Potential Drug-induced Liver Injury Research Articles

Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanistic in vitro Assays.

Severe drug-induced liver injury (DILI) remains a major safety issue due to its frequency of occurrence, idiosyncratic nature, poor prognosis, and diverse underlying mechanisms. Numerous experimental approaches have been published to improve human DILI prediction with modest success. A retrospective analysis of 125 drugs (70 = most-DILI, 55 = no-DILI) from the Food and Drug Administration Liver Toxicity Knowledge Base was used to investigate DILI prediction based on consideration of human exposure alone or in combination with mechanistic assays of hepatotoxic liabilities (cytotoxicity, bile salt export pump inhibition, or mitochondrial inhibition/uncoupling). Using this dataset, human plasma Cmax,total ≥ 1.1 µM alone distinguished most-DILI from no-DILI compounds with high sensitivity/specificity (80/73%). Accounting for human exposure improved the sensitivity/specificity for each assay and helped to derive predictive safety margins. Compounds with plasma Cmax,total ≥ 1.1 µM and triple liabilities had significantly higher odds ratio for DILI than those with single/dual liabilities. Using this approach, a subset of recent pharmaceuticals with evidence of liver injury during clinical development was recognized as potential hepatotoxicants. In summary, plasma Cmax,total ≥ 1.1 µM along with multiple mechanistic liabilities is a major driver for predictions of human DILI potential. In applying this approach during drug development the challenge will be generating accurate estimates of plasma Cmax,total at efficacious doses in advance of generating true exposure data from clinical studies. In the meantime, drug candidates with multiple hepatotoxic liabilities should be deprioritized, since they have the highest likelihood of causing DILI in case their efficacious plasma Cmax,total in humans is higher than anticipated.

578 Interplay of Gender, Age and Drug Properties in Drug-Induced Liver Injury: Analysis of Adverse Event Reporting at Who Vigibase™

[Background] Clinical hepatotoxicity is highly associated with specific drug properties (e.g., lipophilicity, transport, and metabolism) and daily dose (>100mg). However, how these drug properties interact with age and gender in drug-induced liver injury (DILI) remains unclear. [Aim] To generate hypotheses on drug-patient interactions in DILI, we performed a data-mining analysis using the WHO VigiBaseTM to 1) identify drugs with genderand age-biased reporting frequency (RF) of liver events and 2) explore the association between the groups of identified drugs and drug properties relevant to hepatotoxicity. [Methods] Empirical Bayes Geometric Mean of relative reporting ratio of liver events (EBGM) with 90% confidence interval (CI) was calculated for 375 drugs with established clinical DILI potential (Suzuki, Drug safety 2010; Chen, Drug Discovery Today 2011), partitioning all reported cases into 4 groups by gender and age 50 yrs. Drugs with gender-biased indications were manually excluded from the analysis. Combining Medical Dictionary for Regulatory Activities terms (Hunt, Regul Tox Pharm, 2014), customized liver event terms were created for hepatocellular injury, cholestatic injury, acute liver failure, and overall liver events. Comparing EBGM and 90% CI of overall liver events among the 4 groups, drugs with significant differences in genderand age-specific RF were identified. The groups of identified drugs were then associated with distinct drug properties in the Liver Toxicity Knowledge Base (Chen, Clin Pharm & Ther, 2013). [Results] Overall liver events were 13-20% more frequently reported in women compared tomen. Compared to age-matched men, women<50 yrs exhibited a 40% increased RF of acute liver failure. Across all ages, we identified 43 drugs with an increased RF among women, which were significantly associated with transporter inhibition, mitochondrial liability, and reactive metabolite formation, compared to 186 drugs with no gender difference in RF. Fourteen drugs with an increased RF among men tended to have a higher proportion causing cholestatic injury, while 57 drugs with an increased RF among women only before age 50 yrs were associated with a higher proportion causing hepatocellular injury. Regardless of gender, seventeen drugs with an increased RF in age ≥ 50 yrs were associated with transporter inhibition, lipophilicity, high daily dose (≥100mg), and higher Cmax and plasma protein binding, yet shorter plasma elimination T1/2. [Conclusions] This data-mining analysis identified specific drug properties associated with genderand age-related RF of liver events, suggesting a potential physiologic interplay between these drug properties, gender and age. The discovered associations of gender and age-related DILI and the specific drug properties should be further evaluated for drug-patient interaction in DILI susceptibility.

