Use of a systems model of drug-induced liver injury (DILIsym®) to elucidate the mechanistic differences between acetaminophen and its less-toxic isomer, AMAP, in mice

The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury

Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.

Treatment of chronic hepatitis D with peginterferon lambda-the phase 2 LIMT-1 clinical trial

BACKGROUND AND AIMS

HDV infection leads to the most aggressive form of human viral hepatitis for which there is no FDA-approved therapy. PEG IFN-lambda-1a (Lambda) has previously demonstrated a good tolerability profile in HBV and HCV patients compared to PEG IFN-alfa. The goal of Phase 2 LIMT-1 trial was to evaluate the safety and efficacy of Lambda monotherapy in patients with HDV.

APPROACH AND RESULTS

An open-label study of Lambda 120 or 180 mcg, administered once weekly by subcutaneous injections for 48 weeks, followed by 24 weeks of posttreatment follow-up. Thirty-three patients were allocated to Lambda 180 mcg (n=14) or 120 mcg (n=19). Baseline mean values: HDV RNA 4.1 log10 IU/mL (SD±1.4); ALT 106 IU/L (35-364); and bilirubin 0.5 mg/dL (0.2-1.2). Intention-to-treat rates of virologic response to Lambda 180 mcg and 120 mcg, 24 weeks following treatment cessation were 5 of 14(36%) and 3 of 19 (16%), respectively. The posttreatment response rate of 50% was seen in low BL viral load (≤4 log10) on 180 mcg. Common on-treatment adverse events included flu-like symptoms and elevated transaminase levels. Eight (24%) cases of hyperbilirubinemia with or without liver enzyme elevation, leading to drug discontinuation, were mainly observed in the Pakistani cohort. The clinical course was uneventful, and all responded favorably to dose reduction or discontinuation.

CONCLUSIONS

Treatment with Lambda in patients with chronic HDV may result in virologic response during and following treatment cessation. Clinical phase 3 development of Lambda for this rare and serious disease is ongoing.

Investigating bile acid-mediated cholestatic drug-induced liver injury using a mechanistic model of multidrug resistance protein 3 (MDR3) inhibition

Inhibition of the canalicular phospholipid floppase multidrug resistance protein 3 (MDR3) has been implicated in cholestatic drug-induced liver injury (DILI), which is clinically characterized by disrupted bile flow and damage to the biliary epithelium. Reduction in phospholipid excretion, as a consequence of MDR3 inhibition, decreases the formation of mixed micelles consisting of bile acids and phospholipids in the bile duct, resulting in a surplus of free bile acids that can damage the bile duct epithelial cells, i.e., cholangiocytes. Cholangiocytes may compensate for biliary increases in bile acid monomers via the cholehepatic shunt pathway or bicarbonate secretion, thereby influencing viability or progression to toxicity. To address the unmet need to predict drug-induced bile duct injury in humans, DILIsym, a quantitative systems toxicology model of DILI, was extended by representing key features of the bile duct, cholangiocyte functionality, bile acid and phospholipid disposition, and cholestatic hepatotoxicity. A virtual, healthy representative subject and population (n = 285) were calibrated and validated utilizing a variety of clinical data. Sensitivity analyses were performed for 1) the cholehepatic shunt pathway, 2) biliary bicarbonate concentrations and 3) modes of MDR3 inhibition. Simulations showed that an increase in shunting may decrease the biliary bile acid burden, but raise the hepatocellular concentrations of bile acids. Elevating the biliary concentration of bicarbonate may decrease bile acid shunting, but increase bile flow rate. In contrast to competitive inhibition, simulations demonstrated that non-competitive and mixed inhibition of MDR3 had a profound impact on phospholipid efflux, elevations in the biliary bile acid-to-phospholipid ratio, cholangiocyte toxicity, and adaptation pathways. The model with its extended bile acid homeostasis representation was furthermore able to predict DILI liability for compounds with previously studied interactions with bile acid transport. The cholestatic liver injury submodel in DILIsym accounts for several processes pertinent to bile duct viability and toxicity and hence, is useful for predictions of MDR3 inhibition-mediated cholestatic DILI in humans.

