Drug-Induced Liver Injury: Highlights and Controversies in the Recent Literature

Hepatic organoids move from adolescence to maturity

Since organoids were developed 15 years ago, they are now in their adolescence as a research tool. The ability to generate 'tissue in a dish' has created enormous opportunities for biomedical research. We examine the contributions that hepatic organoids have made to three areas of liver research: as a source of cells and tissue for basic research, for drug discovery and drug safety testing, and for understanding disease pathobiology. We discuss the features that enable hepatic organoids to provide useful models for human liver diseases and identify four types of advances that will enable them to become a mature (i.e., adult) research tool over the next 5 years. During this period, advances in single-cell RNA sequencing and CRISPR technologies coupled with improved hepatic organoid methodology, which enables them to have a wider range of cell types that are present in liver and to be grown in microwells, will generate discoveries that will dramatically advance our understanding of liver development and the pathogenesis of liver diseases. It will generate also new approaches for treating liver fibrosis, which remains a major public health problem with few treatment options.

Applications of 3D organoids in toxicological studies: a comprehensive analysis based on bibliometrics and advances in toxicological mechanisms

A mechanism exploration is an important part of toxicological studies. However, traditional cell and animal models can no longer meet the current needs for in-depth studies of toxicological mechanisms. The three-dimensional (3D) organoid derived from human embryonic stem cells (hESC) or induced pluripotent stem cells (hiPSC) is an ideal experimental model for the study of toxicological effects and mechanisms, which further recapitulates the human tissue microenvironment and provides a reliable method for studying complex cell-cell interactions. This article provides a comprehensive overview of the state of the 3D organoid technology in toxicological studies, including a bibliometric analysis of the existing literature and an exploration of the latest advances in toxicological mechanisms. The use of 3D organoids in toxicology research is growing rapidly, with applications in disease modeling, organ-on-chips, and drug toxicity screening being emphasized, but academic communications among countries/regions, institutions, and research scholars need to be further strengthened. Attempts to study the toxicological mechanisms of exogenous chemicals such as heavy metals, nanoparticles, drugs and organic pollutants are also increasing. It can be expected that 3D organoids can be better applied to the safety evaluation of exogenous chemicals by establishing a standardized methodology.

Risk Factors for Immune Checkpoint Inhibitor-Induced Liver Injury and the Significance of Liver Biopsy

Immune checkpoint inhibitor (ICI)-induced liver injury (LI) is a common adverse event, but the clinical characteristics based on the classification of hepatocellular injury and cholestatic types are not fully evaluated. This study aims to analyze risk factors and histological findings in relation to the classification of ICI-induced LI. In total, 254 ICI-induced LI patients among 1086 treated with ICIs between September 2014 and March 2022 were classified according to the diagnostic criteria for drug-induced LI (DILI), and their risk factors and outcomes were evaluated. Kaplan-Meier analyses showed that overall survival in patients with hepatocellular-injury-type LI was significantly longer than others (p < 0.05). Regarding pre-treatment factors, the lymphocyte count was significantly higher in patients with ICI-induced LI, especially in hepatocellular-injury-type LI. Gamma glutamyl transferase (γGTP) and alkaline phosphatase (ALP) were also significantly lower in patients with ICI-induced LI (p < 0.05). Multivariate analyses revealed that malignant melanoma, high lymphocyte count, and low ALP levels were extracted as factors contributing to hepatocellular-injury-type LI. The histological findings among 37 patients diagnosed as ICI-induced LI via liver biopsy also revealed that the spotty/focal necrosis was significantly frequent in hepatocellular-injury-type LI, whereas ductular reactions were frequently observed in cholestatic-type LI. It is suggested that the histological inflammation pattern in patients with LI is closely correlated with the type of DILI.

Human Leucocyte Antigen Genetics in Idiosyncratic Drug-Induced Liver Injury with Evidence Based on the Roussel Uclaf Causality Assessment Method

The human leucocyte antigen (HLA) allele variability was studied in cohorts of patients with idiosyncratic drug-induced liver injury (iDILI). Some reports showed an association between HLA genetics and iDILI, proposing HLA alleles as a potential risk factor for the liver injury. However, the strength of such assumptions heavily depends on the quality of the iDILI diagnosis, calling for a thorough analysis. Using the PubMed database and Google Science, a total of 25 reports of case series or single cases were retrieved using the terms HLA genes and iDILI. It turned out that in 10/25 reports (40%), HLA genetics were determined in iDILI cases, for which no causality assessment method (CAM) was used or a non-validated tool was applied, meaning the findings were based on subjective opinion, providing disputable results and hence not scoring individual key elements. By contrast, in most iDILI reports (60%), the Roussel Uclaf Causality Assessment Method (RUCAM) was applied, which is the diagnostic algorithm preferred worldwide to assess causality in iDILI cases and represents a quantitative, objective tool that has been well validated by both internal and external DILI experts. The RUCAM provided evidence-based results concerning liver injury by 1 drug class (antituberculotics + antiretrovirals) and 19 different drugs, comprising 900 iDILI cases. Among the top-ranking drugs were amoxicillin-clavulanate (290 cases, HLA A*02:01 or HLA A*30:02), followed by flucloxacillin (255 cases, HLA B*57:01), trimethoprim-sulfamethoxazole (86 cases, HLA B*14:01 or HLA B*14:02), methimazole (40 cases, HLA C*03:02), carbamazepine (29 cases, HLA A*31:01), and nitrofurantoin (26 cases, HLA A*33:01). In conclusion, the HLA genetics in 900 idiosyncratic drug-induced liver injury cases with evidence based on the RUCAM are available for studying the mechanistic steps leading to the injury, including metabolic factors through cytochrome P450 isoforms and processes that activate the innate immune system to the adaptive immune system.

Influence of N-acetyltransferase 2 polymorphisms and clinical variables on liver function profile of tuberculosis patients

BACKGROUND

Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase 2 (NAT2) gene as well as several other clinical factors can contribute to the elevation of liver function test values in tuberculosis (TB) patients receiving antitubercular therapy (ATT).