Establishment of animal models of drug-induced liver injury and analysis of possible mechanisms

Drug-induced liver injury (DILI) is one of leading causes of attrition during both early and late stages of drug development and postmarketing. DILI is generally classified into the intrinsic and idiosyncratic types. Intrinsic DILI is dose dependent and predictable as exemplified by acetaminophen toxicity. However, the occurrence of idiosyncratic DILI with very low incidence and severe liver damage is difficult to predict because of the complex nature of DILI and poor understanding of its mechanism. In this review, we summarize current knowledge and our accumulated experimental findings on the pathogenic mechanisms of DILI focusing on the reactive metabolites of drugs formed by drug-metabolizing enzymes and immune- and inflammation-related responses. Considering drug metabolism and pharmacokinetics, we have established nonclinical animal models of DILI for 10 types of clinical drug known to cause idiosyncratic DILI in humans. Using animal models, it has been shown that the formation of reactive metabolites and both innate and adaptive immunity are involved in the pathogenesis of drug hepatotoxicity. Based on information on biomarkers obtained from animal models, we developed a cell-based system that predicts the potential DILI risks of drugs. The results of these studies increased our understanding of the mechanisms of DILI and help to predict and prevent idiosyncratic DILI caused by drug candidates.

Prediction of Drug-Induced Liver Injury in Micropatterned Co-cultures Containing iPSC-Derived Human Hepatocytes.

Primary human hepatocytes (PHHs) are a limited resource for drug screening, their quality for in vitro use can vary considerably across different lots, and a lack of available donor diversity restricts our understanding of how human genetics affect drug-induced liver injury (DILI). Induced pluripotent stem cell-derived human hepatocyte-like cells (iPSC-HHs) could provide a complementary tool to PHHs for high-throughput drug screening, and ultimately enable personalized medicine. Here, we hypothesized that previously developed iPSC-HH-based micropatterned co-cultures (iMPCCs) with murine embryonic fibroblasts could be amenable to long-term drug toxicity assessment. iMPCCs, created in industry-standard 96-well plates, were treated for 6 days with a set of 47 drugs, and multiple functional endpoints (albumin, urea, ATP) were evaluated in dosed cultures against vehicle-only controls to enable binary toxicity decisions. We found that iMPCCs correctly classified 24 of 37 hepatotoxic drugs (65% sensitivity), while all 10 non-toxic drugs tested were classified as such in iMPCCs (100% specificity). On the other hand, conventional confluent cultures of iPSC-HHs failed to detect several liver toxins that were picked up in iMPCCs. Results for DILI detection in iMPCCs were remarkably similar to published data in PHH-MPCCs (65% versus 70% sensitivity) that were dosed with the same drugs. Furthermore, iMPCCs detected the relative hepatotoxicity of structural drug analogs and recapitulated known mechanisms of acetaminophen toxicity in vitro. In conclusion, iMPCCs could provide a robust tool to screen for DILI potential of large compound libraries in early stages of drug development using an abundant supply of commercially available iPSC-HHs.

CAMDA 2014: Learning from differential expression in the Japanese Toxicogenomic Project

Our aim was to predict drug-induced liver injury potential from differential expression profiles in the Japanese Toxicogenomic Project's data. Additionally, we wondered which drug concentrations and treatment periods proved most informative for classification. The study confirmed that the effect of drugs on differential gene expression is dose and time-dependent suggesting that less information is contained in responses to low doses and short treatment periods. Cross-validation performance of predictions was low due to high false positive rate. Present results indicate that distinguishing between differential expression responses to nontoxic and toxic agents is non-trivial. The value of the Japanese Toxicogenomic Project's data for classification purposes would be increased if gene expression responses to additional nontoxic drugs were available.