Unraveling the effect of intra- and intercellular processes on acetaminophen-induced liver injury

In high dosages, acetaminophen (APAP) can cause severe liver damage, but susceptibility to liver failure varies across individuals and is influenced by factors such as health status. Because APAP-induced liver injury and recovery is regulated by an intricate system of intra- and extracellular molecular signaling, we here aim to quantify the importance of specific modules in determining the outcome after an APAP insult and of potential targets for therapies that mitigate adversity. For this purpose, we integrated hepatocellular acetaminophen metabolism, DNA damage response induction and cell fate into a multiscale mechanistic liver lobule model which involves various cell types, such as hepatocytes, residential Kupffer cells and macrophages. Our model simulations show that zonal differences in metabolism and detoxification efficiency are essential determinants of necrotic damage. Moreover, the extent of senescence, which is regulated by intracellular processes and triggered by extracellular signaling, influences the potential to recover. In silico therapies at early and late time points after APAP insult indicated that prevention of necrotic damage is most beneficial for recovery, whereas interference with regulation of senescence promotes regeneration in a less pronounced way.

Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction

Idiosyncratic drug-induced liver injury (iDILI) encompasses the unexpected harms that prescription and non-prescription drugs, herbal and dietary supplements can cause to the liver. iDILI remains a major public health problem and a major cause of drug attrition. Given the lack of biomarkers for iDILI prediction, diagnosis and prognosis, searching new models to predict and study mechanisms of iDILI is necessary. One of the major limitations of iDILI preclinical assessment has been the lack of correlation between the markers of hepatotoxicity in animal toxicological studies and clinically significant iDILI. Thus, major advances in the understanding of iDILI susceptibility and pathogenesis have come from the study of well-phenotyped iDILI patients. However, there are many gaps for explaining all the complexity of iDILI susceptibility and mechanisms. Therefore, there is a need to optimize preclinical human in vitro models to reduce the risk of iDILI during drug development. Here, the current experimental models and the future directions in iDILI modelling are thoroughly discussed, focusing on the human cellular models available to study the pathophysiological mechanisms of the disease and the most used in vivo animal iDILI models. We also comment about in silico approaches and the increasing relevance of patient-derived cellular models.

Comprehensive investigation evaluating the carcinogenic hazard potential of acetaminophen

In 2019, the California Office of Environmental Health Hazard Assessment initiated a review of the carcinogenic hazard potential of acetaminophen under Proposition 65. In conjunction with this review, a multidisciplinary team of experts with significant experience in the fields of hazard assessment, acetaminophen mechanism of action, epidemiology, and preclinical and clinical safety performed comprehensive weight of evidence reviews. The reviews evaluate multiple sources of data, including results from preclinical carcinogenicity, genotoxicity, human epidemiology, and mechanistic studies examining biochemical pathways of acetaminophen metabolism. This introductory article summarizes the comprehensive weight of evidence reviews that were performed on the carcinogenicity hazard potential of acetaminophen which are contained in 6 separate companion articles in this issue of Regulatory Toxicology & Pharmacology. Collectively, these results confirm that acetaminophen is not a carcinogenic hazard at any dose level, consistent with previous conclusions of key scientific bodies.

Application of the DILIsym® Quantitative Systems Toxicology drug-induced liver injury model to evaluate the carcinogenic hazard potential of acetaminophen

In 2019, the California Office of Environmental Health Hazard Assessment (OEHHA) initiated a review of the carcinogenic hazard potential of acetaminophen. The objective of the analysis herein was to inform this review by assessing whether variability in patient baseline characteristics (e.g. baseline glutathione (GSH) levels, pharmacokinetics, and capacity of hepatic antioxidants) leads to potential differences in carcinogenic hazard potential at different dosing schemes: maximum labeled doses of 4 g/day, repeated doses above the maximum labeled dose (>4-12 g/day), and acute overdoses of acetaminophen (>15 g). This was achieved by performing simulations of acetaminophen exposure in thousands of diverse virtual patients scenarios using the DILIsym® Quantitative Systems Toxicology (QST) model. Simulations included assessments of the dose and exposure response for toxicity and mode of cell death based on evaluations of the kinetics of changes of: GSH, N-acetyl-p-benzoquinone-imine (NAPQI), protein adducts, mitochondrial dysfunction, and hepatic cell death. Results support that, at therapeutic doses, cellular GSH binds to NAPQI providing sufficient buffering capacity to limit protein adduct formation and subsequent oxidative stress. Simulations evaluating repeated high-level supratherapeutic exposures or acute overdoses indicate that cell death precedes DNA damage that could result in carcinogenicity and thus acetaminophen does not present a carcinogenicity hazard to humans at any dose.