RESEARCH DESIGN AND METHODS

A prospective study involving dynamic monitoring of the liver function tests among 130 TB patients from baseline to 98 days post ATT initiation was undertaken to assess the influence of pharmacogenomic and clinical variables on the elevation of liver function test values. Genomic DNA was extracted from serum samples for the assessment of NAT2 SNPs. Further, within this study population, we conducted a case control study to identify the odds of developing ATT-induced drug-induced liver injury (DILI) based on NAT2 SNPs, genotype and phenotype, and clinical variables.

RESULTS

NAT2 slow acetylators had higher mean [90%CI] liver function test values for 8-28 days post ATT and higher odds of developing DILI (OR: 2.73, 90%CI: 1.05-7.09) than intermediate acetylators/rapid acetylators.

CONCLUSION

The current study findings provide evidence for closer monitoring among TB patients with specific NAT2 SNPs, genotype and phenotype, and clinical variables, particularly between the period of more than a week to one-month post ATT initiation for better treatment outcomes.

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.

Industry Review of Best Practices for Risk Management of Drug-Induced Liver Injury from Development to Real-World Use

The relative treatment benefit of a drug for patients during development, marketing authorization review, or after approval includes an assessment of the risk of drug-induced liver injury (DILI). In this article, the Pharmacovigilance and Risk Mitigation Working Group of the IQ-DILI Initiative launched in June 2016 within the International Consortium for Innovation and Quality in Pharmaceutical Development presents and reviews three key topics for essential risk management activities to identify, characterize, monitor, mitigate, and communicate DILI risk associated with small molecules during drug development. The three topics are: (1) Current best practices for characterizing the DILI phenotype and the severity and incidence of DILI in the treatment population, including DILI identification, prediction and recovery. (2) Characterization of the relative treatment benefit for patients who will be exposed to a drug and the attendant risk of DILI in conjunction with existing global risk mitigation strategies. (3) Implementation of risk mitigation strategies during drug development highlighting patient factors, healthcare settings and site of product administration, and prescriber and healthcare provider factors. Industry guidance is provided for assessing whether the product labeling is sufficient to minimize the risk of DILI or whether a United States Food and Drug Administration (FDA) Risk Evaluation and Mitigation Strategy (REMS) or European Medicines Agency (EMA) Risk Management Plan (RMP) with additional Risk Minimization Measures (aRMM) is needed.

Relevance of NAT2 genotype and clinical factors to risk for antituberculosis drug-induced liver injury

The study analyzes the risk factors associated with antituberculosis drug-induced liver injury (ATB-DILI), and the relationship between ATB-DILI and NAT2 gene polymorphisms. Out of the 324 included patients, 57 (17.59%) developed ATB-DILI. Age, history of liver disease, alcohol consumption and timing of antituberculosis (ATB) treatment were independent risk factors for ATB-DILI in the patients with tuberculosis (TB; p < 0.05). There was a significant difference in the distribution of NAT2 metabolic phenotypes between the study group and the control group (p < 0.05). The ATB drug treatment for pulmonary TB can cause a high incidence of ATB-DILI. Age, history of liver disease, alcohol consumption and timing of ATB treatment are independent risk factors for ATB-DILI in patients with TB.

Integrating Metabolomics and Network Pharmacology to Decipher the Hepatoprotective Effect Mechanisms of Magnesium Isoglycyrrhizinate Injection

This study aimed to explore the liver protective effects of a fourth-generation glycyrrhizic acid product (magnesium isoglycyrrhizinate injection, MII) in the treatment of mice with drug-induced liver injury-specifically, to determine its effects on plasma metabolites. Moreover, the possible mechanism of its intervention in lipid metabolism and amino acid metabolism through the liver protective effect was preliminarily explored, combined with network pharmacology. The liver injury model of mice was established using acetaminophen (APAP). The protective effect of MII on the mice model was evaluated using pathological tissue sections and biochemical indices such as alanine transaminase (ALT), aspartate aminotransferase (AST), and superoxide dismutase (SOD). Metabolomics analysis of plasma was performed using the UHPLC-QTOF/MS technique to screen for potential biomarkers and enriched metabolic pathways. The potential targets and pathways of MII were predicted by network pharmacology, and the mechanism was verified by Western blot analysis. MII significantly improved the pathological liver changes in mice with liver injury. The content of ALT and AST was decreased, and the activity of SOD was increased significantly (p < 0.05, 0.01). A total of 29 potential biomarkers were identified in the metabolomics analysis, mainly involving seven pathways, such as lipid metabolism and amino acid metabolism. A total of 44 intersection targets of MII in the treatment of liver injury were obtained by network pharmacology, involving lipid metabolism and other related pathways. Western blot analysis results showed that MII could significantly reduce the expression of JAK2 and STAT3. MII can effectively ameliorate liver injury in modeled mice through related pathways such as lipid metabolism and amino acid metabolism. This study could provide not only a scientific basis for the elucidation of the mechanism of action of MII in exerting a hepatoprotective effect, but also a reference for its rational clinical application.

Utility of Liver Biopsy in the Diagnosis and Management of Possible Drug-Induced Liver Injury in Patients Receiving Antituberculosis Therapy: A Retrospective Study

BACKGROUND

Drug-induced liver injury (DILI) secondary to ATT treatment (TB-DILI) is reported in 2-28% of patients. We present here a series of clinical cases of suspected DILI arising during antituberculosis treatment, studied with the aid of liver biopsy.

METHODS

this was a retrospective descriptive study including 10 tuberculosis patients who underwent liver biopsy for suspected TB-DILI at the "Lazzaro Spallanzani" Institute from 2017 to 2022.

