Review pubs.acs.org/crt

Reactive Metabolites: Current and Emerging Risk and Hazard Assessments Richard A. Thompson,*,† Emre M. Isin,‡ Monday O. Ogese,§ Jerome T. Mettetal,∥ and Dominic P. Williams§ †

DMPK, Respiratory, Inflammation & Autoimmunity iMed, AstraZeneca R&D, 431 83 Mölndal, Sweden DMPK, Cardiovascular & Metabolic Diseases iMed, AstraZeneca R&D, 431 83 Mölndal, Sweden § Translational Safety, Drug Safety and Metabolism, AstraZeneca R&D, Darwin Building 310, Cambridge Science Park, Milton Rd, Cambridge CB4 0FZ, United Kingdom ‡



Translational Safety, Drug Safety and Metabolism, AstraZeneca R&D, 35 Gatehouse Dr, Waltham, Massachusetts 02451, United States ABSTRACT: Although idiosyncratic adverse drug reactions are rare, they are still a major concern to patient safety. Reactive metabolites are widely accepted as playing a pivotal role in the pathogenesis of idiosyncratic adverse drug reactions. While there are today well established strategies for the risk assessment of stable metabolites within the pharmaceutical industry, there is still no consensus on reactive metabolite risk assessment strategies. This is due to the complexity of the mechanisms of these toxicities as well as the difficulty in identifying and quantifying short-lived reactive intermediates such as reactive metabolites. In this review, reactive metabolite risk and hazard assessment approaches are discussed, and their pros and cons highlighted. We also discuss the nature of idiosyncratic adverse drug reactions, using acetaminophen and nefazodone to exemplify the complexity of the underlying mechanisms of reactive metabolite mediated hepatotoxicity. One of the key gaps moving forward is our understanding of and ability to predict the contribution of immune activation in idiosyncratic adverse drug reactions. Sections are included on the clinical phenotypes of immune mediated idiosyncratic adverse drug reactions and on the present understanding of immune activation by reactive metabolites. The advances being made in microphysiological systems have a great potential to transform our ability to risk assess reactive metabolites, and an overview of the key components of these systems is presented. Finally, the potential impact of systems pharmacology approaches in reactive metabolite risk assessments is highlighted.



CONTENTS

1. Introduction 2. Role of Reactive Metabolites in Toxicity 2.1. Genotoxicity 2.2. Hepatotoxicity 2.3. Clinical Phenotypes of Immune-Mediated Adverse Drug Reactions 3. Assessing the Propensity to Form Reactive Metabolites 3.1. Awareness/Avoidance: Structural and Experimental Alerts 3.2. Experimental Evidence 4. Reactive Metabolite Risk Assessmnets: Dose and Quantitation of Reactive Metabolite Formation 4.1. Quantitative Measures of Reactive Metabolite Formation in Vitro 4.2. Covalent Binding 4.3. Integrating with Dose 5. Integrated Reactive Metabolite Risk Assessments: Incorporating the Initial Mechanisms of Toxicity 6. Mechanisms of Immune Activation by Drugs/ Reactive Metabolites © XXXX American Chemical Society

6.1. Predicting Immune-Mediated Adverse Drug Reactions: Current Status and Unmet Needs 7. Microphysiological Systems 7.1. Requirement for Improved Models of Hepatotoxicity 7.2. Replication of Hepatic Zonation within in Vitro Cytotoxicity Models 7.3. Media Flow 7.4. Coculture 7.5. Metabolic Functionality 8. Systems Pharmacology Approaches for Reactive Metabolite Risk Assessment 9. Conclusions Author Information Corresponding Author Notes

B C C C E F F F H H H I

M N N N N O O P Q R R R

Special Issue: Toxicology Strategies for Drug Discovery - Present and Future

J

Received: September 28, 2015

L A

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology Biographies Acknowledgments Abbreviations References

Review

to mitigate reactive metabolite risks in drug candidates prior to their entering clinical trials. The liver is the organ that is most frequently affected by reactive metabolite-mediated adverse drug reactions. Druginduced liver injury accounts for more than half the cases of acute liver failure in the United States, with acetaminophen (APAP) being responsible for 80% of the cases of liver failure associated with drugs.17 APAP-induced hepatotoxicity is largely explained by our understanding of its metabolism linked to the production of a reactive metabolite; however, many other drugs cause idiosyncratic drug-induced liver injury, which despite being rare, hard to predict, and showing complex dose dependency can cause significant morbidity and mortality. Studies with paradigm compounds and drugs, such as APAP, have helped to stratify the roles of chemical stress and drug bioactivation in the downstream biological processes which may be initiated by reactive metabolites. These include effects on signaling proteins, adaptation processes (cell defense), organelles, apoptosis, necrosis, inflammation, and activation of the innate and adaptive immune systems. Drug metabolism also plays an important role in the initiation and propagation of drug hypersensitivity through the generation of neoantigens that are recognized by the cellular and humoral immune systems.18 Although the majority of drug biotransformations occur in the liver, there is overwhelming evidence to suggest that localized drug metabolism by immune cells is critical for organ-specific reactions such as cutaneous adverse drug reactions.19−22 These reactions are usually rare and are not typically present in animal species, but they can be serious and even fatal in humans23,24 and may lead to the withdrawal of otherwise effective therapeutic agents. At present, during preclinical drug evaluation there are no widely accepted methods for the identification of drugs that may cause hypersensitivity or idiosyncratic drug reactions in humans.25 In this review, various approaches used in the pharmaceutical industry for hazard identification and risk assessment of reactive metabolites will be presented ranging from in silico/in cerebro assessment of structural features, to drug optimization efforts based on in vitro drug metabolism studies, as well as more complex cell-based systems and experiment based predictive models. Also, more integrated strategies that include measures of the initial mechanism of toxicity will be highlighted. Strengths and weaknesses of these approaches will be discussed. One of the major difficulties in developing strategies for the risk assessment of reactive metabolites is the complexity of the mechanisms involved and the gap in our scientific understanding of the pathogenesis of reactive metabolite-mediated idiosyncratic adverse drug reactions. To understand the driving force behind more integrated reactive metabolite risk assessment strategies, two drugs with reactive metabolite formation and a link to hepatotoxicity, acetaminophen and nefazodone, have been discussed in more detail. The major gap in all reactive metabolite risk assessment strategies today, however, is our inability to assess the activation of the human immune system in nonclinical models. As addressing this gap will be critical in moving forward, we have highlighted the clinical consequences of immunemediated adverse drug reactions and the present understanding of immune activation by reactive metabolites. One area of science that will have a major impact on our ability to risk assess reactive metabolites are the developments taking place with microphysiological systems. This is discussed more in detail in the review as is the potential of systems pharmacology approaches.

R S S S

1. INTRODUCTION In the drug discovery and development process, substantial efforts are directed toward designing drug candidates that will be safe to administer to humans. As part of this process, extensive safety testing of the drug candidate as well as of its expected human metabolites is an important part of the preclinical drug development activities. An equally important aspect is the integration of risk assessment strategies early on in the discovery phase to ensure that selected drug candidates minimize the risk of attrition in preclinical safety testing and secure patient safety both in clinical trials and postmarketing.1 Safety testing of the parent drug candidate and its circulating human metabolites is a relatively well-defined activity.2−5 The recommendations issued by regulatory agencies on safety testing of circulating metabolites clearly define criteria that would make a metabolite one of concern.6,7 Provided that the animal species utilized in the preclinical safety studies are exposed to adequate levels of the drug and its circulating metabolites of “concern”, the degree of confidence in the safety of the parent drug and metabolites in humans is considered high. In fact, a retrospective analysis of 200 marketed drugs combined with 68 drugs with black box warnings or that were withdrawn due to idiosyncratic toxicity showed that adverse drug reactions attributed to stable metabolites constitute only a small percentage of all drug related toxic events.8 That analysis suggests the suitability of animal models for safety testing of the parent drug as well as stable circulating metabolites. Whereas the safety testing of stable circulating human metabolites of drug candidates is a well-defined area, there are several reasons why the same is not true for reactive metabolites.9 First, due to their reactivity and due to the fact that most reactive metabolites do not circulate, the detection, identification, and quantification of these metabolites in vivo is not trivial and is in some cases impossible.10 Second, due to the nature of the toxicities linked to reactive metabolites, some target organ toxicities related to reactive metabolites can be dose dependent and reproducible in both preclinical species and humans. These types of adverse drug reactions, or intrinsic toxicities, will be picked up in the standard preclinical safety assessment programs. However, reactive metabolites are also considered to be a key component of many idiosyncratic adverse drug reactions, which are severe, occur infrequently in humans, and are not reproducible in preclinical animal species.11 Thus, negative findings in preclinical safety studies and even early clinical trials do not guarantee the safety of the drug in late stage clinical trials or postmarketing.12,13 The previously mentioned assessment of idiosyncratic adverse drug reactions showed that 78−86% had structural indications of the potential to form reactive metabolites, and of these, 62−69% had experimental evidence of reactive metabolites being a plausible causative factor.8 Over the last two decades, several market-withdrawals (tienilic acid, bromfenac, troglitazone, nefazodone, sitaxentan, etc.) as well as black-box warnings (flutamide, nevirapine, valproic acid, etc.) primarily due to hepatotoxicity10,14 have increased awareness of the risks of idiosyncratic adverse drug reactions.15,16 This has led pharmaceutical companies to develop risk assessment strategies focusing in particular on early discovery B

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

2. ROLE OF REACTIVE METABOLITES IN TOXICITY 2.1. Genotoxicity. The pioneering work of Elisabeth and James Miller with aminoazo dyes laid the foundation for our understanding of the importance of bioactivation in relation to carcinogenicity.26−28 Today, there is a wide understanding of the classes of chemical carcinogens, their metabolism, and mechanisms of action.29,30 This whole area has correctly been called “one of the success stories of biomedical research”.30 Because of this strong scientific understanding and the central importance of ensuring that new drugs do not cause cancer, risk assessment strategies in this area are well established and widely agreed on.31 The test cascade usually includes both in vitro and in vivo studies. To assess for potential risk from metabolites, the first line in vitro test systems is supplemented with liver microsomal or S9 fractions.32,33 The most common system is liver S9 fractions from rats after the induction with Aroclor 1254.34 While this is from the point of view of drug metabolism, a somewhat artificial system, it was shown that most metabolites generated in human liver S9 fractions were also seen in the Aroclor-induced rat liver system.34 One chemical class worth highlighting is embedded aromatic amines, i.e., amides and sulfonamides. As the toxicity of aromatic amines is well established,35 compounds that could be cleaved in vivo to aromatic amines are problematic. Amides can be hydrolytically labile in vivo,36 and sulfonamides have been shown to be cleaved both in vitro and in vivo by glutathione-S-transferase.37−39 The predictability of these cleavage reactions and the understanding of interspecies differences is poor. These types of compounds usually require the synthesis and testing of the potential aromatic amine metabolite itself, as proving that there is no in vivo metabolism can be exceedingly difficult. 2.2. Hepatotoxicity. There are numerous publications outlining the direct and indirect relationships between drug bioactivation and human toxicity,40,41 in particular, of simple chemical compounds which after a single dose are able to produce selective hepatotoxicity. These compounds are generally toxic across species (APAP, carbon tetrachloride, bromobenzene, etc.). Generally, there is convincing evidence that liver injury arises directly from drug bioactivation, especially using P450 isoform specific transgenic knockout mice. However, even for such simple chemicals, the nature of the ultimate toxic species is not always known with certainty. Consequently, this makes the direct association of many drugs which form chemically reactive metabolites and the associated toxicities extremely difficult (Table 1). The aim for this section, is to exemplify this relationship by looking closer at two examples, APAP and nefazodone, where both compounds are well-known to undergo bioactivation to chemically reactive metabolites, and both are associated with clinical liver toxicity. The overt differences include acetaminophen demonstrating intrinsic hepatotoxicity yet nefazodone showing idiosyncratic toxicity. APAP is a commonly used analgesic and antipyretic which is safe at therapeutic doses (4 g/day). The pharmacological activity is thought to be attributed to the inhibition of cyclooxygenase activity and a reduction in prostaglandin synthesis.50 However, during cases of overdose, acute liver failure (ALF) develops which is due to centrilobular hepatic necrosis. To date, APAP hepatotoxicity still remains a major clinical problem and is the single largest cause of acute liver failure in the UK and USA.51 APAP provides an important tool with clinical relevance to study toxicological consequences of drug metabolism across in vitro, in vivo, and clinical systems.

