Assessment Of Drug-induced Liver Injury Research Articles

Utility of human cytochrome P450 inhibition data in the assessment of drug-induced liver injury

1. Drug-induced liver injury (DILI) is a major cause of drug development discontinuation and drug withdrawal from the market, but there are no golden standard methods for DILI risk evaluation. Since we had found the association between DILI and CYP1A1 or CYP1B1 inhibition, we further evaluated the utility of cytochrome P450 (P450) inhibition assay data for DILI risk evaluation using decision tree analysis. 2. The inhibitory activity of drugs with DILI concern (DILI drugs) and no DILI concern (no-DILI drugs) against 10 human P450s was assessed using recombinant enzymes and luminescent substrates. The drugs were also subjected to cytotoxicity assays and high-content analysis using HepG2 cells. Molecular descriptors were calculated by alvaDesc. 3. Decision tree analysis was performed with the data obtained as variables with or without P450-inhibitory activity to discriminate between DILI drugs and no-DILI drugs. The accuracy was significantly higher when P450-inhibitory activity was included. After the decision tree discrimination, the drugs were further discriminated with the P450-inhibitory activity. The results demonstrated that many false-positive and false-negative drugs were correctly discriminated by using the P450 inhibition data. 4. These results suggest that P450 inhibition assay data are useful for DILI risk evaluation.

Human Hepatic Spheroid Coculture Model for the Assessment of Drug-Induced Liver Injury.

Accurate evaluation of potential drug risks such as drug-induced liver injury (DILI) continues to be a challenge faced by pharmaceutical industry and regulatory agencies. Preclinical testing has served as a foundation for the evaluation of the potential risks and effectiveness of investigational new drug (IND) products in humans. However, current two-dimensional (2D) in vitro human primary hepatocyte (HPH) culture systems cannot accurately depict and simulate the rich environment and complex processes observed in vivo, while animal studies present inherited species-specific differences and low throughput scales. Thus, there is a continued demand to establish new approaches that can better characterize DILI during drug discovery and development. Among others, the three-dimensional (3D) hepatic spheroid model comprising self-aggregated primary human hepatocytes cocultured with non-parenchymal cells (NPCs) appears to be a more accurate representation of the natural hepatic microenvironment with intercellular interactions between hepatocytes, stellate cells, Kupffer cells, liver sinusoidal endothelial cells (LSECs), and other cell types. This model holds the potential to improve the ability for long-term functional and toxicological studies. Here, we provide methodological details for this human hepatic spheroid coculture model system.

Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.

Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, ...) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.

Chinese guideline for diagnosis and management of drug-induced liver injury (2023 version)

Drug-induced liver injury (DILI) is an important adverse drug reaction that can lead to acute liver failure or even death in severe cases. Currently, the diagnosis of DILI still follows the strategy of exclusion. Therefore, a detailed history taking and a thorough and careful exclusion of other potential causes of liver injury is the key to correct diagnosis. This guideline was developed based on evidence-based medicine provided by the latest research advances and aims to provide professional guidance to clinicians on how to identify suspected DILI timely and standardize the diagnosis and management in clinical practice. Based on the clinical settings in China, the guideline also specifically focused on DILI in chronic liver disease, drug-induced viral hepatitis reactivation, common causing agents of DILI (herbal and dietary supplements, anti-tuberculosis drugs, anti-neoplastic drugs), and signal and assessment of DILI in clinical trials.

<i>In Vitro</i> Assessment of Drug-Induced Liver Injury Using Cell-Based Models: A Review

Drug-induced liver injury (DILI) is the reason for 15–18% of medicinal product recalls from the market. Since interspecies differences often limit the relevance of standard non-clinical tests in vivo, a promising alternative is to develop cell-based in vitro methods.The aim of the study was to review current advances in cell modelling for the in vitro identification of DILI.In vitro mechanistic studies of DILI require cells that exhibit activity specific to hepatic metabolising enzymes and transporters. This article reviews the main cell cultures (primary human hepatocytes, immortal cell lines, stem cell-derived hepatocyte-like cells, co-cultures of hepatocytes and non-parenchymal liver cells) and their configurations. The optimisation of cell systems is directed towards enhancing their viability, functionality, compositional and configurational complexity, thus bringing them closer to in vivo models. Potential DILI causes include chemically reactive metabolites, oxidative stress, mitochondrial damage, intracellular accumulation of toxic bile acids resulting from transporter inhibition, and adaptive immune system activation. Accordingly, DILI studies rely on various methods, including innovative technologies for acquisition, storage, and analysis of large datasets (e.g. high-content screening, transcriptomics, proteomics, and metabolomics). Cell models are applicable to both DILI identification and mechanistic studies. Currently, the most promising technologies are omics, complex co-culture models, and organ-on-a-chip systems.