RESULTS

Ten patients who underwent LB were extracted from the database and included in the retrospective study cohort. According to the clinical classification, eight patients had hepatocellular liver injury, one patient had cholestatic injury, and another had mixed-type injury. Histopathological diagnosis revealed liver damage due to DILI in 5/10 (50%) cases. In one case, liver biopsy showed necrotizing granulomatous hepatitis.

CONCLUSIONS

Severe and persistent elevation of hepatic transaminases, hepatic cholestasis despite discontinuation of therapy, and other suspected hepatic conditions are indications for liver biopsy, which remains a valuable tool in the evaluation of selected tuberculosis patients with suspected DILI for many reasons. However, the decision to perform a liver biopsy should be based on clinical judgment, considering the benefits and risks of the procedure.

Drug induced liver injury - a 2023 update

Drug-Induced Liver Injury (DILI) constitutes hepatic damage attributed to drug exposure. DILI may be categorized as hepatocellular, cholestatic or mixed and might also involve immune responses. When DILI occurs in dose-dependent manner, it is referred to as intrinsic, while if the injury occurs spontaneously, it is termed as idiosyncratic. This review predominately focused on idiosyncratic liver injury. The established molecular mechanisms for DILI include (1) mitochondria dysfunction, (2) increased reactive oxygen species levels, (3) presence of elevated apoptosis and necrosis, (4) and bile duct injuries associated with immune mediated pathways. However, it should be emphasized that the underlying mechanisms responsible for DILI are still unknown. Prevention strategies are critical as incidences occur frequently, and treatment options are limited once the injury has developed. The aim of this review was to utilize retrospective cohort studies from across the globe to gain insight into epidemiological patterns. This review considers (1) what is currently known regarding the mechanisms underlying DILI, (2) discusses potential risk factors and (3) implications of the coronavirus pandemic on DILI presentation and research. Future perspectives are also considered and discussed and include potential new biomarkers, causality assessment and reporting methods.

Epidemiology and Management of Drug-induced Liver Injury: Importance of the Updated RUCAM

Drug-induced liver injury (DILI) is a major cause of acute liver injury, liver failure, and liver transplantation worldwide. In recent years, immune checkpoint inhibitors have become widely used. This has led to an increase in DILI, for which pathophysiology and management methods differ significantly from the past. As the number of cases of acute liver injury and liver transplantation due to DILI is expected to increase, information about a DILI is becoming more valuable. DILI is classified into two types according to its etiology: intrinsic DILI, in which the drug or its metabolites cause liver damage that is dose-dependent and predictable; and idiosyncratic DILI, in which liver damage is also dose-independent but unpredictable. In addition, depending on the course of the disease, chronic DILI or drug-induced autoimmune hepatitis may be present. The number of DILI cases caused by antimicrobial agents is decreasing, whereas that caused by drugs for malignant tumors and health foods is increasing. The Roussel Uclaf Causality Assessment Method is widely used to assess causality in DILI. Liver injury is a type of immune-related adverse event. The pattern of hepatic injury in immune-related adverse events is mostly hepatocellular, but mixed type and bile stasis have also been reported. Sclerosing cholangitis caused by immune checkpoint inhibitors has also been reported as a unique type of injury. Treatment mainly comprises withdrawal of immune checkpoint inhibitors and steroid administration; however, mycophenolate mofetil may be considered if the disease is refractory to steroids.

Incidence, risk factors and outcomes of checkpoint inhibitor-induced liver injury: A 10-year real-world retrospective cohort study

Background & Aims

Checkpoint inhibitors (CPI) account for increasing numbers of drug-induced liver injury (DILI) cases. We aimed to determine the incidence rate and risk factors associated with checkpoint inhibitor-induced liver injury (ChILI).

Methods

Prescription event monitoring was performed on all melanoma and renal cancer patients who received CPI at a tertiary centre between 2011 and 2021. ChILI cases were identified using the definitions, grading, and causality assessment methods validated for DILI. We assessed risk factors associated with ChILI in CPI-naive patients using multivariable logistic regression model. Consecutive patients with suspected ChILI from two other tertiary centres were adjudicated and combined for case characterisation and outcomes of ChILI.

Results

Out of 432 patients who received CPI over 10 years, ChILI occurred in 38 (8.8%) with an overall incidence rate of 11.5 per 1,000 person-months (95% CI 8.2-15.8). Probability of ChILI was highest in combination therapy (32%) and no new events occurred beyond 135 days of treatment. Risk factor analysis showed that combination therapy, female sex, higher baseline alanine transferase level and lower baseline alkaline phosphatase level were independently associated with higher risk of ChILI. In total, 99 patients were adjudicated to have ChILI from three centres. Although Common Terminology Criteria for Adverse Events classified 20 patients (20.2%) to have 'life-threatening' grade 4 hepatitis, ChILI severity was graded as mild in 45 (45.5%) and moderate in the remaining 54 (54.5%) cases.

Conclusions

The real-world risk of ChILI is higher than previously reported. Among patients receiving dual CPI, this risk falls markedly after 4.5 months. As Common Terminology Criteria for Adverse Events overestimates its clinical severity, case-definition, evaluation and management of ChILI should be revised to harmonise care.

Impact and implications

Using prescription event monitoring over a 10-year period, the incidence rate of checkpoint inhibitor induced liver injury (ChILI) based on established case definitions for drug-induced liver injury (DILI) is 11.5 per 1,000 person-months. Formal causality assessment identified an alternative cause in 19% of patients with suspected ChILI highlighting the importance of systematic evaluation by clinicians to minimise unnecessary immunosuppression. Intensity of monitoring in patients receiving combination therapy regime after 4.5 months of therapy can be reduced as the risk of new onset ChILI beyond this point is minimal. Current Common Terminology Criteria for Adverse Events (CTCAE) grading overestimates clinical severity of ChILI and hence contributes to avoidable hospitalisation.