At therapeutic doses, around 55% and 30% of renally excreted metabolites are the glucuronide and sulfate conjugates of APAP, respectively (Figure 1).52 A small proportion of the therapeutic dose (5%) is bioactivated primarily by P450 2E1 and also P450 3A4 and P450 1A2 oxidations to the electrophilic intermediate N-acetyl-p-benzoquinonimine (NAPQI). NAPQI is readily detoxified by GSH conjugation and is excreted in the urine as a cysteine or mercapturate product.53,54 In cases of overdose, low capacity sulfation pathways become saturated, and a greater fraction of the dose undergoes glucuronidation and oxidation. Under these conditions, NAPQI accumulates and cellular stores of GSH become depleted due to the shift in NAPQI formation and GSH synthesis.54−57 The standard treatment for APAP intoxication is N-acetylcysteine (NAC) administration, which replaces hepatic GSH after depletion or conjugation to NAPQI and prevents toxicity, although this is most beneficial if given within 16 h of the overdose. The depletion of hepatic GSH has been shown to be an obligatory step to enable NAQPI to covalently bind to and potentially inhibit the function of a number of critical proteins within cells, leading to cell death.58−61 Examples of critical proteins whose function is inhibited via modification by NAQPI include γ-glutamylcysteine ligase catalytic subunit (GCLC),62 glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldehyde dehydrogenase, and Ca2+/Mg2+ ATPase.63−65 Similarly, covalent binding has been hypothesized to contribute to mitochondrial dysfunction, and the resulting disruption in Ca2+ and ATP homeostasis is thought to be a critical step in the development of cell death associated with APAP overdose. Moreover, the importance of mitochondrial protein binding in the mechanism of APAP toxicity is highlighted by observations with the nontoxic regioisomer of APAP, acetyl meta-aminophenol (AMAP). AMAP undergoes an overall similar level of covalent binding but significantly less covalent binding to mitochondrial protein than APAP.66 Therefore, the extent of covalent binding and which proteins are modified, rather than covalent binding per se, represent a major factor underlying APAP hepatotoxicity. Nefazodone is an antidepressant, withdrawn from the US market in 2004, following withdrawal in Canada and Europe, due to incidences of hepatotoxicity. A black box warning for hepatotoxicity stated that there was 1 case of liver failure resulting in death or transplant per 250,000−300,000 patient years, and over 20 deaths had been reported to the FDA.6 Patients that presented with nefazodone hepatotoxicity did so 1−8 months after commencement of treatment (200−400 mg daily).45,67 In patients with acute liver failure, histology demonstrated bile duct proliferation, cholestasis, and centrilobular necrosis.45 It is unclear how nefazodone caused hepatotoxicity in humans, and the three mechanisms currently presented in the literature are discussed below. Nefazodone is predominantly metabolized by P450 3A4.68 During metabolism in human and rat liver microsomes, it is bioactivated to several quinone-imines and iminium ions that can be trapped with GSH and cyanide, respectively.69,70 The major quinone-imine is formed from hydroxylation para to the piperazinyl nitrogen which can then undergo two electron oxidation to form the corresponding quinone-imine (Figure 2).8,70 The bioactivation of nefazodone in vitro has led to the investigation of binding to liver protein as a mechanism of toxicity. It has been shown to irreversibly bind to human liver proteins in microsomes, S9 fractions, and hepatocytes.70,71 In human liver microsomes, the level of irreversible binding is C

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

Table 1. Clinical and Biomarker Classification of Drug-Induced Liver Injury That Can Arise from Reactive Metabolitesa type of injury

clinical presentation

biomarkers

hepatocellular injury

abdominal pain, malaise, fever and jaundice42

elevations in serum ALT, AST, or both hyperbilirubinemia in severe cases no or minimal elevations in ALP43

cholestatic injury

jaundice and pruritus usually benign but sometimes protracted vanishing bile duct syndrome42

prominent elevations in serum ALP and total bilirubin, 2 times ULN43

mixed hepatocellularcholestatic hepatitis

mixed symptoms

borderline elevations of ALP and ALT43

drug-induced autoimmune hepatitis

rash and joint pains may precede acute or chronic hepatic injury fatigue, nausea, and poor appetite idiopathic autoimmune hepatitis and jaundice47

moderate elevations in ALT with minimal elevations in ALP elevation of serum antibodies like antinuclear antibody, smooth muscle antibody, and antibody to liver-kidney microsomes elevated immunoglobulin and globulin levels48

a

drugs implicated acetaminophen44 amiodarone42 diclofenac42 isoniazid42 ketoconazole42 minocycline42 nefazodone45 nitrofurantoin46 amoxicillin−clavulanic acid43 cephalosporins42 chlorpromazine42 erythromycin42 flucloxacillin42 terbinafine42 carbamazepine42 flutamide42 ibuprofen42 phenytoin42 sulphonamides42 verapamil42 hydralazine49 methyldopa49 minocycline49 nitrofurantoin49

ALP, alkaline phosphatase; ALT, Alanine aminotransferase; AST, aspartate aminotransferase; ULN, upper limit of normal.

Figure 1. Bioactivation and detoxication pathways of APAP.

Figure 2. Oxidation of nefazodone to the reactive quinone imine intermediate. Reprinted from ref 8. Copyright 2011 American Chemical Society.

1364 pmol drug equivalent/mg protein,71 which is over 20 times that of the 50 pmol drug equivalent/mg protein level which Evans et al. suggested as a trigger to initiate investigative studies

for understanding and designing away from covalent binding.72 This binding was dramatically reduced to 306 pmol/mg in the presence of a mixture of UDPGA and GSH and 254 pmol/mg in D

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

toxic epidermal necrolysis (TEN) are the most severe forms, with higher mortality rates compared to those of maculopapular exanthema (MPE), acute generalized exanthematous pustulosis (AGEP), and drug rash/reaction with eosinophilia and systemic symptoms (DRESS). Other cutaneous manifestations of drug hypersensitivity reactions include urticaria, fixed drug eruptions, photosensitive reactions, and erythema exudativum multiforme.81−83 The clinical manifestations of the different cutaneous adverse drug reactions differ and are dependent on the effector cells implicated and cytokine profile of activated T-lymphocytes. While CD4+ T-lymphocytes play an important role in drug-induced MPE and AGEP, CD8+ lymphocytes are involved in SJS and TEN.86 MPE is the most common cutaneous manifestation of the beta-lactam, sulphonamides, quinolones, NSAIDS, anticonvulsants, and allopurinol hypersensitivity reactions. However, there are several other causes of MPE including human immunodeficiency virus (HIV), Epstein−Barr virus (EBV), and cytomegalovirus (CMV), which complicate diagnosis.87 MPE accounts for between 31 and 95% of all drug-induced cutaneous reactions.88,89 The onset of MPE is between 8 and 11 days following drug administration and persists for up to 2 days after the drug has been discontinued.90 MPE is characterized by faint pink or red macules that further develop into maculopapular rash with moderate to severe itching and fever. Drug-specific cytotoxic CD4+ T-lymphocytes are the predominant effector cells that mediate MPE.91−96 Cytokines including INF-ϒ, perforin, granzyme-B, and IL-5, together with chemokines like CCL11/ eotaxin, CCL5/RANTES, and CCL27/CTACKS, play an important role in the pathogenesis of MPE.97−101 Supportive treatments for mild MPE include withdrawal of the implicated drug and application of emollients to affected areas of the skin. For more severe forms of this reaction, short courses of systemic antihistamines and topical corticosteroids are administered. AGEP was first described in 1980 by Beylot and his colleagues.102 It is also referred to as pustular drug eruption or toxic pustuloderma and is mediated by IL-8 secreting T-lymphocytes. Aminopenicillins, macrolides, clindamycin, and sulfonamides are the major drugs implicated in AGEP.103,104 The incidence of AGEP is between 1 and 5 per million per year.105,106 These reactions appear about 5 days following the administration of the causative drug, with clinical symptoms persisting for 1−2 weeks after the cessation of drug therapy.107 AGEP is characterized by numerous small primary, nonfollicular sterile pustules, leucocytosis, eosinophilia, and large areas of edematous erythema108−110 accompanied by skin detachment similar to that seen in SJS and TEN.109,111 In the absence of appropriate clinical intervention, AGEP has a fatality rate of approximately 5%.112 DRESS is characterized by high fever, morbilliform skin rash, malaise, lymphadenopathy, and damage to multiple internal organs including the kidneys, liver, lungs, and/or heart. The liver is the organ most commonly involved, often resulting in fulminant hepatitis.113 The pathophysiology of DRESS involves the recruitment of eosinophils, mediated through IL-5 secreted by activated T-lymphocytes.114 The reactivation of human herpes virus 6 and 7 (HHV-6 and HHV-7) plays a critical role in DRESS.115,116 Certain clinical manifestations of DRESS are linked to a systemic immune response against the reactivation of HHV-6, HHV-7, EBV, and CMV, prompted by the causative drug.117 Picard and his colleagues reported viral reactivation in 76% of patients with DRESS following the administration of carbamazepine, allopurinol, or sulfamethoxazole (SMX). Interestingly, they reported that approximately 50% of the CD8+

human hepatocytes. Taking into account the intrinsic clearance showed that there was a high rate of binding in liver microsomes.73 The link between bioactivation and toxicity is less clear, and it has been proposed that the parent nefazodone compound was the cause of hepatotoxicity in patients, due to in vitro observations of interference in biliary and mitochondrial assays. Indeed, Dykens et al. demonstrated that nefazodone could elicit its toxicity through the inhibition of complex I of the oxidative phosphorylation chain causing a collapse of the mitochondrial membrane potential.74 Also, Kostrubsky et al. reported that nefazodone can inhibit its excretion into the bile through the bile salt export pump (BSEP), causing an accumulation of both nefazodone and toxic bile salts in the liver. In neither case did the metabolism of the compound make it more toxic.75 The examples of APAP and nefazodone indicate that while it is important to understand the ability of compounds to become irreversibly bound to proteins, it is equally important to identify the likelihood of irreversible binding leading to perturbation of cell health, in order to improve risk assessments for the first time in human clinical trials. However, an additional hazard is when no effect on cellular health has been seen despite detectable covalent binding to cellular proteins. This situation raises the possibility that drug−protein haptens will be formed by patients taking the drug and will in the majority of patients elicit no adverse effect whatsoever. The danger here is that, for example, 1 patient in 10,000 has either a unique genotype, containing HLA alleles conferring drug specific sensitivity, or a particular disease phenotype or concomitant medications that render him or her susceptible to drug-induced liver injury. In the following section, we will look at the clinical phenotype of drug-induced hypersensitivity. 2.3. Clinical Phenotypes of Immune-Mediated Adverse Drug Reactions. Drug hypersensitivity represents an impediment to the drug development process and a burden on many national health services. Although many of these reactions are mild and self-limiting, i.e., symptoms resolve after drug withdrawal, a limited number of patients develop serious and sometimes life-threatening conditions. In most cases, no simple relationship is apparent between the dose of drug administered and the development of clinical symptoms. Despite this, it should be noted that most drugs associated with a high incidence of hypersensitivity are administered at high doses.76 As has been discussed, the bioactivation of drugs by hepatic and/or extra hepatic enzymes is sometimes accompanied by significant generation of reactive metabolites which play a critical role in idiosyncratic adverse drug reactions.12,77 These reactive metabolites can covalently modify endogenous proteins to form antigenic determinants that can activate drug-specific T cells, and result in immune-mediated idiosyncratic adverse drug reactions.18 Carbamazepine,78 sulphamethoxazole,79 and nevirapine80 are some examples of drugs that generate proteinreactive metabolites associated with immune-mediated adverse cutaneous reactions. Although drug-induced hypersensitivity reactions target multiple organs including lungs, heart, liver, kidneys, blood, and skin, the skin is one of the most commonly affected organs and accounts for most adverse drug reactions in hospitalized patients.81−83 The large surface area, dense network of dendritic cells (DCs), and vast network of blood vessels make the skin more susceptible to pathogenic T-cell reactions compared to other organs.84,85 Cutaneous reactions to medications vary in appearance and severity. Stevens Johnson syndrome (SJS) and E