Establishment of hyperoxic cell culture system for predicting drug-induced liver injury: reducing accumulated lipids in hepatocytes derived from chimeric mice with humanized liver.

Drug-induced liver injury (DILI) is a major adverse reaction. Species-specific differences between humans and laboratory animals make it difficult to establish evaluation models that can accurately predict DILI in the preclinical phase. Chimeric mice with humanized liver are potential predictive models for understanding DILI. Chimeric mice generated by transplanting human hepatocytes into urokinase-type plasminogen activator/severe combined immunodeficient mice are known to develop fatty liver and show lipid accumulation in isolated hepatocytes. It is speculated that the lipids accumulated in hepatocytes may interfere with DILI assessment. It is known that normal 20% oxygen culture conditions do not meet oxygen demand because oxygen consumption rate is higher than the oxygen supply rate. Therefore, we predicted that hyperoxic cultures could induce hepatocyte function and reduce accumulated lipids. A culture of chimeric mouse hepatocytes in 40% oxygen showed reduced intracellular lipid and triglyceride levels compared to those cultured in 20% oxygen on days 7 and 10. In addition, fatty acid β-oxidation (FAO) activity increased from day 7 under 40% oxygen conditions. On the other hand, FAO activity increased on day 10 under 20% conditions. Microarray and Ingenuity Pathway Analysis showed that lipid metabolism-related pathways were downregulated under 40% oxygen conditions for 7 days, suggesting the involvement of several mechanisms in decreasing lipid levels and increasing FAO. Furthermore, some pathways related to cellular function and maintenance were upregulated under 40% oxygen conditions for 7 days. In conclusion, chimeric mouse hepatocytes cultured under hyperoxic conditions may be useful for predicting DILI.

Value of combined detection of peripheral blood monocyte chemotactic protein-1, high mobility group protein-1, and ferritin in diagnosis and assessment of drug-induced liver injury

Value of combined detection of peripheral blood monocyte chemotactic protein-1, high mobility group protein-1, and ferritin in diagnosis and assessment of drug-induced liver injury

Advanced human liver models for the assessment of drug-induced liver injury

Drug safety issues continue to occur even with drugs that are approved after the completion of clinical studies. Drug-induced liver injury (DILI) is a major obstacle to drug development, because the liver is the primary site of drug metabolism, and injuries caused during this process are severe. Conventional in vitro human liver models, such as 2-dimensional hepatic cell lines, lack in vivo physiological relevance, and animal studies have limitations in the form of species differences and regulatory restrictions. To resolve this issue, an increasing number of 3-dimensional human liver systems, including organoids, are being developed. In this review, we provide an overview of recent assessments of DILI prediction, approaches for in vitro hepatotoxicity evaluation, and a variety of advanced human liver models. We discuss the advantages, limitations, and future perspectives of current human liver models for accurate drug safety evaluations.

Development of binary classification models for assessment of drug-induced liver injury in humans using a large set of FDA-approved drugs

Drug-induced liver injury (DILI) has been identified as one of the major causes for drugs withdrawn from the market, and even termination during the late stages of development. Therefore, it is imperative to evaluate the DILI potential of lead compounds during the research and development process. Although various computational models have been developed to predict DILI, most of which applied the DILI data were extracted from preclinical sources. In this investigation, the in silico prediction models for DILI were constructed based on 1140 FDA-approved drugs by using naïve Bayes classifier approach. The genetic algorithm method was applied for the molecular descriptors selection. Among these established prediction models, the NB-11 model based on eight molecular descriptors combined with ECFP_18 showed the best prediction performance for DILI, which gave 91.7% overall prediction accuracy for the training set, and 68.9% concordance for the external test set. Therefore, the established NB-11 prediction model can be used as a reliable virtual screening tool to predict DILI adverse effect in the early stages of drug design. In addition, some new structural alters for DILI were identified, which could be used for structural optimization in the future drug design by medicinal chemists.