Drug-induced liver injury and COVID-19: Use of artificial intelligence and the updated Roussel Uclaf Causality Assessment Method in clinical practice

BACKGROUND

Liver injury is a relevant condition in coronavirus disease 2019 (COVID-19) inpatients. Pathophysiology varies from direct infection by virus, systemic inflammation or drug-induced adverse reaction (DILI). DILI detection and monitoring is clinically relevant, as it may contribute to poor prognosis, prolonged hospitalization and increase indirect healthcare costs. Artificial Intelligence (AI) applied in data mining of electronic medical records combining abnormal liver tests, keyword searching tools, and risk factors analysis is a relevant opportunity for early DILI detection by automated algorithms.

AIM

To describe DILI cases in COVID-19 inpatients detected from data mining in electronic medical records (EMR) using AI and the updated Roussel Uclaf Causality Assessment Method (RUCAM).

METHODS

The study was conducted in March 2021 in a hospital in southern Brazil. The NoHarm^© system uses AI to support decision making in clinical pharmacy. Hospital admissions were 100523 during this period, of which 478 met the inclusion criteria. From these, 290 inpatients were excluded due to alternative causes of liver injury and/or due to not having COVID-19. We manually reviewed the EMR of 188 patients for DILI investigation. Absence of clinical information excluded most eligible patients. The DILI assessment causality was possible via the updated RUCAM in 17 patients.

RESULTS

Mean patient age was 53 years (SD ± 18.37; range 22-83), most were male (70%), and admitted to the non-intensive care unit sector (65%). Liver injury pattern was mainly mixed, mean time to normalization of liver markers was 10 d, and mean length of hospitalization was 20.5 d (SD ± 16; range 7-70). Almost all patients recovered from DILI and one patient died of multiple organ failure. There were 31 suspected drugs with the following RUCAM score: Possible (n = 24), probable (n = 5), and unlikely (n = 2). DILI agents in our study were ivermectin, bicalutamide, linezolid, azithromycin, ceftriaxone, amoxicillin-clavulanate, tocilizumab, piperacillin-tazobactam, and albendazole. Lack of essential clinical information excluded most patients. Although rare, DILI is a relevant clinical condition in COVID-19 patients and may contribute to poor prognostics.

CONCLUSION

The incidence of DILI in COVID-19 inpatients is rare and the absence of relevant clinical information on EMR may underestimate DILI rates. Prospects involve creation and validation of alerts for risk factors in all DILI patients based on RUCAM assessment causality, alterations of liver biomarkers and AI and machine learning.

Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery

Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical industry and research, where it has been utilized to efficiently identify new chemical entities with desirable properties. The application of AI algorithms to drug discovery presents both remarkable opportunities and challenges. This review article focuses on the transformative role of AI in medicinal chemistry. We delve into the applications of machine learning and deep learning techniques in drug screening and design, discussing their potential to expedite the early drug discovery process. In particular, we provide a comprehensive overview of the use of AI algorithms in predicting protein structures, drug-target interactions, and molecular properties such as drug toxicity. While AI has accelerated the drug discovery process, data quality issues and technological constraints remain challenges. Nonetheless, new relationships and methods have been unveiled, demonstrating AI's expanding potential in predicting and understanding drug interactions and properties. For its full potential to be realized, interdisciplinary collaboration is essential. This review underscores AI's growing influence on the future trajectory of medicinal chemistry and stresses the importance of ongoing synergies between computational and domain experts.

[Drug toxic hepatopathy - an underestimated danger]

Drug-induced toxic hepatopathies and drug-induced liver injury, DILI, are characterized by a variety of clinical manifestations and therefore represent a significant diagnostic challenge. This article shows how DILI is diagnosed and what therapy options exist. Current special cases of DILI genesis are also discussed (DOACs, IBD drugs, tyrosine kinase inhibitors). These newer substances and corresponding hepatotoxic effects are not yet fully understood. The internationally recognized and online available RUCAM score (Roussel Uclaf Causality Assessment Method) helps to assess the probability of drug-related toxic liver damage.

Advances in Idiosyncratic Drug-Induced Liver Injury Issues: New Clinical and Mechanistic Analysis Due to Roussel Uclaf Causality Assessment Method Use

Clinical and mechanistic considerations in idiosyncratic drug-induced liver injury (iDILI) remain challenging topics when they are derived from mere case narratives or iDILI cases without valid diagnosis. To overcome these issues, attempts should be made on pathogenetic aspects based on published clinical iDILI cases firmly diagnosed by the original RUCAM (Roussel Uclaf Causality Assessment Method) or the RUCAM version updated in 2016. Analysis of RUCAM-based iDILI cases allowed for evaluating immune and genetic data obtained from the serum and the liver of affected patients. For instance, strong evidence for immune reactions in the liver of patients with RUCAM-based iDILI was provided by the detection of serum anti-CYP 2E1 due to drugs like volatile anesthetics sevoflurane and desflurane, partially associated with the formation of trifluoroacetyl (TFA) halide as toxic intermediates that form protein adducts and may generate reactive oxygen species (ROS). This is accompanied by production of anti-TFA antibodies detected in the serum of these patients. Other RUCAM-based studies on serum ANA (anti-nuclear antibodies) and SMA (anti-smooth muscle antibodies) associated with AIDILI (autoimmune DILI) syn DIAIH (drug-induced autoimmune hepatitis) provide additional evidence of immunological reactions with monocytes as one of several promoting immune cells. In addition, in the blood plasma of patients, mediators like the cytokines IL-22, IL-22 binding protein (IL-22BP), IL-6, IL-10, IL 12p70, IL-17A, IL-23, IP-10, or chemokines such as CD206 and sCD163 were found in DILI due to anti-tuberculosis drugs as ascertained by the prospective updated RUCAM, which scored a high causality. RUCAM-based analysis also provided compelling evidence of genetic factors such as HLA (human leucocyte antigen) alleles contributing to initiate iDILI by a few drugs. In conclusion, analysis of published RUCAM-based iDILI cases provided firm evidence of immune and genetic processes involved in iDILI caused by specific drugs.

AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules

Drug-induced liver injury (DILI), believed to be a multifactorial toxicity, has been a leading cause of attrition of small molecules during discovery, clinical development, and postmarketing. Identification of DILI risk early reduces the costs and cycle times associated with drug development. In recent years, several groups have reported predictive models that use physicochemical properties or in vitro and in vivo assay endpoints; however, these approaches have not accounted for liver-expressed proteins and drug molecules. To address this gap, we have developed an integrated artificial intelligence/machine learning (AI/ML) model to predict DILI severity for small molecules using a combination of physicochemical properties and off-target interactions predicted in silico. We compiled a data set of 603 diverse compounds from public databases. Among them, 164 were categorized as Most DILI (M-DILI), 245 as Less DILI (L-DILI), and 194 as No DILI (N-DILI) by the FDA. Six machine learning methods were used to create a consensus model for predicting the DILI potential. These methods include k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), Naïve Bayes (NB), artificial neural network (ANN), logistic regression (LR), weighted average ensemble learning (WA) and penalized logistic regression (PLR). Among the analyzed ML methods, SVM, RF, LR, WA, and PLR identified M-DILI and N-DILI compounds, achieving a receiver operating characteristic area under the curve of 0.88, sensitivity of 0.73, and specificity of 0.9. Approximately 43 off-targets, along with physicochemical properties (fsp³, log S, basicity, reactive functional groups, and predicted metabolites), were identified as significant factors in distinguishing between M-DILI and N-DILI compounds. The key off-targets that we identified include: PTGS1, PTGS2, SLC22A12, PPARγ, RXRA, CYP2C9, AKR1C3, MGLL, RET, AR, and ABCC4. The present AI/ML computational approach therefore demonstrates that the integration of physicochemical properties and predicted on- and off-target biological interactions can significantly improve DILI predictivity compared to chemical properties alone.

Molecular Idiosyncratic Toxicology of Drugs in the Human Liver Compared with Animals: Basic Considerations

Drug induced liver injury (DILI) occurs in patients exposed to drugs at recommended doses that leads to idiosyncratic DILI and provides an excellent human model with well described clinical features, liver injury pattern, and diagnostic criteria, based on patients assessed for causality using RUCAM (Roussel Uclaf Causality Assessment Method) as original method of 1993 or its update of 2016. Overall, 81,856 RUCAM based DILI cases have been published until mid of 2020, allowing now for an analysis of mechanistic issues of the disease. From selected DILI cases with verified diagnosis by using RUCAM, direct evidence was provided for the involvement of the innate and adapted immune system as well as genetic HLA (Human Leucocyte Antigen) genotypes. Direct evidence for a role of hepatic immune systems was substantiated by (1) the detection of anti-CYP (Cytochrome P450) isoforms in the plasma of affected patients, in line with the observation that 65% of the drugs most implicated in DILI are metabolized by a range of CYP isoforms, (2) the DIAIH (drug induced autoimmune hepatitis), a subgroup of idiosyncratic DILI, which is characterized by high RUCAM causality gradings and the detection of plasma antibodies such as positive serum anti-nuclear antibodies (ANA) and anti-smooth muscle antibodies (ASMA), rarely also anti-mitochondrial antibodies (AMA), (3) the effective treatment with glucocorticoids in part of an unselected RUCAM based DILI group, and (4) its rare association with the immune-triggered Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) caused by a small group of drugs. Direct evidence of a genetic basis of idiosyncratic DILI was shown by the association of several HLA genotypes for DILI caused by selected drugs. Finally, animal models of idiosyncratic DILI mimicking human immune and genetic features are not available and further search likely will be unsuccessful. In essence and based on cases of DILI with verified diagnosis using RUCAM for causality evaluation, there is now substantial direct evidence that immune mechanisms and genetics can account for idiosyncratic DILI by many but not all implicated drugs, which may help understand the mechanistic background of the disease and contribute to new approaches of therapy and prevention.

Drug-induced liver injury: a comprehensive review

Drug-induced liver injury (DILI) remains a challenge in clinical practice and is still a diagnosis of exclusion. Although it has a low incidence amongst the general population, DILI accounts for most cases of acute liver failure with a fatality rate of up to 50%. While multiple mechanisms of DILI have been postulated, there is no clear causal relationship between drugs, risk factors and mechanisms of DILI. Current best practice relies on a combination of high clinical suspicion, thorough clinical history of risk factors and timeline, and extensive hepatological investigations as supported by the international Roussel Uclaf Causality Assessment Method criteria, the latter considered a key diagnostic algorithm for DILI. This review focuses on DILI classification, risk factors, clinical evaluation, future biomarkers and management, with the aim of facilitating physicians to correctly identify DILI early in presentation.

Hepatocyte ferroptosis contributes to anti-tuberculosis drug-induced liver injury: Involvement of the HIF-1α/SLC7A11/GPx4 axis

Anti-tuberculosis drug-induced liver injury (ATB-DILI) is a common serious adverse event observed during the clinical treatment of tuberculosis. However, the molecular mechanisms underlying ATB-DILI remain unclear. A recent study has indicated that ferroptosis and lipid peroxidation may be involved in liver injury. Therefore, this study aimed to investigate the role of ferroptosis in the molecular mechanisms underlying ATB-DILI. Our results showed that anti-TB drugs induced hepatocyte damage in vivo and in vitro and inhibited BRL-3A cell activity in a dose-dependent manner, accompanied by increased lipid peroxidation and reduced antioxidant levels. Moreover, ACSL4 expression and Fe²⁺ concentration significantly increased following anti-TB drug treatment. Interestingly, anti-TB drug-induced hepatocyte damage was reversed by ferrostatin-1 (Fer-1, a specific ferroptosis inhibitor). In contrast, treatment with erastin (a ferroptosis inducer) resulted in further elevation of ferroptosis indicators. Additionally, we also found that anti-TB drug treatment inhibited HIF-1α/SLC7A11/GPx4 signaling in vivo and in vitro. Notably, HIF-1α knockdown significantly enhanced anti-TB drug-induced ferroptotic events and the subsequent exacerbation of hepatocyte damage. In conclusion, our findings indicated that ferroptosis plays a crucial role in the development of ATB-DILI. Furthermore, anti-TB drug-induced hepatocyte ferroptosis was shown to be regulated by HIF-1α/SLC7A11/GPx4 signaling. These findings shed new light on the mechanisms underlying ATB-DILI and suggest novel therapeutic strategies for this disease.