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

and corticosteroids160 have been reported to show clinical benefit. Unlike the skin, the role of the adaptive system in reactions in the liver is not well-defined. A number of studies have demonstrated that drug-specific T-cells may play a vital role in the progression of drug-induced liver injury.161,162 Furthermore, multiple HLA risk alleles have been reported as susceptibility factors for idiosyncratic drug-induced liver injury. Some examples of HLA-associated drug-induced liver injury include: flucloxacillin (B*57:01),163 ximelagatran (DRB1*07:01 and HLA-DQA1*02),164 lapatinib (HLA-DRB1*0701-DQA1*0202/ DQB1*0203),165 and co-amoxiclav (DRB1*15:01).166 The various clinical phenotypes, biomarkers, and drugs implicated are summarized in Table 1.42 Furthermore, agranulocytosis, a condition characterized by severe leukopenia, and increased susceptibility to infections has been reported with a number of drugs. The proposed mechanisms of drug-induced agranulocytosis include direct toxicity, inherited abnormalities in drug metabolism, and immunological reactions.167,168 Neutopenia (absolute neutrophil count 14 for a combination of daily doses ≥100 mg and log P ≥ 3. As a screening tool, this is attractive due to the low number of false positives, i.e., a specificity of 96% (46/48). At the same time, however, the sensitivity was 38% (44/116) indicating that a substantial number of drugs of concern would be missed. The authors also highlight the strong correlation between lipophilicity and hepatic metabolism. This of course could lead one to speculate that increasing lipophilicity is leading to an increase in the fraction of the dose being eliminated via metabolism (f m) and thus increasing the propensity for reactive metabolite formation. Covalent binding is one of the most useful quantitative measures of reactive metabolite formation (see above), and there are numerous approaches based on the use of covalent binding in combination with dose. Nakayama et al. used a set of 42 drugs which had been categorized into three risk categories based on indications of severe hepatotoxicity, neutropenia, Stevens Johnson syndrome or agranulocytosis.223 Radiolabeled analogues of the drugs were tested for covalent binding in human liver microsomes and hepatocytes, and in rat liver extracted after in vivo dosing of the radiolabeled drug. The results of the covalent binding assessment for the three studies showed a poor correlation between the different approaches. The covalent binding results for each of the approaches were then plotted against the recommended daily dose of the drug. The best outcome was when covalent binding in human hepatocytes was combined with dose. This allowed the drugs to be split into three separate zones, with clear high and low risk zones, and a middle zone with a mixture of compounds from all three categories. While the strategy would be helpful in decision making for compounds in the high or low risk categories, the large number of drugs from all three categories in the middle zone creates a high degree of uncertainty. A similar approach used a set of radiolabeled analogues of 12 drug-induced liver injury positive and 12 negative drugs.71 Covalent binding levels resulting from the incubation of drugs were compared with human liver microsomes in the presence of

(1) NADPH, (2) NADPH complemented with UDPGA, and (3) NADPH complemented with GSH. The studies were complemented with incubations in human hepatocytes. In general, a correlation was seen between the results in all four systems, even though none of them could on their own differentiate among drug-induced liver injury positive and drug-induced liver injury negative compounds. While multiplying the covalent binding with Cmax gave a better correlation, it was still inadequate to differentiate positive from negative druginduced liver injury compounds. However, using maximum daily dose instead of Cmax considerably improved the separation both with human liver microsomes and hepatocytes and was recommended as a tool to risk assesses drug candidates. Another risk assessment strategy makes use of maximal therapeutic daily dose but for the assessment of reactive metabolite formation combines covalent binding in human liver microsomes, GSH adduct formation in human liver microsomes assessed by LC-MS, and TDI in P450 1A2, 2C9, 2C19, 2D6, and 3A4.233 A set of 223 drugs (51% associated with clinical hepatotoxicity) was used for the validation of the strategy. Of these, 190 were tested in human liver microsomes with GSH and 179 in TDI assays, and the covalent binding of 53 compounds was assessed in human liver microsomes. Clinical dose was then plotted against each of the results, and the best specificity was seen when an arbitrary cutoff of daily dose >100 mg and covalent binding >200 pmol eq/mg protein is introduced where 100% of the 10 compounds in this category were hepatotoxins. However, as the majority of the hepatotoxins were below the arbitrary cutoff, the sensitivity was only 36% (10/28). A decision tree was created where it was proposed that all compounds with a predicted dose below 100 mg/day proceed to precandidate selection. Compounds with predicted daily doses above 100 mg/day were to be tested in the TDI and GSH assays, and positive hits in these would trigger further design work. It was pointed out by the authors that due to the semiquantitative nature of GSH adduct formation by LC-MS, that a dose of >100 mg/day and any degree of GSH adduct formation will be considered a risk. In another approach, the formation of thiol adducts was followed, but instead of assessing for the formation of GSH adducts, dansyl glutathione was used as a nucleophilic trapping agent.235 The assay allowed for the detection and quantification of the trapped adduct by a fluorescence detector, thus providing an alternative to a radiolabel to obtain a quantitative measure of reactive metabolite formation. The assay is, however, performed in liver microsomes limiting the metabolic pathways that will be operating. One of the key strengths of the approach is the use of a daily body burden for reactive metabolites (Drm) as a risk measure. The Drm is derived from the following eq (eq 1):

Drm = D·fa ·fm ·frm

(1)

where D is the total daily dose (mg/day), fa is the fraction of the dose absorbed, f m is the fraction of the dose eliminated via metabolism, and f rm is the fraction of the metabolism leading to thiol-reactive metabolites. The concept of a daily body burden is based on a couple key assumptions. One is that the relevant risk measure for reactive metabolites is the total amount of compound bound per day and not the circulating plasma levels. A second is that it includes a quantitative assessment of the metabolic route(s) leading to reactive metabolite formation rather than the amount of trapped adduct or covalent binding in a static in vitro system run under a short time period (usually under 2 h). I

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

insults, e.g., the parent drug. Further idiosyncratic adverse drug reactions such as drug-induced liver injury have a complex array of initial mechanisms of toxicity, such as cell stress, mitochondrial impairment, specific immune responses,237 or interference with bile salt export transporters such as BSEP.238 It has been proposed that to improve our ability to predict reactive metabolite pathogenesis, risk assessment strategies need to include an assessment of the metabolic activation of compounds but complemented with an assessment of the potential of the compounds or their metabolites to mediate these initial mechanisms of toxicity.8,239 An approach using a multifactorial hazard assessment was proposed as a tool for the assessment of the risk of idiosyncratic adverse drug reactions from candidate drugs.232 The approach used a covalent binding burden based on in vitro covalent binding in human hepatocytes, adjusted for the metabolic turnover in the hepatocytes and the daily clinical dose of the compound. The covalent binding burden was complemented with an in vitro panel covering a number of the key measures of initial mechanisms of toxicity. These included (1) P450 metabolism independent intrinsic cell cytotoxicity assessed in non-P450 expressing THLE cells (SV40 T-antigen-immortalized human liver epithelial cells), (2) P450 3A4 potentiated cell toxicity in THLE cell lines that express P450 3A4,240−242 (3) assessment of mitochondrial injury by following cytotoxicity in HepG2 cells cultured in glucose vs galactose containing media,243 (4) inhibition of the bile salt export pump BSEP,244 and (5) the multidrug resistance-associated protein 2, Mrp2.245 Cutoff values were determined for each of the assays with scores of either 1 = concern or 0 = no concern. A set of 36 radiolabeled drugs, where 27 had severe or marked idiosyncratic adverse drug reaction concern and 9 with low concern, were tested in the in vitro panel as well as in the covalent binding assay. The combined scores from the 5 assays in the in vitro panel were plotted against the covalent binding burden for each compound as shown in Figure 7. Four zones were defined with Zone 1 containing only

The daily body burden as a risk assessment tool has also been applied to studies of covalent binding to human hepatocytes.69 The characterization of nine hepatotoxins and nine nonhepatotoxins based on the estimated total daily body burden of covalent binding to human hepatocytes is shown in Figure 6.

Figure 6. Categorization of hepatotoxins and nonhepatotoxins based on estimated total daily body burden of covalent binding from hepatocyte data. Abbreviations: APAP, acetaminophen; BEN, benoxaprofen; BUS, busprione; CAR, carbamazepine; DIC, diclofenac; DIPH, diphenhydramine; FEL, felbamate; IND, indomethacin; MEL, meloxicam; NEF, nefazodone; PAR, paroxetine; PRO, propranolol; RAL, raloxifene; SIM, simvastatin; SUD, sudoxicam; TA, tienilic acid; and THEO, theophylline. Adapted from ref 69. Copyright 2009 American Chemical Society.

It was highlighted that if a cutoff of 1 mg estimated daily body burden were used, the overall sensitivity and selectivity for distinguishing the hepatotoxins from the nonhepatotoxins would be 67 and 71%, respectively. The study also highlighted one of the difficulties of these types of studies, the in vitro assessment of compounds with very low overall rates of metabolism. Three of the hepatotoxins showed no measurable covalent binding; however, for two of these (carbamazepine and felbamate) there was no substrate turnover, confounding the interpretation of the results. In this section, we have highlighted the importance of quantitative measures of reactive metabolite formation and dose in risk assessment strategies. However, at the same time it is clear that it is difficult to set cutoffs that give both high selectivity and sensitivity in separating problematic drugs from safe ones.

Figure 7. Integrated in vitro hazard matrix. The idiosyncratic adverse drug reactivity categories are severe concern (black inverted triangles), marked concern (red triangles), and low concern (green circles). Reprinted from ref 232. Copyright 2012 American Chemical Society.

5. INTEGRATED REACTIVE METABOLITE RISK ASSESSMENTS: INCORPORATING THE INITIAL MECHANISMS OF TOXICITY While reactive metabolites are considered to play a pivotal role in the pathogenesis of idiosyncratic adverse drug reactions,236 one of the difficulties of risk assessment strategies based solely on the propensity to form or the actual formation of reactive metabolites is the underlying assumption that there are no other chemical

low risk drugs. The approach allowed the discrimination between safe and unsafe drugs with a high sensitivity (100%) and good specificity (78%). A variation of this strategy was applied to the assessment of three endothelin receptor antagonists, sitaxentan, bosentan, and J

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

ambrisentan.246 The compounds were chosen due to their clinical safety profiles, where sitaxentan was withdrawn in 2010 due to idiosyncratic drug-induced liver injury.247 Despite no indication of liver injury in the preclinical toxicity package248 numerous cases of liver failure were reported after clinical treatment with sitaxentan.247 Bosentan has a U.S. Food and Drug Administration black box warning for drug-induced liver injury, and frequent observations of increased ALT levels have been seen in clinical trials.249,250 The mechanisms behind the toxicities for both compounds are poorly defined, even if BSEP inhibition has been proposed as a possible explanation.250,251 Ambrisentan, however, is considered safe, and no increased liver signals were observed, even in patients who had, due to increased plasma ALT levels, discontinued bosentan or sitaxentan treatment.252,253 In the study, the compounds were radiolabeled, and covalent binding was measured in human hepatocytes.246 The compounds were also tested in a modified version of the above-mentioned in vitro panel where the assessment of mitochondrial injury was instead conducted by studying the potential for inhibition of mitochondrial respiration in human liver-derived HuH-7 cells using a Seahorse XFe96 analyzer.246 The results were analyzed both as in the previous work using cutoffs based on direct readouts from the in vitro panel but also taking into account the published maximum plasma concentration (Cmax) levels from clinical studies. Ambrisentan showed no signals in any of the assays either with or without exposure adjustment. Bosentan showed a borderline risk (including a hit in the BSEP inhibition assay) where hits in the in vitro panel decreased from two to one after exposure adjustment. Sitaxentan, however, had hits in all the assays in the in vitro panel both with and without exposure adjustment. Those results together with a very high covalent binding body burden for this compound put it in a high risk category. The results seen in the study were consistent with the clinical picture and would have clearly highlighted sitaxentan as a high risk compound. In recent work by Shah et al., a retrospective analysis of clinical exposure levels of 70 drugs linked to and 55 not linked to drug-induced liver injury (based on the U.S. Food and Drug Administration Liver Toxicity Knowledge Base) was performed to assess the value of using Cmax levels as a tool for drug-induced liver injury prediction.254 Their analysis showed that with this data set, total Cmax (Cmax,total) was a better predictor of toxicity than unbound Cmax (Cmax,u). It was also shown that Cmax,total alone could discriminate drugs linked or not linked to druginduced liver injury with a sensitivity of 80% and a selectivity of 73%. A further assessment of the data was performed by complementing the Cmax,total values with results from a multiparameter set of in vitro assays assessing for suspected initial mechanisms of toxicity. This set included assessment of (1) cell toxicity in THLE or HepG2 cells,255,256 (2) mitochondrial function using a phosphorescent probe in isolated rat mitochondria,257 and (3) BSEP inhibition in human BSEP vesicles.75 This approach showed that compounds with Cmax,total ≥ 1.1 μM and triple liabilities in the in vitro set had significantly higher probability of drug-induced liver injury than those with one or two liabilities. In another recent publication, 81 marketed or withdrawn drugs were studied.258 The drugs were split into two categories: low and high drug-induced liver injury risk, where the high category was a merger of moderate and severe risk compounds based on the FDA categorization.259 Generation of reactive metabolites was tested via glutathione adduct formation and P450 3A4 time-dependent inhibition. Further key measures of