A Comparison of Mesenchymal Stem Cell-derived Hepatocyte-like Cells and HepG2 Cells for Use in Drug-Induced Liver Injury Studies.

Liver cell lines obtained from hepatomas, for example, HepG2 cells, are commonly used in drug toxicity studies. However, functional hepatocyte-like cells derived from mesenchymal stem cells (MSCs) could be a better option for use in the study of drug metabolism and toxicity. Overdose of acetaminophen (APAP) and excess alcohol consumption are common causes of liver damage. The objective of the present study was to investigate the use of MSC-derived hepatocyte-like cells (MSCdH) in the assessment of drug-induced liver injury (by using APAP and ethanol), and to compare the toxic effects observed in the MSCdH with those exhibited by HepG2 cells. MSCs were isolated from umbilical cord and their functionality confirmed by their ability to differentiate into adipocytes, osteocytes and hepatocyte-like cells. It was shown that the MSCs successfully differentiated into hepatocyte-like cells, and these cells were further characterised by using various enzyme assays and by assessing albumin secretion and urea synthesis. Cytotoxicity was evaluated in the HepG2 and MSCdH after exposure to ethanol and APAP, with cell viability being determined by using the MTT assay. After exposure to ethanol and to APAP, cell viability decreased in a concentration-dependent manner for both types of hepatocytes. The respective EC50 values of ethanol-induced toxicity for HepG2 and MSCdH cells were 2.5% and 1.3% v/v (p < 0.001); for APAP-induced toxicity they were 19.1mM and 12.6mM (p < 0.001). These findings show that there is a distinct difference between the two types of hepatocytes in terms of APAP-induced and ethanol-induced liver injury.

Assessing Toxicity in Drug Trials in Liver Disease.

Since the early trials in viral hepatitis, more and more new drugs are being tested for use in various liver diseases. Since drug hepatotoxicity is a major cause of drugs under investigation not making it to market, the assessment of drug-induced liver injury in clinical trials of new drugs is crucial. This review will focus on the systems that are used to assess drug-induced liver injury in clinical trials and will discuss how some of these criteria are inappropriate or inaccurate in this function together with suggestions for improvement.

Recent Progress in Fluorescent Sensors for Drug-Induced Liver Injury Assessment.

Drug-induced liver injury (DILI) is a persistent concern in drug discovery and clinical medicine. The current clinical methods to assay DILI by analyzing the enzymes in serum are still not optimal. Recent studies showed that fluorescent sensors would be efficient tools for detecting the concentration and distribution of DILI indicators with high sensitivity and specificity, in real-time, in situ, and with low damage to biosamples, as well as diagnosing DILI. This review focuses on the assessment of DILI, introduces the current mechanisms of DILI, and summarizes the design strategies of fluorescent sensors for DILI indicators, including ions, small molecules, and related enzymes. Some challenges for developing DILI diagnostic fluorescent sensors are put forward. We believe that these design strategies and challenges to evaluate DILI will inspire chemists and give them opportunities to further develop other fluorescent sensors for accurate diagnoses and therapies for other diseases.

Development and Application of a Transcriptomic Signature of Bioactivation in an Advanced In Vitro Liver Model to Reduce Drug-induced Liver Injury Risk Early in the Pharmaceutical Pipeline.

Early risk assessment of drug-induced liver injury (DILI) potential for drug candidates remains a major challenge for pharmaceutical development. We have previously developed a set of rat liver transcriptional biomarkers in short-term toxicity studies to inform the potential of drug candidates to generate a high burden of chemically reactive metabolites that presents higher risk for human DILI. Here, we describe translation of those NRF1-/NRF2-mediated liver tissue biomarkers to an in vitro assay using an advanced micropatterned coculture system (HEPATOPAC) with primary hepatocytes from male Wistar Han rats. A 9-day, resource-sparing and higher throughput approach designed to identify new chemical entities with lower reactive metabolite-forming potential was qualified for internal decision making using 93 DILI-positive and -negative drugs. This assay provides 81% sensitivity and 90% specificity in detecting hepatotoxicants when a positive test outcome is defined as the bioactivation signature score of a test drug exceeding the threshold value at an in vitro test concentration that falls within 3-fold of the estimated maximum drug concentration at the human liver inlet following highest recommended clinical dose administrations. Using paired examples of compounds from distinct chemical series and close structural analogs, we demonstrate that this assay can differentiate drugs with lower DILI risk. The utility of this in vitro transcriptomic approach was also examined using human HEPATOPAC from a single donor, yielding 68% sensitivity and 86% specificity when the aforementioned criteria are applied to the same 93-drug test set. Routine use of the rat model has been adopted with deployment of the human model as warranted on a case-by-case basis. This in vitro transcriptomic signature-based strategy can be used early in drug discovery to derisk DILI potential from chemically reactive metabolites by guiding structure-activity relationship hypotheses and candidate selection.