Incidence and Economic Burden of Adverse Drug Reactions in Hospitalization: A Prospective Study in Korea

BACKGROUND

Adverse drug reactions (ADRs) are escalating, and their socioeconomic burden is increasing. However, large-scale prospective studies investigating ADRs during hospitalization are rare in Korea. We prospectively investigated the incidence, characteristics, and economic burden of ADRs in hospitalized patients based on electronic medical records (EMRs).

METHODS

Among patients admitted to three hospitals from October 2016 to October 2017, 5,000 patients were randomly selected and prospectively observed during hospitalization. Research nurses monitored and detected patients who had symptoms, signs, or laboratory findings suspicious for ADRs using an EMR-based detection protocol. Next, allergy and ADR specialists reviewed the medical records to determine the relationship between adverse reactions and drugs. Cases in which a causal relationship was certain, probable/likely, or possible were included in the ADR cases. Clinically meaningful ADR cases or those leading to prolonged hospitalization were defined as significant ADRs.

RESULTS

ADRs occurred in 510 (10.2%) patients. The mean length of hospital stay was approximately 5 days longer in patients with ADRs. Opioids accounted for the highest percentage of total ADRs. Significant ADRs were observed in 148 (3.0%) patients. Antibiotics accounted for the highest percentage of significant ADRs. Drug hypersensitivity reactions (DHRs) occurred in 88 (1.8%) patients. Antibiotics accounted for the highest percentage of DHRs. The average medical expenses for one day of hospitalization per patient were highest in significant ADRs, followed by non-significant ADRs, and non-ADRs.

CONCLUSION

ADRs in hospitalized patients are an important clinical issue, resulting in a substantial socioeconomic burden. EMR-based strategy could be a useful tool for ADR monitoring and early detection.

Treatment of Drug-Induced Liver Injury

Current pharmacotherapy options of drug-induced liver injury (DILI) remain under discussion and are now evaluated in this analysis. Needless to say, the use of the offending drug must be stopped as soon as DILI is suspected. Normal dosed drugs may cause idiosyncratic DILI, and drugs taken in overdose commonly lead to intrinsic DILI. Empirically used but not substantiated regarding efficiency by randomized controlled trials (RCTs) is the intravenous antidote treatment with N-acetylcysteine (NAC) in patients with intrinsic DILI by N-acetyl-p-aminophenol (APAP) overdose. Good data recommending pharmacotherapy in idiosyncratic DILI caused by hundreds of different drugs are lacking. Indeed, a recent analysis revealed that just eight RCTs have been published, and in only two out of eight trials were DILI cases evaluated for causality by the worldwide used Roussel Uclaf Causality Assessment Method (RUCAM), representing overall a significant methodology flaw, as results of DILI RCTs lacking RUCAM are misleading since many DILI cases are known to be attributable erroneously to nondrug alternative causes. In line with these major shortcomings and mostly based on anecdotal reports, glucocorticoids (GCs) and other immuno-suppressants may be given empirically in carefully selected patients with idiosyncratic DILI exhibiting autoimmune features or caused by immune checkpoint inhibitors (ICIs), while some patients with cholestatic DILI may benefit from ursodeoxycholic acid use; in other patients with drug-induced hepatic sinusoidal obstruction syndrome (HSOS) and coagulopathy risks, the indication for anticoagulants should be considered. In view of many other mechanistic factors such as the hepatic microsomal cytochrome P450 with a generation of reactive oxygen species (ROS), ferroptosis with toxicity of intracellular iron, and modification of the gut microbiome, additional therapy options may be available in the future. In summation, stopping the offending drug is still the first line of therapy for most instances of acute DILI, while various therapies are applied empirically and not based on good data from RCTs awaiting further trials using the updated RUCAM that asks for strict exclusion and inclusion details like liver injury criteria and provides valid causality rankings of probable and highly probable grades.

Standard Venipuncture vs a Capillary Blood Collection Device for the Prospective Determination of Abnormal Liver Chemistry

Background

Abnormal liver function is a common manifestation of human disease and may also occur in approved and investigational medications as drug-induced liver injury (DILI). Capillary blood collection devices may allow for more frequent and convenient measurement outside of the clinic. Validation of such approaches is lacking.

Methods

This prospective, biospecimens collection study evaluated the Tasso+ in patients with abnormal liver tests (NCT05259618). The primary objective was to define the concordance of alanine aminotransferase (ALT) obtained via Tasso+ compared to standard venipuncture. Secondary objectives included measurement of 14 other analytes and patient surveys. At the time of venipuncture, 2 Tasso+ samples were collected: one was centrifuged and shipped, and the other was refrigerated and shipped as whole blood.

Results

Thirty-six patients with elevated ALT values were enrolled. In total, 100 venipuncture, 50 Tasso+ centrifuged, and 48 Tasso+ whole blood samples were obtained. Tasso+ centrifuged samples demonstrated concordance correlation coefficients (CCC) of &gt;0.99 for ALT, alkaline phosphatase (ALP), aspartate aminotransferase (AST), and total bilirubin and CCC &gt;0.95 for albumin, chloride, enzymatic creatinine, serum glucose, magnesium, and phosphorus. Tasso+ whole blood showed CCC of &gt;0.99 for AST, bilirubin total, and enzymatic creatinine and CCC &gt;0.95 for ALT, ALP, albumin, magnesium, and phosphorus. Hemolysis was comparable across the 3 sample types, but its impact was reflected in the Tasso+ potassium data. Patient feedback indicated a very favorable patient experience.