A critical review of the acetaminophen preclinical carcinogenicity and tumor promotion data and their implications for its carcinogenic hazard potential

In 2019 the California Office of Environmental Health Hazard Assessment (OEHHA) initiated a review of the carcinogenic hazard potential of acetaminophen, including an assessment of the long-term rodent carcinogenicity and tumor initiation/promotion studies. The objective of the analysis herein was to inform this review process with a weight-of-evidence assessment of these studies and an assessment of the relevance of these models to humans. In most of the 14 studies, there were no increases in the incidences of tumors in any organ system. In the few studies in which an increase in tumor incidence was observed, there were factors such as absence of a dose response and a rodent-specific tumor supporting that these findings are not relevant to human hazard identification. In addition, we performed qualitative analysis and quantitative simulations of the exposures to acetaminophen and its metabolites and its toxicity profile; the data support that the rodent models are toxicologically relevant to humans. The preclinical carcinogenicity results are consistent with the broader weight of evidence assessment and evaluations of multiple international health authorities supporting that acetaminophen is not a carcinogenic hazard.

The DILI-sim Initiative: Insights into Hepatotoxicity Mechanisms and Biomarker Interpretation

The drug‐induced liver injury (DILI)‐sim Initiative is a public‐private partnership involving scientists from industry, academia, and the US Food and Drug Administration (FDA). The Initiative uses quantitative systems toxicology (QST) to build and refine a model (DILIsym) capable of understanding and predicting liver safety liabilities in new drug candidates and to optimize interpretation of liver safety biomarkers used in clinical studies. Insights gained to date include the observation that most dose‐dependent hepatotoxicity can be accounted for by combinations of just three mechanisms (oxidative stress, interference with mitochondrial respiration, and alterations in bile acid homeostasis) and the importance of noncompetitive inhibition of bile acid transporters. The effort has also provided novel insight into species and interpatient differences in susceptibility, structure‐activity relationships, and the role of nonimmune mechanisms in delayed idiosyncratic hepatotoxicity. The model is increasingly used to evaluate new drug candidates and several clinical trials are underway that will test the model's ability to prospectively predict liver safety. With more refinement, in the future, it may be possible to use the DILIsym predictions to justify reduction in the size of some clinical trials. The mature model could also potentially assist physicians in managing the liver safety of their patients as well as aid in the diagnosis of DILI.

Quantitative Systems Toxicology Approaches to Understand and Predict Drug-Induced Liver Injury

The DILI-sim Initiative is a public-private partnership using quantitative systems toxicology to build a model (DILIsym) capable of understanding and predicting liver safety liabilities in drug candidates. The effort has provided insights into mechanisms underlying dose-dependent drug-induced liver injury (DILI) and interpatient differences in susceptibility to dose-dependent DILI. DILIsym may be useful in identifying drugs capable of causing idiosyncratic hepatotoxicity. DILIsym is used to optimize interpretation of traditional and newer serum biomarkers of DILI. DILIsym results are considered in drug development decisions. In the future, it may be possible to use DILsym predictions to justify reduction in size of some clinical trials.

Latest advances in diagnosing and predicting DILI: what was new in 2017?

Drug-induced liver injury (DILI) remains an increasingly recognized cause of hepatotoxicity and liver failure worldwide. In 2017, we continued to learn about predicting, diagnosing, and prognosticating drug hepatotoxicity. Areas covered: In this review, we selected from over 1200 articles from 2017 to synopsize updates in DILI. There were new HLA haplotypes associated with medications including HLA-C0401 and HLA-B*14. There has been continued work with quantitative systems pharmacology, particularly with the DILIsym® initiative, which employs mathematical representations of DILI mechanisms to predict hepatotoxicity in simulated populations. Additionally, knowledge regarding microRNAs (miRNAs) continues to expand. Some new miRNAs this past year include miRNA-223 and miRNA-605. Aside from miRNAs, other biomarkers for diagnosis, prognosis, and even prediction of DILI were explored. Studies on K18, OPN, and MCSFR have correlated DILI and liver-associated death within 6 months. Conversely, a new prognostic panel using apolipoportein-A1 and haptoglobin has been proposed to predict recovery. Further study of CDH5 has also provided researchers a possible new biomarker for prediction and susceptibility to DILI. Expert commentary: Although research on DILI remains quite promising, there is yet to be a reliable, simple method to predict, diagnose, and risk assess this form of hepatotoxicity.

