Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important Substructures

Predicting whether a compound can cause drug-induced liver injury (DILI) is difficult due to the complexity of drug mechanism. The cysteine trapping assay is a method for detecting reactive metabolites that bind to microsomes covalently. However, it is cumbersome to use 35S isotope-labeled cysteine for this assay. Therefore, we constructed an in silico classification model for predicting a positive/negative outcome in the cysteine trapping assay. We collected 475 compounds (436 in-house compounds and 39 publicly available drugs) based on experimental data performed in this study, and the composition of the results showed 248 positives and 227 negatives. Using a Message Passing Neural Network (MPNN) and Random Forest (RF) with extended connectivity fingerprint (ECFP) 4, we built machine learning models to predict the covalent binding risk of compounds. In the time-split dataset, AUC-ROC of MPNN and RF were 0.625 and 0.559 in the hold-out test, restrictively. This result suggests that the MPNN model has a higher predictivity than RF in the time-split dataset. Hence, we conclude that the in silico MPNN classification model for the cysteine trapping assay has a better predictive power. Furthermore, most of the substructures that contributed positively to the cysteine trapping assay were consistent with previous results.

Assessing Liver Effects of Cannabidiol and Valproate Alone and in Combination Using Quantitative Systems Toxicology

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox-Gastaut syndrome, and tuberous sclerosis complex, elevations in serum alanine aminotransferase (ALT) > 3× the upper limit of normal were observed in some patents, but the incidence was much greater in patients who were receiving treatment with valproate (VPA) before starting CBD. To explore potential mechanisms underlying this interaction, we used DILIsym, a quantitative systems toxicology model, to predict ALT elevations in a simulated human population treated with CBD alone, VPA alone, and when CBD dosing was starting during treatment with VPA. We gathered in vitro data assessing the potential for CBD, the two major CBD metabolites, and VPA to cause hepatotoxicity via inhibition of bile acid transporters, mitochondrial dysfunction, and production of reactive oxygen species (ROS). Physiologically-based pharmacokinetic models for CBD and VPA were used to predict liver exposure. DILIsym simulations predicted dose-dependent ALT elevations from CBD treatment and this was predominantly driven by ROS production from the parent molecule. DILIsym also predicted VPA treatment to cause ALT elevations which were transient when mitochondrial biogenesis was incorporated into the model. Contrary to the clinical experience, simulation of 2 weeks treatment with VPA prior to introduction of CBD treatment did not predict an increase of the incidence of ALT elevations relative to CBD treatment alone. We conclude that the marked increased incidence of CBD-associated ALT elevations in patients already receiving VPA is unlikely to involve the three major mechanisms of direct hepatotoxicity.

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.

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.

Applications of In Silico Models to Predict Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a major cause of the withdrawal of pre-marketed drugs, typically attributed to oxidative stress, mitochondrial damage, disrupted bile acid homeostasis, and innate immune-related inflammation. DILI can be divided into intrinsic and idiosyncratic DILI with cholestatic liver injury as an important manifestation. The diagnosis of DILI remains a challenge today and relies on clinical judgment and knowledge of the insulting agent. Early prediction of hepatotoxicity is an important but still unfulfilled component of drug development. In response, in silico modeling has shown good potential to fill the missing puzzle. Computer algorithms, with machine learning and artificial intelligence as a representative, can be established to initiate a reaction on the given condition to predict DILI. DILIsym is a mechanistic approach that integrates physiologically based pharmacokinetic modeling with the mechanisms of hepatoxicity and has gained increasing popularity for DILI prediction. This article reviews existing in silico approaches utilized to predict DILI risks in clinical medication and provides an overview of the underlying principles and related practical applications.

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.

Applications of Quantitative Systems Pharmacology (QSP) in Drug Development for NAFLD and NASH and Its Regulatory Application

Nonalcoholic steatohepatitis (NASH) is a widely prevalent disease, but approved pharmaceutical treatments are not available. As such, there is great activity within the pharmaceutical industry to accelerate drug development in this area and improve the quality of life and reduce mortality for NASH patients. The use of quantitative systems pharmacology (QSP) can help make this overall process more efficient. This mechanism-based mathematical modeling approach describes both the pathophysiology of a disease and how pharmacological interventions can modify pathophysiologic mechanisms. Multiple capabilities are provided by QSP modeling, including the use of model predictions to optimize clinical studies. The use of this approach has grown over the last 20 years, motivating discussions between modelers and regulators to agree upon methodologic standards. These include model transparency, documentation, and inclusion of clinical pharmacodynamic biomarkers. Several QSP models have been developed that describe NASH pathophysiology to varying extents. One specific application of NAFLDsym, a QSP model of NASH, is described in this manuscript. Simulations were performed to help understand if patient behaviors could help explain the relatively high rate of fibrosis stage reductions in placebo cohorts. Simulated food intake and body weight fluctuated periodically over time. The relatively slow turnover of liver collagen allowed persistent reductions in predicted fibrosis stage despite return to baseline for liver fat, plasma ALT, and the NAFLD activity score. Mechanistic insights such as this that have been derived from QSP models can help expedite the development of safe and effective treatments for NASH patients.