Specificity of transaminase activities in the prediction of drug-induced hepatotoxicity.

The activities of the transaminases (aminotransferases) alanine aminotransferase and aspartate aminotransferase in the blood (serum or plasma) are widely used as sensitive markers of possible tissue damage and, in particular for liver toxicity. On the other hand, an increase in transaminase activities is not always accompanied by findings suggestive of hepatotoxicity. Transaminases are some of the key enzymes in the gluconeogenesis and glycolysis pathways and exist in many organs and tissues which have high activities of the gluconeogenesis and glycolysis. The activities of transaminases are altered not only in the liver but also in other organs by modification of gluconeogenesis by nutritional or hormonal factors and this phenomenon leads to alteration of transaminase activity in the blood. Drugs, which are considered to directly or secondarily modify gluconeogenesis through lowering blood glucose levels or activating lipid metabolism, such as α-glucosidase inhibitors and fibrates, slightly increase transaminase activities in the blood but there is little evidence that the phenomenon is related to drug-induced liver injury (DILI). This type of elevations can be called pharmacology-related elevation. The pharmacology-related elevation of transaminase activities sometimes makes it difficult to assess precisely the potential hepatotoxicity of new investigational drugs. Considering the characteristic of transaminases, concomitant use of new biomarkers more specific to hepatic injury is needed in the assessment of DILI both in non-clinical and clinical studies. In this review, we will discuss the specificity of transaminases to DILI and future perspectives for transaminases in the estimation of risk of DILI.

Prediction of clinically relevant drug-induced liver injury from structure using machine learning.

Drug-induced liver injury (DILI) is the most common cause of acute liver failure and often responsible for drug withdrawals from the market. Clinical manifestations vary, and toxicity may or may not appear dose-dependent. We present several machine-learning models (decision tree induction, k-nearest neighbor, support vector machines, artificial neural networks) for the prediction of clinically relevant DILI based solely on drug structure, with data taken from published DILI cases. Our models achieved corrected classification rates of up to 89%. We also studied the association of a drug's interaction with carriers, enzymes and transporters, and the relationship of defined daily doses with hepatotoxicity. The results presented here are useful as a screening tool both in a clinical setting in the assessment of DILI as well as in the early stages of drug development to rule out potentially hepatotoxic candidates.

Agreement Among Different Scales for Causality Assessment in Drug-Induced Liver Injury.

The causality assessment of drug-induced liver injury (DILI) remains a challenge and eagerly awaits the development of reliable hepatotoxicity biomarkers. None of the different available algorithms used for the causality assessment of DILI has been universally accepted as the gold standard. This study was conducted to examine the agreement among different causality assessment scales in reporting DILI. The World Health Organization-Uppsala Monitoring Center (WHO-UMC), Naranjo, Roussel Uclaf Causality Assessment Method (RUCAM), Maria & Victorino (M & V) and Digestive Disease Week-Japan (DDW-J) assessment scales were used to compare the causalities in all the reported cases of DILI in our adverse drug reaction (ADR) monitoring centre from January 2014 to June 2017. The probability of the causality assessment was classified as 'definite', 'probable', 'possible' and 'unlikely'. The agreement obtained among the causality assessments was analysed using the weighted kappa (κ w) test. A total of 33 cases of DILI were included in our analyses. Anti-tubercular therapy (ATT) and methotrexate were the drugs that most commonly caused DILI. The overall agreement among the different scales was poor. The best agreement was found between RUCAM and DDW-J scales (κ w: 0.685). There were discrepancies among the different causality scales in assessing DILI. This might be due to the different definitions of causality criteria and subjective variability during assessment. A personalised assessment scale incorporating the latest information on specific risk factors and evidence-based criteria for DILI is warranted.