Quantitative Chemical Proteomic Profiling of the in Vivo Targets of Reactive Drug Metabolites

Idiosyncratic liver toxicity represents an important problem in drug research and pharmacotherapy. Reactive drug metabolites that modify proteins are thought to be a principal factor in drug-induced liver injury. Here, we describe a quantitative chemical proteomic method to identify the targets of reactive drug metabolites in vivo. Treating mice with clickable analogues of four representative hepatotoxic drugs, we demonstrate extensive covalent binding that is confined primarily to the liver. Each drug exhibited a distinct target profile that, in certain cases, showed strong enrichment for specific metabolic pathways (e.g., lipid/sterol pathways for troglitazone). Site-specific proteomics revealed that acetaminophen reacts with high stoichiometry with several conserved, functional (seleno)cysteine residues throughout the liver proteome. Our findings thus provide an advanced experimental framework to characterize the proteomic reactivity of drug metabolites in vivo, revealing target profiles that may help to explain mechanisms and identify risk factors for drug-induced liver injury.

Mechanistic Modelling of Drug-Induced Liver Injury: Investigating the Role of Innate Immune Responses

Drug-induced liver injury (DILI) remains an adverse event of significant concern for drug development and marketed drugs, and the field would benefit from better tools to identify liver liabilities early in development and/or to mitigate potential DILI risk in otherwise promising drugs. DILIsym software takes a quantitative systems toxicology approach to represent DILI in pre-clinical species and in humans for the mechanistic investigation of liver toxicity. In addition to multiple intrinsic mechanisms of hepatocyte toxicity (ie, oxidative stress, bile acid accumulation, mitochondrial dysfunction), DILIsym includes the interaction between hepatocytes and cells of the innate immune response in the amplification of liver injury and in liver regeneration. The representation of innate immune responses, detailed here, consolidates much of the available data on the innate immune response in DILI within a single framework and affords the opportunity to systematically investigate the contribution of the innate response to DILI.

Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury

Sandwich-cultured hepatocytes (SCH) are metabolically competent and have proper localization of basolateral and canalicular transporters with functional bile networks. Therefore, this cellular model is a unique tool that can be used to estimate biliary excretion of compounds. SCH have been used widely to assess hepatobiliary disposition of endogenous and exogenous compounds and metabolites. Mechanistic modeling based on SCH data enables estimation of metabolic and transporter-mediated clearances, which can be used to construct physiologically based pharmacokinetic models for prediction of drug disposition and drug-drug interactions in humans. In addition to pharmacokinetic studies, SCH also have been used to study cytotoxicity and perturbation of biological processes by drugs and hepatically generated metabolites. Human SCH can provide mechanistic insights underlying clinical drug-induced liver injury (DILI). In addition, data generated in SCH can be integrated into systems pharmacology models to predict potential DILI in humans. In this review, applications of SCH in studying hepatobiliary drug disposition and bile acid-mediated DILI are discussed. An example is presented to show how data generated in the SCH model were used to establish a quantitative relationship between intracellular bile acids and cytotoxicity, and how this information was incorporated into a systems pharmacology model for DILI prediction.

A model qualification method for mechanistic physiological QSP models to support model-informed drug development

Mechanistic physiological modeling is a scientific method that combines available data with scientific knowledge and engineering approaches to facilitate better understanding of biological systems, improve decision‐making, reduce risk, and increase efficiency in drug discovery and development. It is a type of quantitative systems pharmacology (QSP) approach that places drug‐specific properties in the context of disease biology. This tutorial provides a broadly applicable model qualification method (MQM) to ensure that mechanistic physiological models are fit for their intended purposes.

Elucidating Differences in the Hepatotoxic Potential of Tolcapone and Entacapone With DILIsym(®), a Mechanistic Model of Drug-Induced Liver Injury

Tolcapone and entacapone are catechol‐O‐methyltransferase (COMT) inhibitors developed as adjunct therapies for treating Parkinson's disease. While both drugs have been shown to cause mitochondrial dysfunction and inhibition of the bile salt export protein (BSEP), liver injury has only been associated with the use of tolcapone. Here we used a multiscale, mechanistic model (DILIsym^®) to simulate the response to tolcapone and entacapone. In a simulated population (SimPops™) receiving recommended doses of tolcapone (200 mg t.i.d.), increases in serum alanine transaminase (ALT) >3× the upper limit of normal (ULN) were observed in 2.2% of the population. In contrast, no simulated patients receiving recommended doses of entacapone (200 mg 8× day) experienced serum ALT >3× ULN. Further, DILIsym^® analyses revealed patient‐specific risk factors that may contribute to tolcapone‐mediated hepatotoxicity. In summary, the simulations demonstrated that differences in mitochondrial uncoupling potency and hepatic exposure primarily account for the difference in hepatotoxic potential for tolcapone and entacapone.