Conclusions

The capillary blood collection device, Tasso+, showed substantial to almost perfect concordance to standard venipuncture for measurement of abnormal liver function. Studies are ongoing to validate longitudinal sampling outside of the clinic.

Clinicaltrials.gov Registration Number: NCT05259618

Machine learning insights concerning inflammatory and liver-related risk comorbidities in non-communicable and viral diseases

The liver is a key organ involved in a wide range of functions, whose damage can lead to chronic liver disease (CLD). CLD accounts for more than two million deaths worldwide, becoming a social and economic burden for most countries. Among the different factors that can cause CLD, alcohol abuse, viruses, drug treatments, and unhealthy dietary patterns top the list. These conditions prompt and perpetuate an inflammatory environment and oxidative stress imbalance that favor the development of hepatic fibrogenesis. High stages of fibrosis can eventually lead to cirrhosis or hepatocellular carcinoma (HCC). Despite the advances achieved in this field, new approaches are needed for the prevention, diagnosis, treatment, and prognosis of CLD. In this context, the scientific com-munity is using machine learning (ML) algorithms to integrate and process vast amounts of data with unprecedented performance. ML techniques allow the integration of anthropometric, genetic, clinical, biochemical, dietary, lifestyle and omics data, giving new insights to tackle CLD and bringing personalized medicine a step closer. This review summarizes the investigations where ML techniques have been applied to study new approaches that could be used in inflammatory-related, hepatitis viruses-induced, and coronavirus disease 2019-induced liver damage and enlighten the factors involved in CLD development.

Incidence and Temporal Trend of Antituberculosis Drug-Induced Liver Injury: A Systematic Review and Meta-Analysis

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards were followed, and the protocol was registered in PROSPERO (CRD42020200077). Five electronic databases were searched to identify eligible studies published between 1990 and 2022. Search terms included anti-TB treatment and drug-induced liver injury. Studies that reported the incidence of ATLI or provided sufficient data to calculate the incidence of ATLI were included, and duplicate studies were excluded. Meta-analysis was conducted on the basis of logit-transformed metrics for the incidence of ATLI with 95% confidence intervals (CIs), followed by a predefined subgroup meta-analysis. Temporal trend analyses were performed to describe the change in pooled incidence over time. A random effects metaregression was conducted to explore the source of heterogeneity. All statistical analyses were carried out using R 4.0.1.

Results

A total of 160 studies from 156 records with 116147 patients were included in the meta-analysis. Based on the random effects model, the pooled incidence of ATLI was 11.50% (95% CI: 10.10%–12.97%) and showed an upward trend over time (P < 0.001). Patients who received first-line anti-TB drugs, patients in South America, and patients with hepatitis B and C virus coinfection had a higher incidence of ATLI (13.66%, 18.16%, and 39.19%, respectively). Sensitivity analyses also confirmed this robust incidence after the exclusion of some studies. The metaregression showed that different anti-TB regimens and geographical regions were important explanatory factors of the heterogeneity between studies.

Conclusions

The present systematic review provided a basis for estimating the incidence of ATLI worldwide, which varied among patients with different anti-TB regimens in different geographical regions and with different coinfections and had an upward trend. Regular liver function monitoring is imperative for patient safety during the anti-TB treatment course.

Genetics of drug-induced liver injury: Current knowledge and future prospects

Idiosyncratic drug-induced liver injury (DILI) remains an important clinical problem, both during drug development and the prescription of a range of licensed drugs. Although rare, the consequences are serious. Ongoing studies on genetic risk factors for DILI, especially genomewide association studies, have resulted in the identification of a number of genetic risk factors, including particular HLA alleles and a few non-HLA genes, both immune-related and metabolic. Some non-HLA associations, such as N-acetyltransferase 2 in isoniazid DILI and interferon regulatory factor 6 in interferon-beta DILI are likely to be drug-specific due to the role of the associated gene, but there is also evidence for polygenic susceptibility involving pathways such as oxidative and endoplasmic reticulum stress and mitochondrial function for DILI induced by multiple drugs. Increased knowledge of genetic risk factors should assist in better understanding underlying DILI mechanisms and help improve methods for identifying hepatotoxic drugs early in development. HLA allele-specific T cell proliferation together with in silico prediction of drug binding to specific HLA proteins have confirmed genetic findings for certain common causes of DILI. However, studies in hepatocytes exposed to high drug concentrations suggest toxicity that is not dependent on genotype also occurs. It seems likely that susceptibility to DILI involves several genetic risk factors combining with other factors that affect drug levels. Despite recent progress in detecting genetic risk factors for DILI, low positive predictive values mean that general implementation of genotyping prior to prescription of potentially hepatotoxic drugs is not useful currently.

Highlights of the drug-induced liver injury literature for 2021

INTRODUCTION

In 2021, over 3,000 articles on Drug-Induced Liver Injury (DILI) were published, nearly doubling the annual number compared to 2011. This review selected DILI articles from 2021 we felt held the greatest interest and clinical relevance.

AREAS COVERED

A literature search was conducted using PubMed between 1 March 2021 and 28 February 2022. 86 articles were included. This review discusses new and established cases of hepatotoxins, including new FDA approvals and COVID-19 therapeutics. Developments in biomarkers and causality assessment methods are discussed. Updates from registries are also explored.

EXPERT OPINION

DILI diagnosis and prognostication remain challenging. Roussel Uclaf Causality Assessment Method (RUCAM) is the best option for determining causality and has been increasingly accepted by clinicians. Revised Electronic Causality Assessment Method (RECAM) may be more user-friendly and accurate but requires further validation. Quantitative systems pharmacology methods, such as DILIsym, are increasingly used to predict hepatotoxicity. Oncotherapeutic agents represent many newly approved and described causes of DILI. Such hepatotoxicity is deemed acceptable relative to the benefit these drugs offer. Drugs developed for non-life-threatening disorders may not show a favorable benefit-to-risk ratio and will be more difficult to approve. As the COVID-19 landscape evolves, its effect on DILI deserves further investigation.