Virtual Populations for Quantitative Systems Pharmacology Models

Quantitative systems pharmacology (QSP) places an emphasis on dynamic systems modeling, incorporating considerations from systems biology modeling and pharmacodynamics. The goal of QSP is often to quantitatively predict the effects of clinical therapeutics, their combinations, and their doses on clinical biomarkers and endpoints. In order to achieve this goal, strategies for incorporating clinical data into model calibration are critical. Virtual population (VPop) approaches facilitate model calibration while faced with challenges encountered in QSP model application, including modeling a breadth of clinical therapies, biomarkers, endpoints, utilizing data of varying structure and source, capturing observed clinical variability, and simulating with models that may require more substantial computational time and resources than often found in pharmacometrics applications. VPops are frequently developed in a process that may involve parameterization of isolated pathway models, integration into a larger QSP model, incorporation of clinical data, calibration, and quantitative validation that the model with the accompanying, calibrated VPop is suitable to address the intended question or help with the intended decision. Here, we introduce previous strategies for developing VPops in the context of a variety of therapeutic and safety areas: metabolic disorders, drug-induced liver injury, autoimmune diseases, and cancer. We introduce methodological considerations, prior work for sensitivity analysis and VPop algorithm design, and potential areas for future advancement. Finally, we give a more detailed application example of a VPop calibration algorithm that illustrates recent progress and many of the methodological considerations. In conclusion, although methodologies have varied, VPop strategies have been successfully applied to give valid clinical insights and predictions with the assistance of carefully defined and designed calibration and validation strategies. While a uniform VPop approach for all potential QSP applications may be challenging given the heterogeneity in use considerations, we anticipate continued innovation will help to drive VPop application for more challenging cases of greater scale while developing new rigorous methodologies and metrics.

Quantitative Systems Toxicology and Drug Development: The DILIsym Experience

DILIsym^® is a Quantitative Systems Toxicology (QST) model that has been developed over the last decade by a public-private partnership to predict the liver safety liability in new drug candidates. DILIsym integrates the quantitative abilities of parent and relevant metabolites to cause oxidative stress, mitochondrial dysfunction, and alter bile acid homeostasis. Like the prediction of drug-drug interactions, the data entered into DILIsym are assessed in the laboratory in human experimental systems, and combined with estimates of liver exposure to predict the outcome. DILIsym is now frequently used in decision-making within the pharmaceutical industry and its modeling results are increasingly included in regulatory communications and NDA submissions. DILIsym can be used to identify dominant mechanisms underlying liver toxicity and this information is increasingly being used to identify patient-specific risk factors, including certain disease states. DILIsym is also increasingly used to optimize the interpretation of liver injury biomarkers. DILIsym provides an example of how QST modeling can help speed the delivery of safer new drugs to the patients who need them.

Evaluation of the hepatoprotective effect of curcumin-loaded solid lipid nanoparticles against paracetamol overdose toxicity: Role of inducible nitric oxide synthase

Curcumin (Cur) is a natural compound that exhibited therapeutic effects against various liver injuries however Cur showed poor water solubility and bioavailability. This study aimed to design Cur-loaded solid lipid nanoparticles (SLNs) and to evaluate the hepatoprotective and antioxidant effects in a model of acute hepatotoxicity induced by paracetamol (PCM) overdose compared to the raw Cur and N-acetylcysteine (NAC). SLNs were prepared by emulsion/solvent evaporation method and 3² factorial design was employed. Wistar rats were divided into Control, PCM, PCM + NAC, PCM + raw Cur, and PCM + Cur-SLNs groups and treated orally for 14 days before receiving a single PCM dose. The Cur-loaded SLNs showed high entrapment efficiency % ranging between 69.1 and 92.1%, particle size (PS) between 217 and 506 nm, and zeta potential values between -17.9 and -25.5 mV. The in vivo results revealed that the PCM group exhibited deterioration of liver functions, pathological lesions on the liver tissues, severe oxidative stress, and increases in both the serum and hepatic iNOS levels. Remarkably, the PCM + Cur-SLNs group showed significantly better liver functions and tissue integrity compared to the PCM group. Furthermore, higher reduced glutathione and catalase but lower malondialdehyde and iNOS levels were observed. In conclusion, Cur-loaded SLNs effectively prevented the liver damage induced by PCM overdose through alleviating the oxidative stress and inhibiting the serum and hepatic iNOS expression in an effect comparable to NAC and better than raw Cur.

Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure

Quantitative systems pharmacology (QSP) is an important approach in pharmaceutical research and development that facilitates in silico generation of quantitative mechanistic hypotheses and enables in silico trials. As demonstrated by applications from numerous industry groups and interest from regulatory authorities, QSP is becoming an increasingly critical component in clinical drug development. With rapidly evolving computational tools and methods, QSP modeling has achieved important progress in pharmaceutical research and development, including for heart failure (HF). However, various challenges exist in the QSP modeling and clinical characterization of HF. Machine/deep learning (ML/DL) methods have had success in a wide variety of fields and disciplines. They provide data-driven approaches in HF diagnosis and modeling, and offer a novel strategy to inform QSP model development and calibration. The combination of ML/DL and QSP modeling becomes an emergent direction in the understanding of HF and clinical development new therapies. In this work, we review the current status and achievement in QSP and ML/DL for HF, and discuss remaining challenges and future perspectives in the field.