Comparative metabonomic analysis of hepatotoxicity induced by acetaminophen and its less toxic meta-isomer

The leading cause of drug-induced liver injury in the developed world is overdose with N-acetyl-p-aminophenol (APAP). A comparative metabonomic approach was applied to the study of both xenobiotic and endogenous metabolic profiles reflective of in vivo exposure to APAP (300 mg/kg) and its structural isomer N-acetyl-m-aminophenol (AMAP; 300 mg/kg) in C57BL/6J mice, which was anchored with histopathology. Liver and urine samples were collected at 1 h, 3 h and 6 h post-treatment and analyzed by ¹H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography–mass spectrometry (liver only). Histopathology revealed the presence of centrilobular necrosis from 3 h post-APAP treatment, while an AMAP-mediated necrotic endpoint was not observed within the timescale of this study, yet two of five treated mice showed minimal centrilobular eosinophilia. The ¹H-NMR xenobiotic metabolic profile of APAP-treated animals comprised of mercapturate (urine and liver) and glutathionyl (liver) conjugates detected at 1 h post-treatment. This finding corroborated the hepatic endogenous metabolic profile which showed depletion of glutathione from 1 h onwards. In contrast, AMAP glutathionyl conjugates were not detected, nor was AMAP-induced depletion of hepatic glutathione observed. APAP administration induced significant endogenous hepatic metabolic perturbations, primarily linked to oxidative and energetic stress, and perturbation of amino acid metabolism. Early depletion of glutathione was followed by depletion of additional sulfur-containing metabolites, while altered levels of mitochondrial and glycolytic metabolites indicated a disruption of energy homeostasis. In contrast, AMAP administration caused minimal, transient, distinct metabolic perturbations and by 6 h the metabolic profiles of AMAP-treated mice were indistinguishable from those of controls.

A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure

When evaluating compound similarity, addressing multiple sources of information to reach conclusions about common pharmaceutical and/or toxicological mechanisms of action is a crucial strategy. In this chapter, we describe a systems biology approach that incorporates analyses of hepatotoxicant data for 33 compounds from three different sources: a chemical structure similarity analysis based on the 3D Tanimoto coefficient, a chemical structure-based protein target prediction analysis, and a cross-study/cross-platform meta-analysis of in vitro and in vivo human and rat transcriptomics data derived from public resources (i.e., the diXa data warehouse). Hierarchical clustering of the outcome scores of the separate analyses did not result in a satisfactory grouping of compounds considering their known toxic mechanism as described in literature. However, a combined analysis of multiple data types may hypothetically compensate for missing or unreliable information in any of the single data types. We therefore performed an integrated clustering analysis of all three data sets using the R-based tool iClusterPlus. This indeed improved the grouping results. The compound clusters that were formed by means of iClusterPlus represent groups that show similar gene expression while simultaneously integrating a similarity in structure and protein targets, which corresponds much better with the known mechanism of action of these toxicants. Using an integrative systems biology approach may thus overcome the limitations of the separate analyses when grouping liver toxicants sharing a similar mechanism of toxicity.

Systems toxicology: modelling biomarkers of glutathione homeostasis and paracetamol metabolism

One aim of systems toxicology is to deliver mechanistic, mathematically rigorous, models integrating biochemical and pharmacological processes that result in toxicity to enhance the assessment of the risk posed to humans by drugs and other xenobiotics. The benefits of such 'in silico' models would be in enabling the rapid and robust prediction of the effects of compounds over a range of exposures, improving in vitro-in vivo correlations and the translation from preclinical species to humans. Systems toxicology models of organ toxicities that result in high attrition rates during drug discovery and development, or post-marketing withdrawals (e.g., drug-induced liver injury (DILI)) should facilitate the discovery of safe new drugs. Here, systems toxicology as applied to the effects of paracetamol (acetaminophen, N-acetyl-para-aminophenol (APAP)) is used to exemplify the potential of the approach.

A new polymorph of metacetamol

The existence of a new polymorph of metacetamol together with its properties are reported for the first time.