Clinical Significance of Transient Asymptomatic Elevations in Aminotransferase (TAEAT) in Oncology

Monitoring for liver injury remains an important aspect of drug safety assessment, including for oncotherapeutics. When present, drug-induced liver injury may limit the use or result in the discontinuation of these agents. Drug-induced liver injury can exhibit with a wide spectrum of clinical and biochemical manifestations, ranging from transient asymptomatic elevations in aminotransferases (TAEAT) to acute liver failure. Numerous oncotherapeutics have been associated with TAEAT, with published reports indicating a phenomenon in which patients may be asymptomatic without overt liver injury despite the presence of grade ≥3 aminotransferase elevations. In this review, we discuss the occurrence of TAEAT in the context of oncology clinical trials and clinical practice, as well as the clinical relevance of this phenomenon as an adverse event in response to oncotherapeutics and the related cellular and molecular mechanisms that may underlie its occurrence. We also identify several gaps in knowledge relevant to the diagnosis and the management of TAEAT in patients receiving oncotherapeutics, and identify areas warranting further study to enable the future development of consensus guidelines to support clinical decision-making.

Liver Injury in COVID-19 Patients with Drugs as Causatives: A Systematic Review of 996 DILI Cases Published 2020/2021 Based on RUCAM as Causality Assessment Method

Patients with coronavirus disease 19 (COVID-19) commonly show abnormalities of liver tests (LTs) of undetermined cause. Considering drugs as tentative culprits, the current systematic review searched for published COVID-19 cases with suspected drug-induced liver injury (DILI) and established diagnosis using the diagnostic algorithm of RUCAM (Roussel Uclaf Causality Assessment Method). Data worldwide on DILI cases assessed by RUCAM in COVID-19 patients were sparse. A total of 6/200 reports with initially suspected 996 DILI cases in COVID-19 patients and using all RUCAM-based DILI cases allowed for a clear description of clinical features of RUCAM-based DILI cases among COVID-19 patients: (1) The updated RUCAM published in 2016 was equally often used as the original RUCAM of 1993, with both identifying DILI and other liver diseases as confounders; (2) RUCAM also worked well in patients treated with up to 18 drugs and provided for most DILI cases a probable or highly probable causality level for drugs; (3) DILI was preferentially caused by antiviral drugs given empirically due to their known therapeutic efficacy in other virus infections; (4) hepatocellular injury was more often reported than cholestatic or mixed injury; (5) maximum LT values were found for alanine aminotransferase (ALT) 1.541 U/L and aspartate aminotransferase (AST) 1.076 U/L; (6) the ALT/AST ratio was variable and ranged from 0.4 to 1.4; (7) the mean or median age of the COVID-19 patients with DILI ranged from 54.3 to 56 years; (8) the ratio of males to females was 1.8–3.4:1; (9) outcome was favorable for most patients, likely due to careful selection of the drugs and quick cessation of drug treatment with emerging DILI, but it was fatal in 19 patients; (10) countries reporting RUCAM-based DILI cases in COVID-19 patients included China, India, Japan, Montenegro, and Spain; (11) robust estimation of the percentage contribution of RUCAM-based DILI for the increased LTs in COVID-19 patients is outside of the current scope. In conclusion, RUCAM-based DILI with its clinical characteristics in COVID-19 patients and its classification as a confounding variable is now well defined, requiring a new correct description of COVID-19 features by removing DILI characteristics as confounders.

Liver-side of inflammatory bowel diseases: Hepatobiliary and drug-induced disorders

Hepatobiliary disorders are among the most common extraintestinal manifestations in inflammatory bowel diseases (IBD), both in Crohn’s disease and ulcerative colitis (UC), and therefore represent a diagnostic challenge. Immune-mediated conditions include primary sclerosing cholangitis (PSC) as the main form, variant forms of PSC (namely small-duct PSC, PSC-autoimmune hepatitis overlap syndrome and IgG4-related sclerosing cholangitis) and granulomatous hepatitis. PSC is by far the most common, presenting in up to 8% of IBD patients, more frequently in UC. Several genetic foci have been identified, but environmental factors are preponderant on disease pathogenesis. The course of the two diseases is typically independent. PSC diagnosis is based mostly on typical radiological findings and exclusion of secondary cholangiopathies. Risk of cholangiocarcinoma is significantly increased in PSC, as well as the risk of colorectal cancer in patients with PSC and IBD-related colitis. No disease-modifying drugs are approved to date. Thus, PSC management is directed against symptoms and complications and includes medical therapies for pruritus, endoscopic treatment of biliary stenosis and liver transplant for end-stage liver disease. Other non-immune-mediated hepatobiliary disorders are gallstone disease, whose incidence is higher in IBD and reported in up to one third of IBD patients, non-alcoholic fatty liver disease, pyogenic liver abscess and portal vein thrombosis. Drug-induced liver injury (DILI) is an important issue in IBD, since most IBD therapies may cause liver toxicity; however, the incidence of serious adverse events is low. Thiopurines and methotrexate are the most associated with DILI, while the risk related to anti-tumor necrosis factor-α and anti-integrins is low. Data on hepatotoxicity of newer drugs approved for IBD, like anti-interleukin 12/23 and tofacitinib, are still scarce, but the evidence from other rheumatic diseases is reassuring. Hepatitis B reactivation during immunosuppressive therapy is a major concern in IBD, and adequate screening and vaccination is warranted. On the other hand, hepatitis C reactivation does not seem to be a real risk, and hepatitis C antiviral treatment does not influence IBD natural history. The approach to an IBD patient with abnormal liver function tests is complex due to the wide range of differential diagnosis, but it is of paramount importance to make a quick and accurate diagnosis, as it may influence the therapeutic management.