initial mechanisms of toxicity were monitored in a panel consisting of assays assessing BSEP inhibition, cytotoxicity (mouse fibroblasts and human hepatocytes), and mitochondrial toxicity (mouse fibroblasts grown in medium where glucose had been replaced by galactose). The data were analyzed using readouts either adjusted or not adjusted with daily dose or Cmax,total. Using daily dose for adjustment of the assessments of reactive metabolite formation (GSH adduct formation and TDI) and Cmax,total for adjustment of BSEP, and mitochondrial and cellular toxicity the discrimination between the safe and high risk categories had a sensitivity of 79% and a specificity of 81%. The authors found that removal of the assessment of reactive metabolite formation (GSH adduct formation) had the largest negative effect on the discrimination, and removal of human hepatocyte cellular toxicity had the least. It is generally accepted that idiosyncratic adverse drug reactions are idiosyncratic due to individual patient-related risk factors.260,261 At the same time, it is clear that there are compound-related risk factors that define the initial chemical insult and the molecular and cellular events by which toxicity is induced.239,261 These are the basis of the toxicity pathway, the first step in the overall adverse outcome pathway (see Figure 8).262 All of the approaches discussed in this review have as their basis the minimization of compound-related risk factors to mitigate the risk of idiosyncratic adverse drug reactions. Figure 8 illustrates the approaches split into three categories: (1) propensity to form reactive metabolites, (2) risk assessment based on dose and a quantitative measure of the reactive metabolite formation, and (3) integrated risk assessments which also include basic measures of cellular response. The integrated risk assessment approaches have succeeded in incorporating measures of a number of suspected initial mechanisms of toxicity into useable tools in drug discovery. The integrated risk assessment approaches discussed here have been shown to have good predictability with both sensitivity and specificity values of around 80% or higher. There are, however, difficulties with these types of assessment. While it is clear that dose is an important characteristic of toxicity, even in the case of idiosyncratic adverse drug reactions,231 it has been shown that dose alone cannot adequately differentiate high risk from low risk compounds.223,232 What is less clear is how to optimally incorporate dose/exposure into a risk assessment strategy. If one of the hazards is an assessment of the formation of reactive metabolites such as with in vitro covalent binding, the total amount of the compound leading to a reactive metabolite has been considered the key indicator. This requires an understanding of the daily dose of the compound, the fraction of the metabolism leading to covalent binding, the fraction of the elimination via metabolism and the fraction of the compound absorbed.232 However, if it is, e.g., a competitive inhibitor of a transporter a measure of concentration such as Cmax has been proposed to be more appropriate. All of these approaches described in this section used Cmax, total, in one case based on an analysis of the human exposure in an array of drug compounds254 and another based on the US Food and Drug Administration draft guidance on drug interaction studies.246 A further complication is the relevance of peripheral blood plasma concentrations to the intercellular concentrations. For the endothelin receptor antagonists as examples, in vitro studies in isolated hepatocytes showed a 4-, 20-, and 40-fold higher intracellular than extracellular concentration for ambrisentan, bosentan, and sitaxentan, respectively.251 Finally, use of human dose or exposure in the preclinical phase of drug discovery is K

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

Figure 8. Adverse outcome pathway. Conceptual diagram of an adverse outcome pathway aligned with the risk assessment approaches described in this review. Propensity refers to the approaches described in section 3 on assessing the propensity to form reactive metabolites. Quantitative assessments refer to the approaches described in section 4 on dose and quantitation of reactive metabolite formation. Integrated assessments refer to the approaches described in section 5 on incorporating the initial mechanisms of toxicity.

or directly through the production of apoptosis-inducing cytolytic molecules. In more severe conditions, for example, SJS/TEN, granulysin-secreting cytotoxic CD8+ T-cells predominate. Phenotypic and functional characterization of drug-specific T cells from hypersensitive patients led to the development of an expanded Coombs and Gell classification of hypersensitivity.266−268 Therefore, it was possible to describe different clinical conditions according to the CD phenotype of the drug-specific T cells and the cytokines/effector molecules they secrete. Importantly, this classification is somewhat obsolete as it does not encompass the new populations of T cells that have been discovered over the past decade. Identification of HLA alleles as important susceptibility factors for many forms of hypersensitivity has led to a renewed interest in understanding the nature of the drug interaction with immune receptors, in particular MHC molecules and drug-specific T cell receptors. The most progress has been made exploring whether HLA class I associations with particular forms of hypersensitivity relate to a specific fit of the drug-derived antigen within MHC class I molecules. For example, we now know that antigens derived from abacavir (HLA-B*57:01),264 allopurinol (HLAB*58:01), 269 carbamazepine (HLA-B*15:02 and HLAA*31:01),270,271 and flucloxacillin (HLA-B*57:01)163 interact with a degree of selectivity with the HLA risk allele to activate T-cells from hypersensitive patients.133,272−275 Furthermore, for each of the drugs highlighted above, it is possible to activate ̈ donors with the drug if they carry T cells from healthy drug-naive a risk allele.272,274,276,277 Although genetic studies have identified several HLA class II associations with drug hypersensitivity (e.g., amoxicillin-clavulanate,278 lapatinib,165,279 and ximelagatran164), as yet functional studies have not as yet been able to relate the activation of T cells to restriction of the fit of the drug-derived antigen within the MHC molecule encoded by the HLA risk allele. Does the association between specific hypersensitivity reactions and MHC proteins provide mechanistic information on how T cells are likely to be triggered? The simple answer is no.

dependent on the robustness of the dose or exposure prediction. In our experience, this tends to introduce a large degree of variability into the toxicity prediction but does have the advantage of giving an understanding of a potential worst case scenario. A greater issue is, however, the limitations of the existing assays used in these approaches. Many of the assays used to assess the initial mechanisms of toxicity lack adequate metabolic activation. This applies to THLE null and HepG2 cells as well as BSEP or Mrp2 expressing vesicles. This deficiency will hopefully be addressed through the advances being made in microphysiological systems.263 What is more difficult to address, however, is that the ability to assess immune activation by drugs or reactive metabolites is missing in all models discussed so far in this review. Covalent binding to human hepatocytes or other measures of reactive metabolite formation and reactivity can be considered a surrogate measure and potentially explain their significance in these approaches.232,258 However, a deeper understanding of the mechanisms of immune activation by drugs and their reactive metabolites, and the development of biological models to assess this are one of the key gaps moving forward.

6. MECHANISMS OF IMMUNE ACTIVATION BY DRUGS/REACTIVE METABOLITES Immune-mediated idiosyncratic drug reactions are rare, unpredictable, and sometimes fatal. In the past decade, genome-wide association studies have identified the expression of particular HLA (human leukocyte antigen) alleles as risk factors for certain reactions.163 Risk HLA alleles alone are insufficient in some instances to orchestrate an immune response. Multiple studies have demonstrated that certain individuals expressing risk HLA alleles are tolerant to the “culprit drugs” and do not develop the associated reactions.264,265 In mild conditions, CD4+ T cells are believed to be the primary mediators of tissue injury, potentially inducing cell death indirectly through the release of cytokines that recruit phagocytes L

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

antigen presenting cells) and alters the structure of the peptide binding groove. As such, with time, an altered repertoire of HLA binding self-peptides is displayed on the surface of the antigen presenting cell (Figure 9C). It is assumed that a portion of these peptides cross-react with pathogen-derived peptides and activate pre-existing memory T cells in susceptible patients resulting in abacavir hypersensitivity syndrome. Initially, it was assumed that many drugs might activate T cells via this pathway; however, despite intensive studies a second example has not been forthcoming. This is not surprising as for most forms of drug hypersensitivity, even those with an HLA allele association, patients expressing multiple HLA alleles go on to develop hypersensitivity indicating that the presence of the risk allele increases the likelihood of developing hypersensitivity but is not the sole predisposing factor. Interestingly, more recent research by Meng et al. has demonstrated the formation of an α,βunsaturated abacavir aldehyde in patients, which binds covalently to human serum albumin,287 thus suggesting that multiple molecular mechanisms of immune activation may be responsible for abacavir hypersensitivity syndrome. 6.1. Predicting Immune-Mediated Adverse Drug Reactions: Current Status and Unmet Needs. Unexpected but potentially fatal idiosyncratic drug hypersensitivity reactions are among the most important reasons why drugs have failed at advanced stages of research and development.288 Drug antigen, the disease pathomechanism, and patient-specific factors are the critical predictors of idiosyncratic drug hypersensitivity reactions, but their relative contributions during the initiation, progression, and resolution of drug hypersensitivity are not fully understood. Currently, there are numerous limitations in estimating the relative involvements of comorbidities and comedications in a particular case of idiosyncratic drug hypersensitivity. During the preclinical phases of drug developments, numerous data on the chemistry, efficacy, pharmacokinetics (PK), and pharmacodynamics (PD) of a candidate drug is available to researchers. Also available at this stage is an in-depth understanding of the disease pathogenesis, risk factors, comorbidities, and also diagnostic and prognostic biomarkers, but very little is known at this stage about the genetic (epigenetics and polymorphisms) and nongenetic peculiarities of the potential patient(s) to whom the given drug will be administered, hence the difficulty to fully predict idiosyncratic drug hypersensitivity reactions during early drug development. The efficacy and toxicity profiles of a particular drug are sometimes dependent on interindividual variability.289 The drug antigen can induce idiosyncratic drug hypersensitivity reactions via several molecular mechanisms including: direct cytotoxicity and/or activation of the immune system. Although high throughput assays exist to evaluate potentially toxic molecules based on in vitro covalent haptenation,232 these assays alone are inadequate to predict the potential of a candidate drug and/or its metabolite(s) to induce idiosyncratic drug hypersensitivity reactions, hence the need to develop multiple assays that can integrate the various risk factors and enhance predictability of drug hypersensitivity. Despite the challenges surrounding the development of animal models of idiosyncratic drug hypersensitivity reactions, there has been some remarkable progress. Recent studies involving the inhibition of immune tolerance in transgenic mouse models have for the first time demonstrated a role for the adaptive immune system in both halothane- and amodiaquine-induced-liver injury.290−293 Although substantial efforts have been put into understanding the molecular mechanisms of drug hypersensitivity reactions,

Figure 9. (A) Hapten/pro-hapten hypothesis. T cell recognition of drug antigen: parent drug or their reactive metabolites covalently modify macromolecules like proteins, engulf and then process them by antigen presenting cells and present them in an MHC restricted fashion to T cells. (B) Pharmacological interaction with immune receptor (PI concept). T cell recognition of drug antigen by pharmacological interaction with immune receptors: The parent drug or their reactive metabolites bind noncovalently with TCR and MHC. Dashed lines represent noncovalent interactions. (C) Altered self-peptide repertoire hypothesis. The interaction of peptide A with the HLA molecule does not result in an immune response. The presence of a drug molecule alters the repertoire of the HLA ligand (peptide B) presented to TCR and results in hypersensitivity reactions.