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.

Mixed steatohepatitis: more questions than answers (part 2)

In this review, we discussed the epidemiological and pathogenetic aspects of mixed steatohepatitis (SH), developed due to non-alcoholic fatty liver disease, metabolic associated fatty liver disease, drug-induced liver injury. We discussed the mechanisms of the mutually aggravating influence of etiological factors. Drugs can cause steatosis and SH, as well as contribute to the progressive course of existing SH, primarily of metabolic origin. The issues of interaction of pathogenetic factors, peculiarities of diagnostics and perspectives of pathogenetic and symptomatic treatment are considered. Therapy of mixed SH is based on avoidance of hepatotoxic drugs and lifestyle modification, medications with demonstrated efficacy (such as ademetionine) in certain SH might be used.

Orostachys japonicus ameliorates acetaminophen-induced acute liver injury in mice

ETHNOPHARMACOLOGICAL RELEVANCE

Orostachys japonicus A. Berger (O. japonicus), referred to as Wa-song in Korea is a traditional and herbal medicine. Even though it has been traditionally used to treat inflammation- and toxicity-related diseases, the effects of ethanol extract of O. japonicus (OJE) on acetaminophen (N-acetyl-p-aminophenol, APAP) overdose-induced hepatotoxicity have not been determined yet.

AIM OF THE STUDY

The present study was aimed to investigate the effects of OJE against APAP-induced acute liver injury (ALI) and explore the underlying mechanisms.

MATERIALS AND METHODS

Mice were treated orally with OJE (50, 100, or 200 mg/kg) for seven days before APAP (300 mg/kg) injection. After 12 h of APAP treatment, serum and liver tissues were collected. An in vitro system using primary hepatocytes was also applied in this study.

RESULTS

Pretreatment with OJE, especially at a dose of 200 mg/kg, reduced APAP overdose-induced ALI in mice, as evidenced by decreased serum alanine/aspartate aminotransferase levels, histopathological damage, and inflammation. Consistently, OJE pretreatment reduced the gene transcription of cytochrome P450 (CYP) 3A11 and CYP1A2 in livers of mice injected with or without APAP, at least in part, via inactivation of nuclear receptor pregnane X receptor (PXR). Furthermore, the role of PXR in mediating the OJE regulation of CYPs was confirmed in primary hepatocytes, which showed that OJE pretreatment inhibited PXR activity and APAP hepatotoxicity enhanced by pregnenolone 16α-carbonitrile, a mouse agonist of PXR. Besides, the antioxidative activity provided by OJE, involving increases in hepatic glutathione (GSH) content and decreases in malondialdehyde levels, has been shown to exert hepatoprotective effects in normal and injured livers. Moreover, APAP-activated c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) in mice liver were indirectly inhibited by pretreatment with OJE.

CONCLUSIONS

Taken together, our findings showed that OJE attenuated APAP-induced ALI by decreasing APAP-metabolizing enzymes via inactivation of PXR and the restoration of hepatic GSH content. Therefore, OJE could be a promising hepatoprotective agent.

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.

Assessing Effects of BHV-0223 40 mg Zydis Sublingual Formulation and Riluzole 50 mg Oral Tablet on Liver Function Test Parameters Utilizing DILIsym

For patients with amyotrophic lateral sclerosis who take oral riluzole tablets, approximately 50% experience alanine transaminase (ALT) levels above upper limit of normal (ULN), 8% above 3× ULN, and 2% above 5× ULN. BHV-0223 is a novel 40 mg rapidly sublingually disintegrating (Zydis) formulation of riluzole, bioequivalent to conventional riluzole 50 mg oral tablets, that averts the need for swallowing tablets and mitigates first-pass hepatic metabolism, thereby potentially reducing risk of liver toxicity. DILIsym is a validated multiscale computational model that supports evaluation of liver toxicity risks. DILIsym was used to compare the hepatotoxicity potential of oral riluzole tablets (50 mg BID) versus BHV-0223 (40 mg BID) by integrating clinical data and in vitro toxicity data. In a simulated population (SimPops), ALT levels > 3× ULN were predicted in 3.9% (11/285) versus 1.4% (4/285) of individuals with oral riluzole tablets and sublingual BHV-0223, respectively. This represents a relative risk reduction of 64% associated with BHV-0223 versus conventional riluzole tablets. Mechanistic investigations revealed that oxidative stress was responsible for the predicted ALT elevations. The validity of the DILIsym representation of riluzole and assumptions is supported by its ability to predict rates of ALT elevations for riluzole oral tablets comparable with that observed in clinical data. Combining a mechanistic, quantitative representation of hepatotoxicity with interindividual variability in both susceptibility and liver exposure suggests that sublingual BHV-0223 confers diminished rates of liver toxicity compared with oral tablets of riluzole, consistent with having a lower overall dose of riluzole and bypassing first-pass liver metabolism.