PS2-42: Assessment of Drug Induced Liver Injury Using an Automated Causality Assessment Tool

Background/Aims Drugs are a common cause of acute liver failure. However, confirming the diagnosis of drug-induced liver injury (DILI) is challenging due to its low incidence, lack of diagnostic markers and idiosyncratic nature. Our aim was to develop an automated scoring algorithm to identify potential DILI cases based on the Roussel Uclaf Causality Assessment Method (RUCAM) and test it in healthcare data.

Severe cholestasis due to adalimumab in a Crohn’s disease patient

Elevation of liver biochemistry has been reported with anti-tumor necrosis factor agents, but overt liver failure rarely reported. Autoimmune hepatitis has been more commonly reported with infliximab than adalimumab (ADA). Our case, however, describes the first reported case of ADA-associated severe cholestatic injury. A 39-year-old female with Crohn's disease developed severe jaundice after initiation of ADA. All serologic tests and imaging studies were normal. Liver biopsy showed prominent pericentral canalicular cholestasis, without features of steatosis or sclerosing cholangitis, consistent with drug-induced cholestasis. The serum total bilirubin peaked at 280 μmol/L, and improvement was seen after 5 wk with eventual normalization of liver enzymes at 10 wk. Our case describes the first reported case of ADA-associated severe cholestatic liver disease and the first histopathologic examination of this adverse drug effect. Clinicians need to be aware of this potential drug-induced liver injury when prescribing this commonly used biologic medication.

Understanding hepatotoxicity – from patients to mice to computer

Drug Induced Liver Injury (DILI) remains the major adverse drug event that leads to termination of clinical development programs and regulatory actions including failure to approve for marketing, restricted indications, and withdrawal from the marketplace. The type of DILI that is most problematic is “idiosyncratic” meaning that only a very small fraction of treated patients are susceptible to the DILI. Current preclinical models, even “humanized” ones, do not reliably identify molecules that have this liability and, conversely predict liabilities in molecule that are in fact quite safe for the liver. For example, current preclinical testing does not detect the DILI potential of xymelagatran, a drug withdrawn from worldwide markets due to idiosyncratic hepatotoxicity but would predict a high liver risk for acetaminophen (paracetamol) even when taken as directed. Reliable preclinical testing will probably not be developed until there is greater understanding of the mechanisms underlying DILI. Reasoning that the best models to study DILI are the people who have actually experienced it, we are capitalizing on the resources of the US Drug-Induced Liver Injury Network (DILIN-supported by the National Institutes of Health) that is collecting genomic DNA and other biospecimens from patients who have experienced DILI. In addition to genetic studies, we are partnering with Cellular Dynamics International to reprogram induced pleuripotent stem cells from DILIN subjects in whom we have complete exomic DNA sequence with the goal of producing patient-specific liver cultures, and ultimately, humanized mice. We are also partnering with the Shanghai Centers for Disease Control to prospectively collect a variety of biospecimens, including whole blood for transcriptome analysis, from patients treated for active tuberculosis as part of a larger biomarker discovery initiative. We are using panels of inbred mice to mimic patient population genetic diversity and to identify genes and pathways that may underlie DILI susceptibility in patients. Finally, we have established the DILIsim Initiative which is a public-private partnership that is building a computer model to synthesize the rapidly accumulating data with the goal of predicting DILI liability in drug candidates. DILIsim involves 10 pharmaceutical companies and the Food and Drug Administration.

Validation of Multivariate Outlier Detection Analyses Used to Identify Potential Drug-Induced Liver Injury in Clinical Trial Populations

