and mechanistic understanding of the biological processes for related compounds. In the published literature, this information is often spread across diverse sources and can be varied and unstructured in quality and content. The current work has explored whether it is feasible to collect and use such data for the development of new SARs for the hepatotoxicity endpoint and expand upon the limited information currently available in this area. Reviews of hepatotoxicity data were used to build a structure-searchable database, which was analyzed to identify chemical classes associated with an adverse effect on the liver. Searches of the published literature were then undertaken to identify additional supporting evidence, and the resulting information was incorporated into the database. This collated information was evaluated and used to determine the scope of the SARs for each class identified. Data for over 1266 chemicals were collected, and SARs for 38 classes were developed. The SARs have been implemented as structural alerts using Derek for Windows (DfW), a knowledge-based expert system, to allow clearly supported and transparent predictions. An evaluation exercise performed using a customized DfW version 10 knowledge base demonstrated an overall concordance of 56% and specificity and sensitivity values of 73% and 46%, respectively. The approach taken demonstrates that SARs for complex endpoints can be derived from the published data for use in the in silico toxicity assessment of new compounds.

The use of the Integrated Discrete Multiple Organ Co-culture (IdMOC) system for the evaluation of multiple organ toxicity

The application of the Integrated Discrete Multiple Organ Co-culture (IdMOC) system in the evaluation of organ-specific toxicity is reviewed. In vitro approaches to predict in vivo toxicity have met with limited success, mainly because of the complexity of in vivo toxic responses. In vivo properties that are not well-represented in vitro include organ-specific responses, multiple organ metabolism, and multiple organ interactions. The IdMOC system has been developed to address these deficiencies. The system uses a 'wells-within-a-well' concept for the co-culturing of cells or tissue slices from different organs as physically separated (discrete) entities in the small inner wells. These inner wells are nevertheless interconnected (integrated) by overlying culture medium in the large outer containing well. The IdMOC system thereby models the in vivo situation, in which multiple organs are physically separated but interconnected by the systemic circulation, permitting multiple organ interactions. The IdMOC system, with either cells or tissue slices from multiple organs, can be used to evaluate cell type-specific or organ-specific toxicity.

Human hepatocytes: isolation, cryopreservation and applications in drug development

The recent developments in the isolation, culturing, and cryopreservation of human hepatocytes, and the application of the cells in drug development are reviewed. Recent advances include the improvement of cryopreservation procedures to allow cell attachment, thereby extending the use of the cells to assays that requires prolong culturing such as enzyme induction studies. Applications of human hepatocytes in drug development include the evaluation of metabolic stability, metabolite profiling and identification, drug-drug interaction potential, and hepatotoxic potential. The use of intact human hepatocytes, because of the complete, undisrupted metabolic pathways and cofactors, allows the development of data more relevant to humans in vivo than tissue fractions such as human liver microsomes. Incorporation of key in vivo factors with the intact hepatocytes in vitro may help predictive human in vivo drug properties. For instance, evaluation of drug metabolism and drug-drug interactions with intact human hepatocytes in 100% human serum may eliminate the need to determine in vivo intracellular concentrations for the extrapolation of in vitro data to in vivo. Co-culturing of hepatocytes and nonhepatic primary cells from other organs in the integrated discrete multiple organ co-culture (IdMOC) may allow the evaluation of multiple organ interactions in drug metabolism and drug toxicity. In conclusion, human hepatocytes represent a critical experimental model for drug development, allowing early evaluation of human drug properties to guide the design and selection of drug candidates with a high probability of clinical success.