Herbal Therapy for the Treatment of Acetaminophen-Associated Liver Injury: Recent Advances and Future Perspectives

Acetaminophen (APAP) overdose is the leading cause of drug-induced liver injury worldwide, and mitochondrial oxidative stress is considered the major event responsible for APAP-associated liver injury (ALI). Despite the identification of N-acetyl cysteine, a reactive oxygen species scavenger that is regarded as an effective clinical treatment, therapeutic effectiveness remains limited due to rapid disease progression and diagnosis at a late phase, which leads to the need to explore various therapeutic approaches. Since the early 1990s, a number of natural products and herbs have been found to have hepatoprotective effects against APAP-induced hepatotoxicity in terms of acute liver failure prevention and therapeutic amelioration of ALI. In this review, we summarize the hepatoprotective effects and mechanisms of medicinal plants, including herbs and fruit extracts, along with future perspectives that may provide guidance to improve the current status of herbal therapy against ALI.

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.

Quantitative Systems Toxicology Analysis of In Vitro Mechanistic Assays Reveals Importance of Bile Acid Accumulation and Mitochondrial Dysfunction in TAK-875-Induced Liver Injury

TAK-875 (fasiglifam), a GPR40 agonist in development for the treatment of type 2 diabetes (T2D), was voluntarily terminated in Phase III trials due to adverse liver effects. The potential mechanisms of TAK-875 toxicity were explored by combining in vitro experiments with quantitative systems toxicology (QST) using DILIsym, a mathematical representation of drug-induced liver injury. In vitro assays revealed that bile acid transporters were inhibited by both TAK-875 and its metabolite, TAK-875-Glu. Experimental data indicated that human bile salt export pump (BSEP) inhibition by TAK-875 was mixed whereas sodium taurocholate co-transporting polypeptide (NTCP) inhibition by TAK-875 was competitive. Furthermore, experimental data demonstrated that both TAK-875 and TAK-875-Glu inhibit mitochondrial electron transport chain (ETC) enzymes. These mechanistic data were combined with a physiologically based pharmacokinetic (PBPK) model constructed within DILIsym to estimate liver exposure of TAK-875 and TAK-875-Glu. In a simulated population (SimPops) constructed to reflect T2D patients, 16/245 (6.5%) simulated individuals developed alanine aminotransferase (ALT) elevations, an incidence similar to that observed with 200 mg daily dosing in clinical trials. Determining the mode of bile acid transporter inhibition (K_i) was critical to accurate predictions. In addition, simulations conducted on a sensitive subset of individuals (SimCohorts) revealed that when either BSEP or ETC inhibition was inactive, ALT elevations were not predicted to occur, suggesting that the two mechanisms operate synergistically to produce the observed clinical response. These results demonstrate how utilizing QST methods to interpret in vitro experimental results can lead to an improved understanding of the clinically relevant mechanisms underlying drug-induced toxicity.

Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity

Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF-04895162 (ICA-105665). PF-04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC50 for bile salt export pump (BSEP) inhibition by PF-04895162 was higher (311 µmol/L) than that has been generally thought to contribute to hepatotoxicity. Modeling even higher PF-04895162 liver exposures than were measured in the rat safety studies aggravated mitochondrial toxicity but did not result in rat hepatotoxicity due to insufficient accumulation of cytotoxic bile acid species. This investigative study highlights the potential for combined in vitro and computational screening methods to identify latent hepatotoxic risks and paves the way for similar and prospective studies.

Using Quantitative Systems Toxicology to Investigate Observed Species Differences in CKA-Mediated Hepatotoxicity

CKA, a chemokine receptor antagonist intended for treating inflammatory conditions, produced dose-dependent hepatotoxicity in rats but advanced into the clinic where single doses of CKA up to 600 mg appeared safe in humans. Because existing toxicological platforms used during drug development are not perfectly predictive, a quantitative systems toxicology model investigated the hepatotoxic potential of CKA in humans and rats through in vitro assessments of CKA on mitochondrial respiration, oxidative stress, and bile acid transporters. DILIsym predicted that single doses of CKA caused serum ALT >3xULN in a subset of the simulated rat population, while single doses in a simulated human population did not produce serum ALT elevations. Species differences were largely attributed to differences in liver exposure, but increased sensitivity to inhibition of mitochondrial respiration in the rat also contributed. We conclude that mechanistic modeling can elucidate species differences in the hepatotoxic potential of drug candidates.

Serum metabolome and targeted bile acid profiling reveals potential novel biomarkers for drug-induced liver injury

This study aims to determine the non-invasive, reliable and sensitive biochemical parameters for the diagnosis of drug-induced liver injury (DILI).Ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) and selected reaction monitoring (SRM) were used to profile the serum metabolome and quantify 15 targeted bile acid metabolites, respectively, in samples obtained from 38 DILI patients and 30 healthy controls.A comparison of the resulting serum metabolome profiles of the study participants revealed significant differences between DILI patients and healthy controls. Specifically, serum palmitic acid, taurochenodeoxycholic acid, glycocholic acid (GCA), and tauroursodeoxycholic acid (TUDCA) levels were significantly higher, and serum lysophosphatidylethanolamine levels were significantly lower in DILI patients vs healthy controls (P < .001). Furthermore, the SRM assay of bile acids revealed that the increase in GCA, taurocholic acid (TCA), TUDCA, glycochenodeoxycholic acid (GCDCA), glycochenodeoxycholic sulfate (GCDCS), and taurodeoxycholic acid (TDCA) corresponded to a higher degree of liver damage. These results also indicate that serum concentrations of chenodeoxycholic acid (CDCA), deoxycholic acid (DCA) and lithocholic acid (LCA) were significantly lower in patients with severe DILI, when compared to healthy controls, and that this decrease was closely correlated to the severity of liver damage.Taken together, these results demonstrate that bile acids could serve as potential biomarkers for the early diagnosis and severity of DILI.