Traditionally, drugs are thought to activate T cells via 2 pathways. Pathway 1 (hapten hypothesis; Figure 9A) involves the covalent formation of drug−protein adducts as the initiation step. This is followed by protein processing and release of drugmodified peptides that are believed to bind directly to MHC molecules prior to triggering T cells.280,281 Pathway 2 (pharmacological interaction, PI concept; Figure 9B) involves direct binding of drugs to the peptide-loaded MHC molecules expressed on the surface of antigen presenting cells. The drug− MHC binding interaction is reversible but sufficiently stable to trigger T cell responses.282,283 It is likely that the species interacting with T cell receptors is similar for both pathways (i.e., a MHC peptide−drug complex and T cell receptor). The main differences are (1) the nature of the drug−peptide binding interaction and (2) the way in which the drug is transported to the MHC peptide binding groove. Ground-breaking studies from 3 independent research groups exploring abacavir HLA binding devised a new pathway of drugdependent T cell activation.284−286 The authors demonstrated that abacavir binds directly to endogenous HLA-B*57:01 (within M

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

relatively homogeneous view of liver function and cellular phenotype, when in reality, the morphology and function of hepatocytes vary enormously with their position along the liver sinusoids from the portal triad to the central vein. This phenomenon, termed zonation, has been described in practically all areas of liver function.302 Bioenergetic processes, carbohydrate-, lipid-, nitrogen-, and xenobiotic metabolism, bile acid conjugation, and detoxication processes, have all been predominantly located within separate hepatic zones. The distribution of function along the length of the sinusoid is thought to be regulated by diverse factors such as oxygen and hormone gradients, nutrients, and matrix composition. Importantly, the effects of the aforementioned factors upon nonparenchymal cell distribution and signaling may alter the cross-talk between these cells and hepatocytes, assisting in defining the ultimate phenotype of a hepatocyte at a particular sinusoidal position. The regional characterization of hepatic responses to model hepatotoxins is well described, especially with compounds such as APAP, which elicits centrilobular hydropic, degenerative necrosis in the centrilobular zones of rodent and human livers. This necrotic pattern is also well characterized for carbon tetrachloride and bromobenzene in rodents. Less well characterized are the molecular processes leading to subsequent proliferation in periportal and midzonal regions in rodents. The regional hepatic injury pattern observed after the administration of methapyrilene and allyl alcohol to rats, consists of periportal necrosis.303,304 Importantly, differential zonal responses to hepatotoxins assists in dissecting more sensitive mechanistic details, which are highly unlikely to be observed in in vitro models. For example, the periportal rat hepatotoxin, methapyrilene, elicits initial glutathione depletion in periportal hepatocytes, while stimulating glutathione synthesis and adaptation in centrilobular hepatocytes. In in vitro hepatocyte incubations with methapyrilene, this is simply manifest as glutathione depletion and necrosis, with important adaptive responses being missed. It has been observed with the centrilobular hepatotoxin, APAP, using immunohistochemical techniques that there were dynamic changes in the lobule zonation of glutathionylated proteins. At 1 h after APAP exposure, the level of glutathionylation decreased in a single layer of hepatocytes around the central veins but increased in the remaining centrilobular hepatocytes. The increase correlated with the immunohistochemical localization of APAP covalently bound to protein.305 Subsequently, the level of glutathionylation decreased over time in the centrilobular regions. These temporal and zonal pattern changes in protein glutathionylation after APAP exposure indicate that protein glutathionylation may play a role in protein homeostasis during APAP-induced hepatocellular injury. 7.3. Media Flow. The importance of media flow is difficult to evaluate due to the multiple effects this can elicit in vitro. The positive aspects for inclusion of flow include the removal of metabolites and bile, which would otherwise be toxic to hepatocytes.306 Failure to remove bile, in particular, could lead to the generation of artificially sensitive in vitro models. Flow also allows concentration gradients to be established, such as oxygen, nutrients, or hormones, more correctly simulating a sinusoid. These concentration gradients subsequently allow phenotypic alteration of the hepatocytes giving zonation with cells exposed to higher oxygen and nutrients at the inlet having altered drug metabolism functionality compared with the cells closer to the outlet, which are exposed to decreased concentrations. Mathematical models have been established, designed to enhance physiology in bioartificial livers.307,308 Hepatocyte

knowledge gaps still exist, most especially concerning the role of HLA-risk alleles in immune responses. Addressing this and other important unmet needs for predicting idiosyncratic drug hypersensitivity reactions will require a panel of experiments designed around the drug antigen, environmental/disease factors, and the patient-specific risk factors.

7. MICROPHYSIOLOGICAL SYSTEMS With the development of novel in vitro microphysiological systems, incorporating human multicellular coculture and in vivo-like flow parameters,294 there is a real interest and excitement in this area, particularly with the potential for including patient sensitivity parameters such as infection, obesity, and HLA-typed cells.295 It is beyond the scope of this review to cover the multiple types of novel in vitro models, which have been reviewed extensively elsewhere.294,296−300 7.1. Requirement for Improved Models of Hepatotoxicity. The current in vitro test systems used by the pharmaceutical industry include simple liver-derived cell-based or subcellular models that are poorly predictive of clinical liver injury. Generally, these models do not take account of the mechanistic basis of human drug-induced liver injury or the environmental conditions under which human drug-induced liver injury might occur. Particularly puzzling side effects are caused by the innate and adaptive immune system. Therefore, any attempt at recapitulating this toxicity in vitro requires the physiological components of the different immune systems. These immune mediated reactions are classified as idiosyncratic and thus not predictable drug side effects. While any drug is assumed to be able to elicit hypersensitivity reactions, the frequency differs widely. Antibiotics and antiepileptics are the most prevalent drug classes responsible. As described in the previous section, the risk of sensitization and the severity of clinical symptoms depend on the state of immune activation of the subject, dose, frequency of exposure, route of exposure (epicutaneous is more sensitizing than oral or parenteral applications), duration of exposure, sex (reactions are more frequent in female subjects), and immunogenetic predisposition (in particular HLA-B alleles). This poor predictivity of toxicological potential stems from a number of reasons: (1) the physiological gap between the cells that are currently used and human hepatocytes as they exist in their native state; (2) the lack of physiological integration with other cells and systems within the liver that are required to amplify the initial toxicological lesion into overt toxicity, and (3) there is no way to assess how low level cell damage induced by a drug may, in certain circumstances, lead to overt drug-induced liver injury in only a small minority of patients (i.e., idiosyncratic hepatotoxins). New approaches that improve upon conventional processes of risk assessment and safety evaluation are currently sought. Numerous promising new technologies and approaches have been described or are being developed which replicate many of the key biological processes implicated in reproducible and idiosyncratic/humanspecific drug-induced liver injury.299 These range from simple cell systems to complex in vivo models and may have the potential to enhance prediction and risk assessment of druginduced liver injury in humans if used during drug discovery and/ or preclinical development. The choice of system or model to use depends upon the biology under investigation, for example, in tissue engineering, it is widely accepted that 3D tissue culture models behave very differently than 2D models.301 7.2. Replication of Hepatic Zonation within in Vitro Cytotoxicity Models. Current in vitro models offer both a N

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

order for hepatic bioreactors to be useful in predicting chemical risk, the recapitulation of metabolic functionality within a novel in vitro system should be the absolute minimum requirement. It is important to note that metabolic functionality can be quite different from cytochrome P450 mRNA or protein levels as mRNA does not always translate to protein, and protein may be present but nonfunctional. Many publications use the cytochrome P450 transcript or protein level as a marker of cell functionality, which although helpful is not an assessment of enzyme function. For example, freshly isolated hepatocytes will have a full message and protein complement yet are likely to have rapidly decreasing functional cytochrome P450 capability due to enzyme inactivation by reactive oxygen and nitrogen species.315,316 Allen et al. employed a flat-plate bioreactor to impose physiologic gradients over phenotypically stable hepatocytes and evaluate spatial variations of P450 expression and toxicity.302 Perfusion of APAP resulted in a shift in the dose−response such that 20 mM was completely toxic in bioreactor cultures as compared to 40 mM in static cultures. Also, perfusion cultures at 15 mM demonstrated a toxicity pattern similar to that of the centrilobular localization seen in vivo. This in vitro zonal toxicity provides insight into the deleterious effects of APAP and the factors that contribute to spatial toxicity which would not be observed in conventional culture models. Toxic effects in this study are likely due to the depletion of glutathione, which provides protective inactivation of NAPQI. Though centrilobular localization of APAP toxicity in vivo has been attributed to local expression of P450 isoenzymes 2E1 and 3A, reduced oxygen availability in centrilobular regions may also contribute by depleting ATP and glutathione or increasing damage by reactive species. A combination of these factors likely resulted in the regional toxicity observed in reactor cultures under dynamic oxygen gradients. Demonstration of zonal toxicity in vitro allows decoupling of the effects of P450 bioactivation and glutathione levels on acute APAP toxicity. Hepatocyte sandwich perfusion culture can further improve long-term liver specific functions in vitro due to the improved transport of oxygen and nutrients to the cell surface and effective waste removal from cellular local environment. Perfusion bioreactors have been developed based on conventional sandwich cultures which have a hepatocyte monolayer overlaid by a collagen gel layer 24 h after seeding.317 However, the perfusion flow introduces the hepatocyte culture to the effect of fluid-induced shear stress not typically encountered by the cells in natural livers where hepatocytes are shielded by a layer of sinusoidal endothelial. High shear stress in the perfusion culture could be detrimental to hepatocyte viability and in vitro functions. In addition, the integrity of the top collagen layer in direct contact with media flow may be compromised by the longterm perfusion that leads to the degeneration of the sandwich matrix and, subsequently, the variation in mass transport of drug access during drug testing. Xia et al. have developed a laminar-flow perfusion bioreactor for immediate-overlay sandwich culture that minimizes shear stress and preserves the mass transport consistency.317 The cultured hepatocytes exhibited restored cell polarity, biliary excretion, and maintenance of metabolic functions for 2 weeks. Liver specific functions of hepatocytes, such as the phase I drug metabolic function (e.g., EROD activity), are reported to be maintained for up to 15 days. The perfusion culture exhibited a higher sensitivity to APAP-induced toxicity than the static culture on both day 7 and day 14, attributable to the well-maintained

zonation can be achieved by setting operating parameters. For in vivo models, this is 70 mmHg, which is lower than that required in vitro because in vivo, the red blood cells carry the oxygen, so there is effectively controlled release. Zonation has been achieved in vitro,302,309 however, by regulating the size of the zones. Difficulties concerning inclusion of media flow include the requirement for pumps and a sterile flow environment. At this moment, a drawback is that flow systems are not amenable to HTS and that there can be considerable issues with nonspecific binding. The rate of flow is important, as hepatocytes are generally protected from flow or shear stress due to the lining of hepatic endothelial cells. 7.4. Coculture. There is a current need for hepatic cell coculture either in a 2D or 3D environment. Cells comprising the various innate immunity populations in blood and organs are responsible for the immediate recognition and elimination of pathogens or abnormal structures and constitute the first line defense. Immune cells of the innate immune system have evolved in a specialized way to help broadly eliminate the variety of pathogens they need to remove. Local inflammation from the first line cellular defense attracts neutrophils, specialized in killing pathogens, and NK cells, specialized in the elimination of tumorand virus-infected cells, from blood into the invasion zone. Neutrophils are the largest population of innate immune cells with a lifespan of 5 days. They carry the main first line defense burden at the interface of the human body with the outside world, employing three strategies to eliminate invaders: pathogen uptake, secretion of antimicrobials, and release of neutrophil extracellular traps. As such, it would seem a reasonable requirement that these cells are incorporated into novel in vitro models hoping to recapitulate drug-induced inflammatory toxicity.295 On the most basic level for the liver, this consists of hepatocyte and Kupffer cell coculture, which provides hepatocytes with diffusible growth factors and cytokines. For example, Kupffer cells release both pro-proliferative (e.g., TNFα and IL-6) and antiproliferative (IL-1 and TGF-β) cytokines and signals.310 These cytokines were shown to be involved in precipitating the indirect toxicity of certain drugs, such as trovafloxacin.311 This observation that trovafloxacin causes greater cytotoxicity in the presence of lipopolysaccharide (LPS) in coculture versus hepatocytes alone312 due to the release of inflammatory mediators has also been demonstrated in vivo. Treatment of mice or rats with inflammatory stimuli such as LPS or TNFα together with trovafloxacin caused toxicity only in the presence of the inflammatory stimulus. However, routine assessment of inflammation-mediated toxicity in vitro has so far been difficult due to the lack of commercially available primary human liver model systems incorporating inflammatory cells.312 Clearly, simply sensitizing cells is very different from understanding in vivo risk factors,313and demonstrating increased sensitivity to hepatotoxins does not necessarily mean an improved system. More interesting, however, is the use of endothelial cells to enhance and prolong hepatocyte function, in particular, the use of liver sinusoidal endothelial cells.314 Hepatocyte-fibroblast and liver sinusoidal endothelial cells cross-talk through the production of short-range paracrine signals thus prolonging phenotypic function. 7.5. Metabolic Functionality. There are many different ways in which to assess bioreactor capability. This could be done through the investigation of physiological parameters, such as cell viability, albumin production, or urea detoxification. However, in O