Potential severe liver injury is identified in clinical trials by ALT >3 × upper limits of normal (ULN) and total bilirubin >2 × ULN, and termed 'Hy's Law' by the US FDA. However, there is limited evidence or validation of these thresholds in clinical trial populations. Using liver chemistry data from clinical trials, decision boundaries were built empirically with truncated robust multivariate outlier detection (TRMOD), in a statistically robust manner, and then compared with these fixed thresholds. Additionally, as the analysis of liver chemistry change from baseline has been recently suggested for the identification of liver signals, fold-baseline data was also assessed. The aim of the study was to examine and validate the performance of fixed and empirically derived thresholds for severe liver injury in generally healthy clinical trial populations (i.e. populations without underlying renal, haematological or liver disease). Using phase II-IV clinical trial data, ALT and total bilirubin data were analysed using outlier detection methods to compare with empirically derived and fixed thresholds of the FDA's Hy's Law limits, which were then assessed graphically with the FDA's evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) assessing fold-ULN, as well as a modified eDISH (mDISH) to assess fold-baseline liver chemistries. Data from 28 phase II-IV clinical trials conducted by GlaxoSmithKline were aggregated and analysed by the TRMOD algorithm to create decision boundaries. The data consisted of 18 672 predominantly female subjects with a mean age of 44 years and without known liver disease. Among generally healthy clinical trial subjects, the empirically-derived TRMOD boundaries were approximately equivalent to 'Hy's Law'. TRMOD boundaries for identifying outliers were an ALT limit of 3.4 × ULN and a bilirubin limit of 2.1 × ULN, compared with the FDA's 'Hy's Law' of 3 × ULN and bilirubin 2 × ULN. Inter-laboratory data variations were observed across the 28 studies, and were diminished by use of baseline-corrected data. By applying TRMOD to baseline-corrected data, these boundaries became ALT limit of 3.8 × baseline and bilirubin limit of 4.8 × baseline. Cumulative incidence plots of liver signals identified over time were examined. TRMOD analyses identified normative boundaries and outliers that provide comparative data to detect liver signals in similar trial populations. TRMOD liver chemistry analyses of clinical trial data in generally healthy subjects have confirmed the FDA's Hy's Law threshold as a robust means of detecting liver safety outliers. TRMOD evaluation of liver chemistry data, by both fold-ULN and fold-baseline, provides complementary analyses and valuable normative data for comparison in similar patient populations. No liver signal is present when new clinical trial data from similar patient populations lies within these normative boundaries. Use of baseline-corrected data diminishes inter-laboratory variation and may be more sensitive to possible drug effects. We suggest examining liver chemistries using graphical depictions of both ULN-corrected data (eDISH) and baseline-corrected data (mDISH), as complementary methods.

Validation of Multivariate Outlier Detection Analyses Used to Identify Potential Drug-Induced Liver Injury in Clinical Trial Populations

Validation of Multivariate Outlier Detection Analyses Used to Identify Potential Drug-Induced Liver Injury in Clinical Trial Populations

Characterization of THLE-Cytochrome P450 (P450) Cell Lines: Gene Expression Background and Relationship to P450-Enzyme Activity

The hepatic SV40 large T-antigen immortalized human liver epithelial (THLE) cell line and sublines transfected with cytochromes P450 (P450s) are increasingly being used for evaluation of potential drug-induced liver injury. So far, the available information on transporter and enzyme expression in these transfected cell systems is scattered. The purpose of this study was to characterize THLE cell lines with respect to transporter and enzyme expression. The mRNA expression of 96 typical drug absorption, distribution, metabolism and excretion genes, which encode a selection of transporters, phase I and II drug-metabolizing enzymes, and nuclear hormone receptors, was investigated in five THLE cell lines transfected with individual human P450s and in mock-transfected THLE-null cells using real-time polymerase chain reaction. The majority of the analyzed genes was either absent or expressed at low levels in the THLE-null and THLE-P450 cells, apart from housekeeping genes and the individual transfected P450s. Enzyme activity measurements provided confirmatory functional data for CYP2C9 and CYP3A4. Comparison with gene expression in human liver revealed an overall much lower gene expression in the THLE cell lines. The low levels of expression of a broad range of P450 genes in the THLE cell lines highlight the value of studies undertaken with P450-expressing cell lines for investigation of mechanisms of P450 metabolite-mediated hepatotoxicity. However, when attempting to translate between data obtained in THLE cell lines in vitro and functional consequences in vivo, it is important to take account of their limited expression of genes encoding many other drug-metabolizing enzymes and hepatic transporters.

Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60–70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the “Rule of Three” was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

This Month in Gastroenterology

This Month in Gastroenterology

Drug-Induced Liver Injury

Drug-induced liver injury is a frequent cause of hepatic dysfunction. Reliably establishing whether the liver disease was caused by a drug requires the exclusion of other plausible causes and the search for a clinical drug signature. The drug signature consists of the pattern of liver test abnormality, the duration of latency to symptomatic presentation, the presence or absence of immune-mediated hypersensitivity and the response to drug withdrawal. Determination of causality also includes an evaluation of individual susceptibility to drug-induced liver injury. This susceptibility is governed by both genetic and environmental factors. Components of the drug signature in conjunction with certain risk factors have been incorporated into formal scoring systems that are predictive of the likelihood of drug-induced liver injury. The most validated scoring system is the Roussel-Uclaf causality assessment method, which nonetheless retains certain imperfections. Mitigating the potential for drug-induced liver injury is achieved by the identification of toxicity signals during clinical trials and the monitoring of liver tests in clinical practice. There are three signals of liver toxicity in clinical trials: (i) a statistically significant doubling (or more) in the incidence of serum alanine aminotransferase (ALT) elevation >3 x the upper limit of normal (ULN); (ii) any incidence of serum ALT elevation >8-10 x ULN; and (iii) any incidence of serum ALT elevation >3 x ULN accompanied by a serum bilirubin elevation >2 x ULN. Monitoring of liver tests in clinical practice has shown unconvincing efficacy, but where a benefit-risk analysis would favour continued therapy, monthly monitoring may have some benefit compared with no monitoring at all. With rare exception, treatment of drug-induced liver injury is principally supportive. Drug toxicity is the most common cause of acute liver failure, defined as a prolonged prothrombin time (international normalised ratio > or =1.5) and any degree of mental alteration occurring <26 weeks after the onset of illness in a patient without pre-existing cirrhosis. A patient who meets these criteria must be evaluated for liver transplantation. The pathogenesis of drug-induced liver injury can be examined on the basis of the two principal patterns of injury. The hepatocellular pattern is characterised by a predominant rise in the level of transaminases and results from the demise of hepatocytes by means of either apoptosis or necrosis. The cholestatic pattern is characterised by a predominant rise of the serum alkaline phosphatase level and usually results from injury to the bile ductular cells either directly by the drug or its metabolite, or indirectly by an adaptive immune response.

Antibiotic therapy: a major cause of drug-induced jaundice in southwest England

To determine the incidence and causes of drug-induced jaundice in a rural community. A retrospective analysis of 800 patients presenting to a single-centre jaundice referral system serving a community of 400 000 over a period of 66 months (1998-2004). Standard criteria for drug-induced liver injury were applied to patients with a putative diagnosis of drug-induced jaundice. The incidence rates per prescription of drug-induced jaundice caused by co-amoxiclav and flucloxacillin were derived from local and national annual prescription rates. The incidence of drug-induced jaundice was 1.27 (confidence limits 0.85-1.8) per 100 000 per annum in a total of 28 patients (17 men, mean age 69 years). Antibiotics were the commonest cause of jaundice (n=21). Of these, co-amoxiclav (n=9) and flucloxacillin (n=7) caused the majority with an incidence rate per 100 000 prescriptions of 9.91 (4.6-18.0) and 3.60 (1.5-7.2), respectively. Co-amoxiclav-induced jaundice was observed more commonly in elderly males (age 65 years, M : F 7 : 2). In those patients with flucloxacillin or co-amoxiclav-induced jaundice, bilirubin ranged from 54 to 599 mumol/l (267 mumol/l) with a resolution of jaundice between 30 and 90 days. Counselling with regard to potential drug-induced liver injury and reporting of the adverse reaction had been performed in 1/28 patients. 8.1% patients with no biliary obstruction and jaundice had a drug-induced and predominantly antibiotic-related aetiology particularly affecting an elderly population. We recommend that all patients receiving co-amoxiclav and flucloxacillin should be counselled before the therapy regarding the potential risk of jaundice and that an alternative antibiotic to co-amoxiclav is used if possible in men over the age of 60 years.