Individual serum bile acid profiling in rats aids in human risk assessment of drug-induced liver injury due to BSEP inhibition

Drug-induced liver injury (DILI) has been the most frequent cause of post-marketing drug withdrawals in the last 50years. The multifactorial nature of events that precede severe liver injury in human patients is difficult to model in rodents due to a variety of confounding or contributing factors that include disease state, concurrent medications, and translational species differences. In retrospective analyses, a consistent risk factor for DILI has been the inhibition of the Bile Salt Export Pump (BSEP). One compound known for potent BSEP inhibition and severe DILI is troglitazone. The purpose of the current study is to determine if serum profiling of 19 individual bile acids by liquid chromatography-mass spectrometry (LC/MS) can detect perturbations in bile acid homeostasis in rats after acute intravenous (IV) administration of vehicle or 5, 25, or 50mg/kg troglitazone. Minimal serum transaminase elevations (approximately two-fold) were observed with no evidence of microscopic liver injury. However, marked changes in individual serum bile acids occurred, with dose-dependent increases in the majority of the bile acids profiled. When compared to predose baseline values, tauromuricholic acid and taurocholic acid had the most robust increase in serum levels and dynamic range, with a maximum fold increase from baseline of 34-fold and 29-fold, respectively. Peak bile acid increases occurred within 2hours (h) after dosing and returned to baseline values before 24h. In conclusion, serum bile acid profiling can potentially identify a mechanistic risk of clinical DILI that could be poorly detected by traditional toxicity endpoints.

Tools to Measure Cell Health and Cytotoxicity Using High Content Imaging and Analysis.

High content screening (HCS)-based multiparametric measurements are very useful in early toxicity testing and safety assessment during drug development, and useful in evaluating the impact from new food supplements and environmental toxicants. Mitochondrial membrane potential, plasma membrane permeability, oxidative stress, phosphoplipidosis, and steatosis are a few of the important markers routinely studied for the assessment of drug-induced liver injury and toxicity. Mitochondrial dysfunction leads to oxidative stress and cell death. Liver injury from drug-induced phospholipidosis and steatosis is routinely studied in hepatotoxicity investigations to determine the risk factors and fate of drugs or chemical compounds as some drugs can lead to defects in lipid metabolism and accumulation of lipids in lysosomes. In this chapter, we describe fluorescent reagents and the protocols for the measurement of various parameters such as mitochondrial membrane potential, plasma membrane permeability, oxidative stress, phospholipidosis, and steatosis using high content imaging-based methodologies and instrumentation.

Application of 3D liver microtissues for assessment of drug-induced liver injury (DILI) and for studying liver steatosis

We sought to evaluate a new regional segmentation method for use with three-dimensional (3D) non-contrast abdominal CT images and to report the preliminary results.The proposed method was evaluated in ten cases. Manually segmented areas were used as the gold standard for evaluation. To compare the standard and the extracted liver regions, the degree of coincidence R% was redefined by transforming a volumetric overlap error. We also evaluated the influence of varying the density window size in terms of setting the starting points.We confirmed in ten cases that our method could segment the liver region more precisely than the conventional method. A size of window 15 voxels was optimal as the starting point in all cases.We demonstrated the accuracy of a 3D semiautomatic liver segmentation method for non-contrast CT. This method promises to offer radiologists a time-efficient segmentation aid.

In silico weight of evidence assessment of drug-induced liver injury in humans

Emerging technologies are playing a major role in the generation of new approaches to assess the safety of both foods and drugs. However, the integration of emerging technologies in the regulatory decision-making process requires rigorous assessment and consensus amongst international partners and research communities. To that end, the Global Coalition for Regulatory Science Research (GCRSR) in partnership with the Brazilian Health Surveillance Agency (ANVISA) hosted the seventh Global Summit on Regulatory Science (GSRS17) in Brasilia, Brazil on September 18–20, 2017 to discuss the role of new approaches in regulatory science with a specific emphasis on applications in food and medical product safety. The global regulatory landscape concerning the application of new technologies was assessed in several countries worldwide. Challenges and issues were discussed in the context of developing an international consensus for objective criteria in the development, application and review of emerging technologies. The need for advanced approaches to allow for faster, less expensive and more predictive methodologies was elaborated. In addition, the strengths and weaknesses of each new approach was discussed. And finally, the need for standards and reproducible approaches was reviewed to enhance the application of the emerging technologies to improve food and drug safety. The overarching goal of GSRS17 was to provide a venue where regulators and researchers meet to develop collaborations addressing the most pressing scientific challenges and facilitate the adoption of novel technical innovations to advance the field of regulatory science.