Drug-Induced Liver Injuries (Clinical Guidelines for Physicians)

Aim.Clinical guidelines for the management of adult patients suffering from drug-induced liver injuries (DILI) are intended for all medical specialists, who treat such patients in their clinical practice.

Key findings.The presented recommendations contain information about the epidemiological data, terminology, diagnostic principles, classification, prognosis and management of patients with DILI. The recommendations list pharmacological agents that most commonly cause DILI, including its fatal cases. Dose-dependent and predictable (hepatotoxic), as well as dose-independent and unpredictable (idiosyncratic) DILI forms are described in detail, which information has a particular practical significance. The criteria and types of DILI are described in detail, with the most reliable diagnostic and prognostic scales and indices being provided. The pathogenesis and risk factors for the development of DILI are considered. The clinical and morphological forms (phenotypes) of DILI are described. The diseases that are included into the differential diagnosis of DILI, as well as the principles of its implementation, are given. The role and significance of various diagnostic methods for examining a patient with suspected DILI is described, with the liver biopsy role being discussed. Clinical situations, in which DILI can acquire a chronic course, are described. A section on the assessment of causal relationships in the diagnosis of DILI is presented; the practical value of using the CIOMS-RUCAM scale is shown. All possible therapeutic measures and pharmacological approaches to the treatment of patients with various DILI phenotypes are investigated in detail. A particular attention is paid to the use of glucocorticosteroids in the treatment of DILI.

Conclusion.The presented clinical recommendations are important for improving the quality of medical care in the field of hepatology.

Analyzing the Mechanisms Behind Macrolide Antibiotic-Induced Liver Injury Using Quantitative Systems Toxicology Modeling

PURPOSE

Macrolide antibiotics are commonly prescribed treatments for drug-resistant bacterial infections; however, many macrolides have been shown to cause liver enzyme elevations and one macrolide, telithromycin, has been pulled from the market by its provider due to liver toxicity. This work seeks to assess the mechanisms responsible for the toxicity of macrolide antibiotics.

METHODS

Five macrolides were assessed in in vitro systems designed to test for bile acid transporter inhibition, mitochondrial dysfunction, and oxidative stress. The macrolides were then represented in DILIsym, a quantitative systems pharmacology (QST) model of drug-induced liver injury, placing the in vitro results in context with each compound's predicted liver exposure and known biochemistry.

RESULTS

DILIsym results suggest that solithromycin and clarithromycin toxicity is primarily due to inhibition of the mitochondrial electron transport chain (ETC) while erythromycin toxicity is primarily due to bile acid transporter inhibition. Telithromycin and azithromycin toxicity was not predicted by DILIsym and may be caused by mechanisms not currently incorporated into DILIsym or by unknown metabolite effects.

CONCLUSIONS

The mechanisms responsible for toxicity can be significantly different within a class of drugs, despite the structural similarity among the drugs. QST modeling can provide valuable insight into the nature of these mechanistic differences.

N-acetylcysteine for adults with acute respiratory distress syndrome: A meta-analysis of randomized controlled trials

Background:

Acute respiratory distress syndrome is regarded as a formidable clinical challenge due to its high prevalence and mortality. The treatment of acute respiratory distress syndrome is very complex and difficult. As an adjuvant therapy, the antioxidant N-acetylcysteine has been investigated for several years but the benefit is controversial.

Objectives:

We performed the systematic review and meta-analysis of randomized controlled trials to evaluate the efficacy of N-acetylcysteine on patients with acute respiratory distress syndrome.

Methods:

We searched PubMed, CENTRAL, and CBM databases. Randomized controlled trials comparing the effects of N-acetylcysteine and control were included. Overall mortality was the primary outcome; length of intensive care unit stay, duration of mechanical ventilation, glutathione levels, and PaO2/FiO2 were the secondary outcomes.

Results:

Eight trials with a total of 289 patients were included. Compared to the control group, the N-acetylcysteine group did not lower the overall mortality (risk ratio: 0.83; 95% confidence interval: 0.62 to 1.11; P = 0.21; I2 = 0%). However, N-acetylcysteine significantly shortened intensive care unit stay in the random-effects model (mean difference: –4.47 days; 95% confidence interval: –8.79 to −0.14; P = 0.04; I2 = 46%). Due to substantial heterogeneity and limited number of studies, the data of duration of mechanical ventilation, glutathione levels, and PaO2/FiO2 could not be pooled in the meta-analysis.

Conclusion:

N-acetylcysteine is ineffective in reducing mortality but beneficial for intensive care unit stay. Nonetheless, the effectiveness of N-acetylcysteine for acute respiratory distress syndrome is limited and further research is required before strong recommendations can be made.