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

8. SYSTEMS PHARMACOLOGY APPROACHES FOR REACTIVE METABOLITE RISK ASSESSMENT While major advances are being made in the microphysiological systems area, understanding the potential safety profile of compounds with reactive metabolite liabilities requires interpreting preclinical safety end points as they are expected to manifest themselves in humans. The ability to scale results from preclinical species to humans would be important to understand the likelihood of toxicity based on known physiological and metabolic differences between species. However, as previously discussed, reactive metabolites are reactive and short-lived, and thus difficult to detect in vivo. Further, while preclinical animal species have shown great value in assessing risk related to many types of toxicity, they are often poor predictors of idiosyncratic adverse drug reactions, forcing a reliance on in vitro data. Similarly, detailed information about the tissue distribution of suspected reactive metabolites is unlikely to be available, lending further weight to a physiologically based pharmacokinetics (PBPK) approach which can make estimates of plasma and tissue PK based on in vitro ADMET data. Because of these difficulties, assessment of reactive metabolites is well suited to benefit from PBPK and PBPK/PD models which aim to describe the tissue exposure and potential toxicity of reactive metabolites in silico. Mathematical modeling for the predictive safety of reactive metabolites has been applied for years in the field of environmental toxicology, where such models allow studies to be simulated which would not be experimentally possible.321,322 Understanding the propensity for a compound to induce damage through the production of reactive metabolites involves understanding the exposure of the parent in metabolic tissues, the rate of conversion to reactive metabolite, accumulation of the reactive metabolite, and the formation of adducts with endogenous proteins and neutralization processes (e.g., GSH) (Figure 10). The ADME of the parent can be modeled utilizing standard PBPK models, with emphasis on the distribution to the primary metabolic tissues (e.g., liver, kidney) and the rate of metabolic conversion into the reactive metabolite. Similarly, exposure of the reactive metabolite can be modeled with a PBPK approach where the dosing of the reactive metabolite coincides with the site of metabolism of the parent compound. One route of toxicity induced from reactive metabolites can occur when the cellular ability to neutralize the metabolite is overwhelmed or depleted, allowing the reactive metabolites to form adducts with endogenous proteins. To improve predictions of this route of toxicity, the balance between the rate and duration of the reactive metabolite exposure and recovery of GSH levels needs to be accounted for in a modeling approach. One example of a model which accounts for this process is implemented in the DILIsym platform.323 In the DILIsym model, the buildup of reactive metabolites is modeled as a competition between rapid reaction with glutathione and slow reaction with cellular proteins, while accounting for the limited pool of GSH and the dynamics of GSH renewal. In one example, this platform was utilized to predict the toxicity of methapyriline323 and in another to evaluate the differential toxicity between APAP and AMAP.324 The latter example illustrates how in a modeling context, multiple hypotheses were able to be tested directly, and in this case, the model suggested that the major difference is due to differences in the rate of production of reactive metabolites rather than inherent differences in the toxicity of the produced metabolites.

drug metabolic functions of the sandwich perfusion culture. Approximately 60% of cell death was observed in the perfusion culture treated with 25 mM of APAP for 24 h. Furthermore, the cell viability in the perfusion culture after APAP treatment on day 7 and day 14 was similar. In contrast, the static culture treated with APAP on day 7 and day 14 produced highly variable cell viability results. Prot et al. have attempted to combine enzymatic functionality with proteomic and transcriptomic assessment of their flat-bed, HepG2-populated bioreactor.318 Classical studies demonstrating the hepatotoxic effect of APAP performed in vitro show that cytotoxicity is observed for concentrations of APAP ranging up to 5 to 20 mM with interspecies differences. In this case, APAP led to an EC50 of 1 mM concentration for 72 h of contact only in the microfluidic biochip configuration.318 This result is in accordance with the toxic plasma level observed in humans and which ranges between 1 and 2 mM. Prot et al. did not take into account the protein binding to APAP in their work. Although APAP has a weak affinity for plasma proteins ( 200 compounds. Chem. Res. Toxicol. 25, 2067−2082. (234) Chen, M., Borlak, J., and Tong, W. (2013) High lipophilicity and high daily dose of oral medications are associated with significant risk for drug-induced liver injury. Hepatology 58, 388−396. (235) Gan, J., Ruan, Q., He, B., Zhu, M., Shyu, W. C., and Humphreys, W. G. (2009) In vitro screening of 50 highly prescribed drugs for thiol adduct formation–comparison of potential for drug-induced toxicity and extent of adduct formation. Chem. Res. Toxicol. 22, 690−698. (236) Pirmohamed, M., Madden, S., and Park, B. K. (1996) Idiosyncratic drug reactions. Metabolic bioactivation as a pathogenic mechanism. Clin. Pharmacokinet. 31, 215−230. (237) Russmann, S., Kullak-Ublick, G. A., and Grattagliano, I. (2009) Current concepts of mechanisms in drug-induced hepatotoxicity. Curr. Med. Chem. 16, 3041−3053. (238) Morgan, R. E., Trauner, M., van Staden, C. J., Lee, P. H., Ramachandran, B., Eschenberg, M., Afshari, C. A., Qualls, C. W., Jr, Lightfoot-Dunn, R., and Hamadeh, H. K. (2010) Interference with bile salt export pump function is a susceptibility factor for human liver injury in drug development. Toxicol. Sci. 118, 485−500. (239) Thompson, R. A., Isin, E. M., Li, Y., Weaver, R., Weidolf, L., Wilson, I. D., Claesson, A., Page, K., Dolgos, H., and Kenna, J. G. (2011) Risk assessment and mitigation strategies for reactive metabolites in drug discovery and development. Chem.-Biol. Interact. 192, 65−71. (240) Greer, M. L., Smith, T. J. D., and Kenna, J. G. (2009) Mechanisms of Drug Hepatotoxicity in Man: Novel Insights Provided by the THLE-CYP Cell Panel. Toxicology 262, 4−4. (241) Gustafsson, F., Foster, A. J., Sarda, S., Bridgland-Taylor, M., and Kenna, J. G. (2014) A Correlation Between the In Vitro Drug Toxicity of Drugs to Cell Lines That Express Human P450s and Their Propensity to Cause Liver Injury in Humans. Toxicol. Sci. 137, 189−211. (242) Foster, A. J., Prime, L. H., Gustafsson, F., Temesi, D. G., Isin, E. M., Midlov, J., Castagnoli, N., and Kenna, J. G. (2013) Bioactivation of the Cannabinoid Receptor Antagonist Rimonabant to a Cytotoxic Iminium Ion Metabolite. Chem. Res. Toxicol. 26, 124−135.

(243) Dykens, J. A., and Will, Y. (2007) The significance of mitochondrial toxicity testing in drug development. Drug Discovery Today 12, 777−785. (244) Dawson, S., Stahl, S., Paul, N., Barber, J., and Kenna, J. G. (2012) In vitro inhibition of the bile salt export pump correlates with risk of cholestatic drug-induced liver injury in humans. Drug Metab. Dispos. 40, 130−138. (245) Colombo, F., Armstrong, C., Duan, J., and Rioux, N. (2012) A high throughput in vitro mrp2 assay to predict in vivo biliary excretion. Xenobiotica 42, 157−163. (246) Kenna, J. G., Stahl, S. H., Eakins, J. A., Foster, A. J., Andersson, L. C., Bergare, J., Billger, M., Elebring, M., Elmore, C. S., and Thompson, R. A. (2015) Multiple compound-related adverse properties contribute to liver injury caused by endothelin receptor antagonists. J. Pharmacol. Exp. Ther. 352, 281−290. (247) Galiè, N., Hoeper, M. M., Gibbs, J. S. R., and Simonneau, G. (2011) Liver toxicity of sitaxentan in pulmonary arterial hypertension. Eur. Respir. J. 37, 475−476. (248) Owen, K., Cross, D. M., Derzi, M., Horsley, E., and Stavros, F. L. (2012) An overview of the preclinical toxicity and potential carcinogenicity of sitaxentan (Thelin®), a potent endothelin receptor antagonist developed for pulmonary arterial hypertension. Regul. Toxicol. Pharmacol. 64, 95−103. (249) Humbert, M., Segal, E. S., Kiely, D. G., Carlsen, J., Schwierin, B., and Hoeper, M. M. (2007) Results of European post-marketing surveillance of bosentan in pulmonary hypertension. Eur. Respir. J. 30, 338−344. (250) Fattinger, K., Funk, C., Pantze, M., Weber, C., Reichen, J., Stieger, B., and Meier, P. J. (2001) The endothelin antagonist bosentan inhibits the canalicular bile salt export pump: a potential mechanism for hepatic adverse reactions. Clin. Pharmacol. Ther. 69, 223−231. (251) Lepist, E. I., Gillies, H., Smith, W., Hao, J., Hubert, C., St. Claire, R. L., 3rd, Brouwer, K. R., and Ray, A. S. (2014) Evaluation of the endothelin receptor antagonists ambrisentan, bosentan, macitentan, and sitaxsentan as hepatobiliary transporter inhibitors and substrates in sandwich-cultured human hepatocytes. PLoS One 9, e87548. (252) McGoon, M. D., Frost, A. E., Oudiz, R. J., Badesch, D. B., Galie, N., Olschewski, H., McLaughlin, V. V., Gerber, M. J., Dufton, C., Despain, D. J., and Rubin, L. J. (2006) Ambrisentan Rescue Therapy in Patients With Pulmonary Arterial Hypertension Who Discontinued Bosentan or Sitaxsentan Due to Liver Function Test Abnormalities. Chest 130, 122−129. (253) Frampton, J. E. (2011) Ambrisentan. Am. J. Cardiovasc. Drugs 11, 215−226. (254) Shah, F., Leung, L., Barton, H. A., Will, Y., Rodrigues, A. D., Greene, N., and Aleo, M. D. (2015) Setting Clinical Exposure Levels of Concern for Drug-Induced Liver Injury (DILI) Using Mechanistic in vitro Assays. Toxicol. Sci. 147, 500−514. (255) Greene, N., Fisk, L., Naven, R. T., Note, R. R., Patel, M. L., and Pelletier, D. J. (2010) Developing structure-activity relationships for the prediction of hepatotoxicity. Chem. Res. Toxicol. 23, 1215−1222. (256) Marroquin, L. D., Hynes, J., Dykens, J. A., Jamieson, J. D., and Will, Y. (2007) Circumventing the Crabtree effect: replacing media glucose with galactose increases susceptibility of HepG2 cells to mitochondrial toxicants. Toxicol. Sci. 97, 539−547. (257) Hynes, J., Marroquin, L. D., Ogurtsov, V. I., Christiansen, K. N., Stevens, G. J., Papkovsky, D. B., and Will, Y. (2006) Investigation of drug-induced mitochondrial toxicity using fluorescence-based oxygensensitive probes. Toxicol. Sci. 92, 186−200. (258) Schadt, S., Simon, S., Kustermann, S., Boess, F., McGinnis, C., Brink, A., Lieven, R., Fowler, S., Youdim, K., Ullah, M., Marschmann, M., Zihlmann, C., Siegrist, Y. M., Cascais, A. C., Di Lenarda, E., Durr, E., Schaub, N., Ang, X., Starke, V., Singer, T., Alvarez-Sanchez, R., Roth, A. B., Schuler, F., and Funk, C. (2015) Minimizing DILI risk in drug discovery - A screening tool for drug candidates. Toxicol. In Vitro 30, 429. (259) Chen, M., Vijay, V., Shi, Q., Liu, Z., Fang, H., and Tong, W. (2011) FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discovery Today 16, 697−703. Z