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling

Elevations of liver enzymes have been observed in clinical trials with BAL30072, a novel antibiotic. In vitro assays have identified potential mechanisms for the observed hepatotoxicity, including electron transport chain (ETC) inhibition and reactive oxygen species (ROS) generation. DILIsym, a quantitative systems pharmacology (QSP) model of drug-induced liver injury, has been used to predict the likelihood that each mechanism explains the observed toxicity. DILIsym was also used to predict the safety margin for a novel BAL30072 dosing scheme; it was predicted to be low. DILIsym was then used to recommend potential modifications to this dosing scheme; weight-adjusted dosing and a requirement to assay plasma alanine aminotransferase (ALT) daily and stop dosing as soon as ALT increases were observed improved the predicted safety margin of BAL30072 and decreased the predicted likelihood of severe injury. This research demonstrates a potential application for QSP modeling in improving the safety profile of candidate drugs.

Systems pharmacology modeling of drug-induced hyperbilirubinemia: Differentiating hepatotoxicity and inhibition of enzymes/transporters

Elevations in serum bilirubin during drug treatment may indicate global liver dysfunction and a high risk of liver failure. However, drugs also can increase serum bilirubin in the absence of hepatic injury by inhibiting specific enzymes/transporters. We constructed a mechanistic model of bilirubin disposition based on known functional polymorphisms in bilirubin metabolism/transport. Using physiologically based pharmacokinetic (PBPK) model-predicted drug exposure and enzyme/transporter inhibition constants determined in vitro, our model correctly predicted indinavir-mediated hyperbilirubinemia in humans and rats. Nelfinavir was predicted not to cause hyperbilirubinemia, consistent with clinical observations. We next examined a new drug candidate that caused both elevations in serum bilirubin and biochemical evidence of liver injury in rats. Simulations suggest that bilirubin elevation primarily resulted from inhibition of transporters rather than global liver dysfunction. We conclude that mechanistic modeling of bilirubin can help elucidate underlying mechanisms of drug-induced hyperbilirubinemia, and thereby distinguish benign from clinically important elevations in serum bilirubin.

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.

Application of a Mechanistic Model to Evaluate Putative Mechanisms of Tolvaptan Drug-Induced Liver Injury and Identify Patient Susceptibility Factors

Tolvaptan is a selective vasopressin V2 receptor antagonist, approved in several countries for the treatment of hyponatremia and autosomal dominant polycystic kidney disease (ADPKD). No liver injury has been observed with tolvaptan treatment in healthy subjects and in non-ADPKD indications, but ADPKD clinical trials showed evidence of drug-induced liver injury (DILI). Although all DILI events resolved, additional monitoring in tolvaptan-treated ADPKD patients is required. In vitro assays identified alterations in bile acid disposition and inhibition of mitochondrial respiration as potential mechanisms underlying tolvaptan hepatotoxicity. This report details the application of DILIsym software to determine whether these mechanisms could account for the liver safety profile of tolvaptan observed in ADPKD clinical trials. DILIsym simulations included physiologically based pharmacokinetic estimates of hepatic exposure for tolvaptan and2 metabolites, and their effects on hepatocyte bile acid transporters and mitochondrial respiration. The frequency of predicted alanine aminotransferase (ALT) elevations, following simulated 90/30  mg split daily dosing, was 7.9% compared with clinical observations of 4.4% in ADPKD trials. Toxicity was multifactorial as inhibition of bile acid transporters and mitochondrial respiration contributed to the simulated DILI. Furthermore, simulation analysis identified both pre-treatment risk factors and on-treatment biomarkers predictive of simulated DILI. The simulations demonstrated that in vivo hepatic exposure to tolvaptan and the DM-4103 metabolite, combined with these 2 mechanisms of toxicity, were sufficient to account for the initiation of tolvaptan-mediated DILI. Identification of putative risk-factors and potential novel biomarkers provided insight for the development of mechanism-based tolvaptan risk-mitigation strategies.

Antioxidant and hepatoprotective activity of vitex honey against paracetamol induced liver damage in mice

Fourteen vitex honeys from China were investigated to evaluate its antioxidant and hepatoprotective activity against paracetamol-induced liver damage. All honey samples exhibited high total phenolic content (344-520 mg GAE per kg), total flavonoid content (19-31 mg Rutin per kg), and strong antioxidant activity in DPPH radical scavenging, ferric reducing antioxidant power and Ferrous ion-chelating ability. Nine phenolic acids were detected in vitex honey samples, in which caffeic acid was the main compound. Honey from Heibei Zanhuang (S2) ranked the highest antioxidant activity was orally administered to mice (5 g kg(-1), 20 g kg(-1)) for 70 days. In high-dose (20 g kg(-1)), vitex honey pretreatment resulting in significant increase in serum oxygen radical absorbance capacity (15.07%) and decrease in Cu(2+)-mediate lipoprotein oxidation (80.07%), and suppression in alanine aminotransferase (75.79%) and aspartate aminotransferase (74.52%), enhancement in the superoxide dismutase and glutathione peroxidase activities and reduction in malondialdehyde (36.15%) and 8-hydroxy-2'-deoxyguanosine (19.6%) formation compared with paracetamol-intoxicated group. The results demonstrated the hepatoprotection of vitex honey against paracetamol-induced liver damage might attribute to its antioxidant and/or perhaps pro-oxidative property.

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.

Comparing the Therapeutic Effectiveness of N-acetylcysteine with the Combination of N-acetyl Cysteine and Cimetidine in Acute Acetaminophen Toxicity: A Double-Blinded Clinical Trial

BACKGROUND

N-acetylcysteine (NAC) has been used as a classic treatment for hepatotoxicity induced by N-acetyl-p-benzoquinone imine (NAPQI) as a metabolite of acetaminophen. However, cimetidine theoretically can reduce the production of toxic metabolites through the inhibition of cytochrome p450, and it recently was proposed as a complementary treatment for acetaminophen toxicity.

OBJECTIVE

The aim of this study was to compare the effects of treating acute acetaminophen toxicity with NAC alone and with a combination of NAC and cimetidine.

METHODS

From October 2013 to March 2014, 105 patients suspected of acetaminophen toxicity who had paraclinical confirmation of toxicity requiring medical treatment (based on the risk assessment nomogram of acetaminophen serum level) were enrolled in this double-blind, randomized, controlled trial at Imam Reza Hospital in Mashhad, Iran. The patients were divided into two groups, i.e., 1) patients who were treated with NAC alone (group A) and 2) patients who were treated with a combination of NAC and cimetidine (group B). The primary outcomes were 1) the serum level of acetaminophen and 2) the serum level of aminotransferases at the time of admission and 4, 12, 24, and 48 hours after admission. Exclusion criteria included multiple toxicities, concurrent diseases that could affect liver enzymes, the use of other drugs, and dissatisfaction with the project. For measuring quantitative data, SPSS version 16 was used for t-test analysis and for analyzing the qualitative data with chi-squared analysis.

RESULTS

Sixty patients (32 females and 28 males) with a mean age of 25.2 ± 7.3 years were classified in two groups of 30.. There was no difference between the groups in terms of their admission information. The average levels of acetaminophen in both groups at admission, 12, 24, and 48 hours after hospitalization were not significantly different from each other. Twelve hours after hospitalization, the aspartate aminotransferase (AST) level in the group treated with NAC was significantly higher than in the group treated with the combination of NAC and cimetidine (IU/L30.1 ± 110.0 versus IU/L26.38 ± 94.93, p = 0.044). At the other times that the level of liver enzymes was assessed, the serum levels of urea and creatinine were not significantly different in the two groups (p > 0.05).

CONCLUSION

The intravenous administration of 300 mg of cimetidine every six hours with NAC did not improve the level of hepatoprotective action significantly compared with the NAC treatment protocol alone.

Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges

It is likely that computer modelling and simulations will become an element of comprehensive cardiac safety testing. Their role would be primarily the integration and the interpretation of previously gathered data. There are still unanswered questions and issues which we list and describe below. They include sources of data used for the development of the models as well as data utilized as input information, which can come from the in vitro studies and the quantitative structure-activity relationship models. The pharmacokinetics of the drugs in question play a crucial role as their active concentration should be considered, yet the question remains where is the right place to assess it. The pharmacodynamic angle includes complications coming from multiple drugs (i.e. active metabolites) acting in parallel as well as the type of interaction with (potentially) multiple affected channels. Once established, the model and the methodology of its use should be further validated, optimistically against individual data reported at the clinical level as the physiological, anatomical, and genetic parameters play a crucial role in the drug-triggered arrhythmia induction. All the abovementioned issues should be at least considered and-hopefully-resolved, to properly utilize the mathematical models for a cardiac safety assessment.

Pathways involved in acetaminophen hepatotoxicity with specific targets for inhibition/downregulation

Insights on molecular/immunological mechanisms involve in APAP hepatotoxicity and pave way for researchers/clinicians/pharma bodies to identify novel biomarkers, effective bioactive candidates and fruitful therapy against APAP hepatotoxicity.

Exploring BSEP inhibition-mediated toxicity with a mechanistic model of drug-induced liver injury

Inhibition of the bile salt export pump (BSEP) has been linked to incidence of drug-induced liver injury (DILI), presumably by the accumulation of toxic bile acids in the liver. We have previously constructed and validated a model of bile acid disposition within DILIsym®, a mechanistic model of DILI. In this paper, we use DILIsym® to simulate the DILI response of the hepatotoxic BSEP inhibitors bosentan and CP-724,714 and the non-hepatotoxic BSEP inhibitor telmisartan in humans in order to explore whether we can predict that hepatotoxic BSEP inhibitors can cause bile acid accumulation to reach toxic levels. We also simulate bosentan in rats in order to illuminate potential reasons behind the lack of toxicity in rats compared to the toxicity observed in humans. DILIsym® predicts that bosentan, but not telmisartan, will cause mild hepatocellular ATP decline and serum ALT elevation in a simulated population of humans. The difference in hepatotoxic potential between bosentan and telmisartan is consistent with clinical observations. However, DILIsym® underpredicts the incidence of bosentan toxicity. DILIsym® also predicts that bosentan will not cause toxicity in a simulated population of rats, and that the difference between the response to bosentan in rats and in humans is primarily due to the less toxic bile acid pool in rats. Our simulations also suggest a potential synergistic role for bile acid accumulation and mitochondrial electron transport chain (ETC) inhibition in producing the observed toxicity in CP-724,714, and suggest that CP-724,714 metabolites may also play a role in the observed toxicity. Our work also compares the impact of competitive and noncompetitive BSEP inhibition for CP-724,714 and demonstrates that noncompetitive inhibition leads to much greater bile acid accumulation and potential toxicity. Our research demonstrates the potential for mechanistic modeling to contribute to the understanding of how bile acid transport inhibitors cause DILI.