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

(260) Senior, J. R. (2008) What is idiosyncratic hepatotoxicity? What is it not? Hepatology 47, 1813−1815. (261) Ulrich, R. G. (2007) Idiosyncratic toxicity: a convergence of risk factors. Annu. Rev. Med. 58, 17−34. (262) Andersen, M. E., and Krewski, D. (2009) Toxicity testing in the 21st century: bringing the vision to life. Toxicol. Sci. 107, 324−330. (263) Bale, S. S., Vernetti, L., Senutovitch, N., Jindal, R., Hegde, M., Gough, A., McCarty, W. J., Bakan, A., Bhushan, A., Shun, T. Y., Golberg, I., DeBiasio, R., Usta, O. B., Taylor, D. L., and Yarmush, M. L. (2014) In vitro platforms for evaluating liver toxicity. Exp. Biol. Med. (London, U. K.) 239, 1180−1191. (264) Mallal, S., Nolan, D., Witt, C., Masel, G., Martin, A. M., Moore, C., Sayer, D., Castley, A., Mamotte, C., Maxwell, D., James, I., and Christiansen, F. T. (2002) Association between presence of HLAB*5701, HLA-DR7, and HLA-DQ3 and hypersensitivity to HIV-1 reverse-transcriptase inhibitor abacavir. Lancet 359, 727−732. (265) Martin, A. M., Nolan, D., Gaudieri, S., Almeida, C. A., Nolan, R., James, I., Carvalho, F., Phillips, E., Christiansen, F. T., Purcell, A. W., McCluskey, J., and Mallal, S. (2004) Predisposition to abacavir hypersensitivity conferred by HLA-B*5701 and a haplotypic Hsp70Hom variant. Proc. Natl. Acad. Sci. U. S. A. 101, 4180−4185. (266) Pichler, W. J. (2003) Delayed drug hypersensitivity reactions. Ann. Intern. Med. 139, 683−693. (267) Pichler, W. J. (2003) Drug-induced autoimmunity. Curr. Opin. Allergy Clin. Immunol. 3, 249−253. (268) Pichler, W. J., Yawalkar, N., Britschgi, M., Depta, J., Strasser, I., Schmid, S., Kuechler, P., and Naisbitt, D. (2002) Cellular and molecular pathophysiology of cutaneous drug reactions. Am. J. Clin. Dermatol. 3, 229−238. (269) Hung, S. I., Chung, W. H., Liou, L. B., Chu, C. C., Lin, M., Huang, H. P., Lin, Y. L., Lan, J. L., Yang, L. C., Hong, H. S., Chen, M. J., Lai, P. C., Wu, M. S., Chu, C. Y., Wang, K. H., Chen, C. H., Fann, C. S., Wu, J. Y., and Chen, Y. T. (2005) HLA-B*5801 allele as a genetic marker for severe cutaneous adverse reactions caused by allopurinol. Proc. Natl. Acad. Sci. U. S. A. 102, 4134−4139. (270) McCormack, M., Alfirevic, A., Bourgeois, S., Farrell, J. J., Kasperaviciute, D., Carrington, M., Sills, G. J., Marson, T., Jia, X., de Bakker, P. I., Chinthapalli, K., Molokhia, M., Johnson, M. R., O’Connor, G. D., Chaila, E., Alhusaini, S., Shianna, K. V., Radtke, R. A., Heinzen, E. L., Walley, N., Pandolfo, M., Pichler, W., Park, B. K., Depondt, C., Sisodiya, S. M., Goldstein, D. B., Deloukas, P., Delanty, N., Cavalleri, G. L., and Pirmohamed, M. (2011) HLA-A*3101 and carbamazepineinduced hypersensitivity reactions in Europeans. N. Engl. J. Med. 364, 1134−1143. (271) Chung, W. H., Hung, S. I., Hong, H. S., Hsih, M. S., Yang, L. C., Ho, H. C., Wu, J. Y., and Chen, Y. T. (2004) Medical genetics: a marker for Stevens-Johnson syndrome. Nature 428, 486. (272) Monshi, M. M., Faulkner, L., Gibson, A., Jenkins, R. E., Farrell, J., Earnshaw, C. J., Alfirevic, A., Cederbrant, K., Daly, A. K., French, N., Pirmohamed, M., Park, B. K., and Naisbitt, D. J. (2013) Human leukocyte antigen (HLA)-B*57:01-restricted activation of drug-specific T cells provides the immunological basis for flucloxacillin-induced liver injury. Hepatology 57, 727−739. (273) Lichtenfels, M., Farrell, J., Ogese, M. O., Bell, C. C., Eckle, S., McCluskey, J., Park, B. K., Alfirevic, A., Naisbitt, D. J., and Pirmohamed, M. (2014) HLA restriction of carbamazepine-specific T-Cell clones from an HLA-A*31:01-positive hypersensitive patient. Chem. Res. Toxicol. 27, 175−177. (274) Chessman, D., Kostenko, L., Lethborg, T., Purcell, A. W., Williamson, N. A., Chen, Z., Kjer-Nielsen, L., Mifsud, N. A., Tait, B. D., Holdsworth, R., Almeida, C. A., Nolan, D., Macdonald, W. A., Archbold, J. K., Kellerher, A. D., Marriott, D., Mallal, S., Bharadwaj, M., Rossjohn, J., and McCluskey, J. (2008) Human leukocyte antigen class I-restricted activation of CD8+ T cells provides the immunogenetic basis of a systemic drug hypersensitivity. Immunity 28, 822−832. (275) Yun, J., Mattsson, J., Schnyder, K., Fontana, S., Largiader, C. R., Pichler, W. J., and Yerly, D. (2013) Allopurinol hypersensitivity is primarily mediated by dose-dependent oxypurinol-specific T cell response. Clin. Exp. Allergy 43, 1246−1255.

(276) Yun, J., Marcaida, M. J., Eriksson, K. K., Jamin, H., Fontana, S., Pichler, W. J., and Yerly, D. (2014) Oxypurinol directly and immediately activates the drug-specific T cells via the preferential use of HLAB*58:01. J. Immunol. 192, 2984−2993. (277) Farrell, J., Lichtenfels, M., Sullivan, A., Elliott, E. C., Alfirevic, A., Stachulski, A. V., Pirmohamed, M., Naisbitt, D. J., and Park, B. K. (2013) Activation of carbamazepine-responsive T-cell clones with metabolically inert halogenated derivatives. J. Allergy Clin. Immunol. 132, 493−495. (278) Donaldson, P. T., Daly, A. K., Henderson, J., Graham, J., Pirmohamed, M., Bernal, W., Day, C. P., and Aithal, G. P. (2010) Human leucocyte antigen class II genotype in susceptibility and resistance to co-amoxiclav-induced liver injury. J. Hepatol. 53, 1049− 1053. (279) Spraggs, C. F., Parham, L. R., Hunt, C. M., and Dollery, C. T. (2012) Lapatinib-induced liver injury characterized by class II HLA and Gilbert’s syndrome genotypes. Clin. Pharmacol. Ther. 91, 647−652. (280) Padovan, E., Bauer, T., Tongio, M. M., Kalbacher, H., and Weltzien, H. U. (1997) Penicilloyl peptides are recognized as T cell antigenic determinants in penicillin allergy. Eur. J. Immunol. 27, 1303− 1307. (281) Brander, C., Mauri-Hellweg, D., Bettens, F., Rolli, H., Goldman, M., and Pichler, W. J. (1995) Heterogeneous T cell responses to betalactam-modified self-structures are observed in penicillin-allergic individuals. J. Immunol. 155, 2670−2678. (282) Schnyder, B., Burkhart, C., Schnyder-Frutig, K., von Greyerz, S., Naisbitt, D. J., Pirmohamed, M., Park, B. K., and Pichler, W. J. (2000) Recognition of sulfamethoxazole and its reactive metabolites by drugspecific CD4+ T cells from allergic individuals. J. Immunol. 164, 6647− 6654. (283) Zanni, M. P., von Greyerz, S., Schnyder, B., Brander, K. A., Frutig, K., Hari, Y., Valitutti, S., and Pichler, W. J. (1998) HLA-restricted, processing- and metabolism-independent pathway of drug recognition by human alpha beta T lymphocytes. J. Clin. Invest. 102, 1591−1598. (284) Illing, P. T., Vivian, J. P., Dudek, N. L., Kostenko, L., Chen, Z., Bharadwaj, M., Miles, J. J., Kjer-Nielsen, L., Gras, S., Williamson, N. A., Burrows, S. R., Purcell, A. W., Rossjohn, J., and McCluskey, J. (2012) Immune self-reactivity triggered by drug-modified HLA-peptide repertoire. Nature 486, 554−558. (285) Ostrov, D. A., Grant, B. J., Pompeu, Y. A., Sidney, J., Harndahl, M., Southwood, S., Oseroff, C., Lu, S., Jakoncic, J., de Oliveira, C. A., Yang, L., Mei, H., Shi, L., Shabanowitz, J., English, A. M., Wriston, A., Lucas, A., Phillips, E., Mallal, S., Grey, H. M., Sette, A., Hunt, D. F., Buus, S., and Peters, B. (2012) Drug hypersensitivity caused by alteration of the MHC-presented self-peptide repertoire. Proc. Natl. Acad. Sci. U. S. A. 109, 9959−9964. (286) Norcross, M. A., Luo, S., Lu, L., Boyne, M. T., Gomarteli, M., Rennels, A. D., Woodcock, J., Margulies, D. H., McMurtrey, C., Vernon, S., Hildebrand, W. H., and Buchli, R. (2012) Abacavir induces loading of novel self-peptides into HLA-B*57:01: an autoimmune model for HLAassociated drug hypersensitivity. AIDS 26, F21−29. (287) Meng, X., Lawrenson, A. S., Berry, N. G., Maggs, J. L., French, N. S., Back, D. J., Khoo, S. H., Naisbitt, D. J., and Park, B. K. (2014) Abacavir forms novel cross-linking abacavir protein adducts in patients. Chem. Res. Toxicol. 27, 524−535. (288) Csermely, P., Korcsmaros, T., Kiss, H. J., London, G., and Nussinov, R. (2013) Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol. Ther. 138, 333−408. (289) Turner, R. M., Park, B. K., and Pirmohamed, M. (2015) Parsing interindividual drug variability: an emerging role for systems pharmacology. Wiley Interdiscip. Rev. Syst. Biol. Med. 7, 221−241. (290) Chakraborty, M., Fullerton, A. M., Semple, K., Chea, L. S., Proctor, W. R., Bourdi, M., Kleiner, D. E., Zeng, X., Ryan, P. M., Dagur, P. K., Berkson, J. D., Reilly, T. P., and Pohl, L. R. (2015) Drug-induced allergic hepatitis develops in mice when myeloid-derived suppressor cells are depleted prior to halothane treatment. Hepatology 62, 546−557. (291) Mak, A., and Uetrecht, J. (2015) The Role of CD8 T Cells in Amodiaquine-Induced Liver Injury in PD1−/− Mice Cotreated with Anti-CTLA-4. Chem. Res. Toxicol. 28, 1567−1573. AA

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

(292) Metushi, I. G., Cai, P., Dervovic, D., Liu, F., Lobach, A., Nakagawa, T., and Uetrecht, J. (2015) Development of a novel mouse model of amodiaquine-induced liver injury with a delayed onset. J. Immunotoxicol. 12, 247−260. (293) Metushi, I. G., Hayes, M. A., and Uetrecht, J. (2015) Treatment of PD-1(−/−) mice with amodiaquine and anti-CTLA4 leads to liver injury similar to idiosyncratic liver injury in patients. Hepatology 61, 1332−1342. (294) Bhatia, S. N., and Ingber, D. E. (2014) Microfluidic organs-onchips. Nat. Biotechnol. 32, 760−772. (295) Giese, C., and Marx, U. (2014) Human immunity in vitro solving immunogenicity and more. Adv. Drug Delivery Rev. 69−70, 103− 122. (296) Esch, E. W., Bahinski, A., and Huh, D. (2015) Organs-on-chips at the frontiers of drug discovery. Nat. Rev. Drug Discovery 14, 248−260. (297) Khetani, S. R., Berger, D. R., Ballinger, K. R., Davidson, M. D., Lin, C., and Ware, B. R. (2015) Microengineered liver tissues for drug testing. J. Lab. Autom. 20, 216−250. (298) Hutzler, J. M., Ring, B. J., and Anderson, S. R. (2015) LowTurnover Drug Molecules: A Current Challenge for Drug Metabolism Scientists. Drug Metab. Dispos. 43, 1917−1928. (299) Godoy, P., Hewitt, N. J., Albrecht, U., Andersen, M. E., Ansari, N., Bhattacharya, S., Bode, J. G., Bolleyn, J., Borner, C., Bottger, J., Braeuning, A., Budinsky, R. A., Burkhardt, B., Cameron, N. R., Camussi, G., Cho, C. S., Choi, Y. J., Craig Rowlands, J., Dahmen, U., Damm, G., Dirsch, O., Donato, M. T., Dong, J., Dooley, S., Drasdo, D., Eakins, R., Ferreira, K. S., Fonsato, V., Fraczek, J., Gebhardt, R., Gibson, A., Glanemann, M., Goldring, C. E., Gomez-Lechon, M. J., Groothuis, G. M., Gustavsson, L., Guyot, C., Hallifax, D., Hammad, S., Hayward, A., Haussinger, D., Hellerbrand, C., Hewitt, P., Hoehme, S., Holzhutter, H. G., Houston, J. B., Hrach, J., Ito, K., Jaeschke, H., Keitel, V., Kelm, J. M., Kevin Park, B., Kordes, C., Kullak-Ublick, G. A., Lecluyse, E. L., Lu, P., Luebke-Wheeler, J., Lutz, A., Maltman, D. J., Matz-Soja, M., McMullen, P., Merfort, I., Messner, S., Meyer, C., Mwinyi, J., Naisbitt, D. J., Nussler, A. K., Olinga, P., Pampaloni, F., Pi, J., Pluta, L., Przyborski, S. A., Ramachandran, A., Rogiers, V., Rowe, C., Schelcher, C., Schmich, K., Schwarz, M., Singh, B., Stelzer, E. H., Stieger, B., Stober, R., Sugiyama, Y., Tetta, C., Thasler, W. E., Vanhaecke, T., Vinken, M., Weiss, T. S., Widera, A., Woods, C. G., Xu, J. J., Yarborough, K. M., and Hengstler, J. G. (2013) Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Arch. Toxicol. 87, 1315−1530. (300) Rebelo, S. P., Costa, R., Silva, M. M., Marcelino, P., Brito, C., and Alves, P. M. (2015) Three-dimensional co-culture of human hepatocytes and mesenchymal stem cells: improved functionality in long-term bioreactor cultures. J. Tissue Eng. Regener. Med., DOI: 10.1002/term.2099. (301) Williams, D. P., Shipley, R., Ellis, M. J., Webb, S., Ward, J., Gardner, I., and Creton, S. (2013) Novel in vitro and mathematical models for the prediction of chemical toxicity. Toxicol. Res. 2, 40−59. (302) Allen, J. W., Khetani, S. R., and Bhatia, S. N. (2005) In vitro zonation and toxicity in a hepatocyte bioreactor. Toxicol. Sci. 84, 110− 119. (303) Lee, V. M., Cameron, R. G., and Archer, M. C. (1998) Zonal location of compensatory hepatocyte proliferation following chemically induced hepatotoxicity in rats and humans. Toxicol. Pathol. 26, 621−627. (304) Mercer, A. E., Regan, S. L., Hirst, C. M., Graham, E. E., Antoine, D. J., Benson, C. A., Williams, D. P., Foster, J., Kenna, J. G., and Park, B. K. (2009) Functional and toxicological consequences of metabolic bioactivation of methapyrilene via thiophene S-oxidation: Induction of cell defence, apoptosis and hepatic necrosis. Toxicol. Appl. Pharmacol. 239, 297−305. (305) Yang, X., Greenhaw, J., Ali, A., Shi, Q., Roberts, D. W., Hinson, J. A., Muskhelishvili, L., Beger, R., Pence, L. M., Ando, Y., Sun, J., Davis, K., and Salminen, W. F. (2012) Changes in mouse liver protein glutathionylation after acetaminophen exposure. J. Pharmacol. Exp. Ther. 340, 360−368.

(306) Schulz, S., Schmitt, S., Wimmer, R., Aichler, M., Eisenhofer, S., Lichtmannegger, J., Eberhagen, C., Artmann, R., Tookos, F., Walch, A., Krappmann, D., Brenner, C., Rust, C., and Zischka, H. (2013) Progressive stages of mitochondrial destruction caused by cell toxic bile salts. Biochim. Biophys. Acta, Biomembr. 1828, 2121−2133. (307) Davidson, A. J., Ellis, M. J., and Chaudhuri, J. B. (2010) A theoretical method to improve and optimize the design of bioartificial livers. Biotechnol. Bioeng. 106, 980−988. (308) Davidson, A. J., Ellis, M. J., and Chaudhuri, J. B. (2012) A theoretical approach to zonation in a bioartificial liver. Biotechnol. Bioeng. 109, 234−243. (309) Allen, J. W., and Bhatia, S. N. (2003) Formation of steady-state oxygen gradients in vitro: application to liver zonation. Biotechnol. Bioeng. 82, 253−262. (310) LeCluyse, E. L., Witek, R. P., Andersen, M. E., and Powers, M. J. (2012) Organotypic liver culture models: meeting current challenges in toxicity testing. Crit. Rev. Toxicol. 42, 501−548. (311) Liguori, M. J., Ditewig, A. C., Maddox, J. F., Luyendyk, J. P., Lehman-McKeeman, L. D., Nelson, D. M., Bhaskaran, V. M., Waring, J. F., Ganey, P. E., Roth, R. A., and Blomme, E. A. (2010) Comparison of TNFalpha to lipopolysaccharide as an inflammagen to characterize the idiosyncratic hepatotoxicity potential of drugs: Trovafloxacin as an example. Int. J. Mol. Sci. 11, 4697−4714. (312) Messner, S., Agarkova, I., Moritz, W., and Kelm, J. M. (2013) Multi-cell type human liver microtissues for hepatotoxicity testing. Arch. Toxicol. 87, 209−213. (313) Ramm, S., and Mally, A. (2013) Role of drug-independent stress factors in liver injury associated with diclofenac intake. Toxicology 312, 83−96. (314) March, S., Hui, E. E., Underhill, G. H., Khetani, S., and Bhatia, S. N. (2009) Microenvironmental regulation of the sinusoidal endothelial cell phenotype in vitro. Hepatology 50, 920−928. (315) Aitken, A. E., Lee, C. M., and Morgan, E. T. (2008) Roles of nitric oxide in inflammatory downregulation of human cytochromes P450. Free Radical Biol. Med. 44, 1161−1168. (316) Lee, C. M., Kim, B. Y., Li, L., and Morgan, E. T. (2008) Nitric oxide-dependent proteasomal degradation of cytochrome P450 2B proteins. J. Biol. Chem. 283, 889−898. (317) Xia, L., Ng, S., Han, R., Tuo, X., Xiao, G., Leo, H. L., Cheng, T., and Yu, H. (2009) Laminar-flow immediate-overlay hepatocyte sandwich perfusion system for drug hepatotoxicity testing. Biomaterials 30, 5927−5936. (318) Prot, J. M., Briffaut, A. S., Letourneur, F., Chafey, P., Merlier, F., Grandvalet, Y., Legallais, C., and Leclerc, E. (2011) Integrated proteomic and transcriptomic investigation of the acetaminophen toxicity in liver microfluidic biochip. PLoS One 6, e21268. (319) Hewitt, N. J., Lechon, M. J., Houston, J. B., Hallifax, D., Brown, H. S., Maurel, P., Kenna, J. G., Gustavsson, L., Lohmann, C., Skonberg, C., Guillouzo, A., Tuschl, G., Li, A. P., LeCluyse, E., Groothuis, G. M., and Hengstler, J. G. (2007) Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab. Rev. 39, 159−234. (320) Bruderer, R., Bernhardt, O. M., Gandhi, T., Miladinovic, S. M., Cheng, L. Y., Messner, S., Ehrenberger, T., Zanotelli, V., Butscheid, Y., Escher, C., Vitek, O., Rinner, O., and Reiter, L. (2015) Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues. Mol. Cell. Proteomics 14, 1400−1410. (321) Campbell, J., Van Landingham, C., Crowell, S., Gentry, R., Kaden, D., Fiebelkorn, S., Loccisano, A., and Clewell, H. (2015) A preliminary regional PBPK model of lung metabolism for improving species dependent descriptions of 1,3-butadiene and its metabolites. Chem.-Biol. Interact. 238, 102−110. (322) Johanson, G., and Filser, J. G. (1996) PBPK model for butadiene metabolism to epoxides: quantitative species differences in metabolism. Toxicology 113, 40−47. AB

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Chemical Research in Toxicology

Review

(323) Howell, B. A., Yang, Y., Kumar, R., Woodhead, J. L., Harrill, A. H., Clewell, H. J., 3., Andersen, M. E., Siler, S. Q., and Watkins, P. B. (2012) In vitro to in vivo extrapolation and species response comparisons for drug-induced liver injury (DILI) using DILIsym: a mechanistic, mathematical model of DILI. J. Pharmacokinet. Pharmacodyn. 39, 527−541. (324) Howell, B. A., Siler, S. Q., and Watkins, P. B. (2014) Use of a systems model of drug-induced liver injury (DILIsym((R))) to elucidate the mechanistic differences between acetaminophen and its less-toxic isomer, AMAP, in mice. Toxicol. Lett. 226, 163−172. (325) Park, B. K., Boobis, A., Clarke, S., Goldring, C. E. P., Jones, D., Kenna, J. G., Lambert, C., Laverty, H. G., Naisbitt, D. J., Nelson, S., Nicoll-Griffith, D. A., Obach, R. S., Routledge, P., Smith, D. A., Tweedie, D. J., Vermeulen, N., Williams, D. P., Wilson, I. D., and Baillie, T. A. (2011) Managing the challenge of chemically reactive metabolites in drug development. Nat. Rev. Drug Discovery 10, 292−306. (326) Aleo, M. D., Luo, Y., Swiss, R., Bonin, P. D., Potter, D. M., and Will, Y. (2014) Human drug-induced liver injury severity is highly associated with dual inhibition of liver mitochondrial function and bile salt export pump. Hepatology 60, 1015−1022. (327) Ankley, G. T., Bennett, R. S., Erickson, R. J., Hoff, D. J., Hornung, M. W., Johnson, R. D., Mount, D. R., Nichols, J. W., Russom, C. L., Schmieder, P. K., Serrrano, J. A., Tietge, J. E., and Villeneuve, D. L. (2010) Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment. Environ. Toxicol. Chem. 29, 730−741. (328) Soldatow, V. Y., LeCluyse, E. L., Griffith, L. G., and Rusyn, I. (2013) In vitro models for liver toxicity testing. Toxicol. Res. 2, 23−39. (329) Khetani, S. R., Kanchagar, C., Ukairo, O., Krzyzewski, S., Moore, A., Shi, J., Aoyama, S., Aleo, M., and Will, Y. (2013) Use of micropatterned cocultures to detect compounds that cause druginduced liver injury in humans. Toxicol. Sci. 132, 107−117. (330) Mueller, D., Kraemer, L., Hoffmann, E., Klein, S., and Noor, F. (2014) 3D organotypic HepaRG cultures as in vitro model for acute and repeated dose toxicity studies. Toxicol. In Vitro 28, 104−112. (331) Seifert, M., Lubitz, A., Trommer, J., Koennig, D., Korus, G., Marx, U., Volk, H., Duda, G., Kasper, G., Lehmann, K., Stolk, M., and Giese, C. (2012) Crosstalk between immune cells and mesenchymal stromal cells in a 3D bioreactor system. Int. J. Artif. Organs 35, 986−995. (332) Scheer, N., and Wilson, I. D. (2015) A comparison between genetically humanized and chimeric liver humanized mouse models for studies in drug metabolism and toxicity. Drug Discovery Today, DOI: 10.1016/j.drudis.2015.09.002. (333) Uetrecht, J., and Kaplowitz, N. (2015) Inhibition of immune tolerance unmasks drug-induced allergic hepatitis. Hepatology 62, 346− 348. (334) Dara, L., Liu, Z., and Kaplowitz, N. (2015) Mechanisms of adaptation and progression in idiosyncratic drug induced liver injury, clinical implications. Liver Int., DOI: 10.1111/liv.12988.

AC

DOI: 10.1021/acs.chemrestox.5b00410 Chem. Res. Toxicol. XXXX, XXX, XXX−XXX

Reactive Metabolites: Current and Emerging Risk and Hazard Assessments.

Although idiosyncratic adverse drug reactions are rare, they are still a major concern to patient safety. Reactive metabolites are widely accepted as ...
562B Sizes 1 Downloads 8 Views