Systems pharmacology modeling predicts delayed presentation and species differences in bile acid-mediated troglitazone hepatotoxicity

Troglitazone (TGZ) causes delayed, life-threatening drug-induced liver injury in some patients but was not hepatotoxic in rats. This study investigated altered bile acid homeostasis as a mechanism of TGZ hepatotoxicity using a systems pharmacology model incorporating drug/metabolite disposition, bile acid physiology/pathophysiology, hepatocyte life cycle, and liver injury biomarkers. In the simulated human population, TGZ (200-600 mg/day × 6 months) resulted in delayed increases in serum alanine transaminase >3× the upper limit of normal in 0.3-5.1%, with concomitant bilirubin elevations >2× the upper limit of normal in 0.3-3.6%, of the population. By contrast, pioglitazone (15-45 mg/day × 6 months) did not elicit hepatotoxicity, consistent with clinical data. TGZ was not hepatotoxic in the simulated rat population. In summary, mechanistic modeling based only on bile acid effects accurately predicted the incidence, delayed presentation, and species differences in TGZ hepatotoxicity, in addition to predicting the relative liver safety of pioglitazone. Systems pharmacology models integrating physiology and experimental data can evaluate drug-induced liver injury mechanisms and may be useful to predict the hepatotoxic potential of drug candidates.

Mechanistic Modeling Reveals the Critical Knowledge Gaps in Bile Acid-Mediated DILI

Bile salt export pump (BSEP) inhibition has been proposed to be an important mechanism for drug-induced liver injury (DILI). Modeling can prioritize knowledge gaps concerning bile acid (BA) homeostasis and thus help guide experimentation. A submodel of BA homeostasis in rats and humans was constructed within DILIsym, a mechanistic model of DILI. In vivo experiments in rats with glibenclamide were conducted, and data from these experiments were used to validate the model. The behavior of DILIsym was analyzed in the presence of a simulated theoretical BSEP inhibitor. BSEP inhibition in humans is predicted to increase liver concentrations of conjugated chenodeoxycholic acid (CDCA) and sulfate-conjugated lithocholic acid (LCA) while the concentration of other liver BAs remains constant or decreases. On the basis of a sensitivity analysis, the most important unknowns are the level of BSEP expression, the amount of intestinal synthesis of LCA, and the magnitude of farnesoid-X nuclear receptor (FXR)-mediated regulation.

An Update on Treatment of Drug-Induced Liver Injury

Drug-induced liver injury (DILI) has been linked to more than 1,000 medications and remains the most common cause of acute liver failure in the United States. Here, we review the most current literature regarding treatment and make recommendations for the management of this relatively common disease. Since treatment of DILI remains largely elusive, recent studies have attempted to define new management strategies for these difficult patients. Early diagnosis and withdrawal of the suspected medication is the mainstay of treatment of DILI. For acetaminophen and Amanita mushroom poisoning, there are specific therapies in use. Finally, there are other possible management modalities for DILI, including corticosteroids and ursodeoxycholic acid.

A single-arm clinical trial of a 48-hour intravenous N-acetylcysteine protocol for treatment of acetaminophen poisoning

INTRODUCTION

Acetylcysteine prevents hepatic injury when administered soon after acetaminophen overdose. The most commonly used treatment protocols are a 72-hour oral and a 21-hour intravenous (IV) protocol. Between 1984 and 1994, 409 patients were enrolled in a study to describe the outcomes of patients who were treated using a 48-hour IV protocol. In 1991, an interim analysis reported the first 223 patients. The objective of this manuscript is to report the rates of hepatotoxicity and adverse events occurring during a 48-hour IV acetylcysteine protocol in the entire 409 patient cohort.

METHODS

This was a multicenter, single-arm, open-label clinical trial enrolling patients who presented with a toxic serum acetaminophen concentration within 24 h of acute acetaminophen ingestion. Patients were treated with 140 mg/kg loading dose followed by 70 mg/kg every 4 h for 12 doses. Serum aminotransferase activities were measured every 8 h during the protocol, and adverse events were recorded. The primary outcome was the percentage of subjects who developed hepatotoxicity defined as a peak serum aminotransferase greater than 1000 IU/L.

RESULTS

Four hundred and nine patients were enrolled, and 309 met inclusion for the outcome analysis. The overall percentage of patients developing hepatotoxicity was 18.1%, and 3.4% of patients treated within 10 h developed hepatotoxicity. One acetaminophen-related death occurred in a patient treated at 22 h. Adverse events occurred in 28.9% of enrolled subjects; the most common adverse events were nausea, vomiting, and flushing, and no events were rated as serious by the investigator.

CONCLUSIONS

Acetaminophen-overdosed patients treated with IV acetylcysteine administered as 140 mg/kg loading dose followed by 70 mg/kg every 4 h for 12 doses had a low rate of hepatotoxicity and few adverse events. This protocol delivers a higher dose of acetylcysteine which may be useful in selected cases involving very large overdoses.