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

Advances in drug-induced liver injury research: in vitro models, mechanisms, omics and gene modulation techniques

Drug-induced liver injury (DILI) refers to drug-mediated damage to the structure and function of the liver, ranging from mild elevation of liver enzymes to severe hepatic insufficiency, and in some cases, progressing to liver failure. The mechanisms and clinical symptoms of DILI are diverse due to the varying combination of drugs, making clinical treatment and prevention complex. DILI has significant public health implications and is the primary reason for post-marketing drug withdrawals. The search for reliable preclinical models and validated biomarkers to predict and investigate DILI can contribute to a more comprehensive understanding of adverse effects and drug safety. In this review, we examine the progress of research on DILI, enumerate in vitro models with potential benefits, and highlight cellular molecular perturbations that may serve as biomarkers. Additionally, we discuss omics approaches frequently used to gather comprehensive datasets on molecular events in response to drug exposure. Finally, three commonly used gene modulation techniques are described, highlighting their application in identifying causal relationships in DILI. Altogether, this review provides a thorough overview of ongoing work and approaches in the field of DILI.

Oleanolic acid induces hepatic injury by disrupting hepatocyte tight junction and dysregulation of farnesoid X receptor-mediated bile acid efflux transporters

Oleanolic acid (OA) is a naturally occurring pentacyclic triterpene compound that has been reported to cause cholestatic liver injury. However, the regulation and pathogenic role of bile acids in OA-induced development of cholestatic liver injury remains largely unclear. Farnesoid X receptor (FXR) is a metabolic nuclear receptor that plays an important role in bile acid homeostasis in the liver by regulating efflux transporters bile salt export pump (BSEP) and multidrug resistance-associated protein 2 (MRP2). The aim of this study was to investigate the effect of OA on hepatocyte tight junction function and determine the role of FXR, BSEP, and MRP2 in the mechanism of impairment of transport of bile acids induced by OA. Both in vivo and in vitro models were used to characterize the OA-induced liver injury. The liquid chromatography-tandem mass spectrometry (LC-MS) was employed to characterize the efflux function of the transporters, and the results showed that OA caused a blockage of bile acids efflux. OA treatment resulted in decreased expression levels of the tight junction proteins zonula occludens-1 and occludin. Immunofluorescence results showed that OA treatment significantly reduced the number of bile ducts and the immunofluorescence intensity. Pretreatment with agonists of FXR and MRP2, respectively, in animal experiments attenuated OA-induced liver injury, while pretreatment with inhibitors of BSEP and MRP2 further aggravated OA-induced liver injury. These results suggest that OA inhibits FXR-mediated BSEP and MRP2, leading to impaired bile acid efflux and disruption of tight junctions between liver cells, resulting in liver damage.

High-Throughput Assessment of Bile Salt Export Pump Inhibition Using RapidFire-MS and DESI-MS

The bile salt export pump (BSEP) assay is widely used to evaluate the potential for drug-induced liver injury (DILI) early in the drug discovery process. While traditional liquid chromatography-mass spectrometry (LC-MS)-based approaches have been utilized for BSEP activity testing, they have intrinsic limitations in either throughput or the requirement for sample preparation and are difficult to scale up in order to screen drug candidates. Here we demonstrate the use of two different high-throughput MS methods based on solid-phase extraction (SPE) and desorption electrospray ionization (DESI) for high-throughput BSEP activity assessment in a label-free manner, with minimal needs for sample workup, at sampling rates of ∼11 and ∼5.5 s/sample, respectively. Both approaches were validated, compared, and successfully applied to the evaluation of 96 drug candidates for the inhibition of taurocholic acid (TCA) transport using BSEP vesicles.

Bioactivation and reactivity research advances - 2023 year in review

Advances in the field of bioactivation have significantly contributed to our understanding and prediction of drug-induced liver injury (DILI). It has been established that many adverse drug reactions, including DILI, are associated with the formation and reactivity of metabolites. Modern methods allow us to detect and characterize these reactive metabolites in earlier stages of drug development, which helps anticipate and circumvent the potential for DILI. Improved in silico models and experimental techniques that better reflect in vivo environments are enhancing predictive capabilities for DILI risk. Further, studies on the mechanisms of bioactivation, including enzyme interactions and the role of individual genetic differences, have provided valuable insights for drug optimizations. Cumulatively, this progress is continually refining our approaches to drug safety evaluation and personalized medicine.

An In Silico Platform to Predict Cardiotoxicity Risk of Anti-tumor Drug Combination with hiPSC-CMs Based In Vitro Study

OBJECTIVE

Antineoplastic agent-induced systolic dysfunction is a major reason for interruption of anticancer treatment. Although targeted anticancer agents infrequently cause systolic dysfunction, their combinations with chemotherapies remarkably increase the incidence. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a potent in vitro model to assess cardiovascular safety. However, quantitatively predicting the reduction of ejection fraction based on hiPSC-CMs is challenging due to the absence of the body's regulatory response to cardiomyocyte injury.

METHODS

Here, we developed and validated an in vitro-in vivo translational platform to assess the reduction of ejection fraction induced by antineoplastic drugs based on hiPSC-CMs. The translational platform integrates drug exposure, drug-cardiomyocyte interaction, and systemic response. The drug-cardiomyocyte interaction was implemented as a mechanism-based toxicodynamic (TD) model, which was then integrated into a quantitative system pharmacology-physiological-based pharmacokinetics (QSP-PBPK) model to form a complete translational platform. The platform was validated by comparing the model-predicted and clinically observed incidence of doxorubicin and trastuzumab-induced systolic dysfunction.

RESULTS

A total of 33,418 virtual patients were incorporated to receive doxorubicin and trastuzumab alone or in combination. For doxorubicin, the QSP-PBPK-TD model successfully captured the overall trend of systolic dysfunction incidences against the cumulative doses. For trastuzumab, the predicted incidence interval was 0.31-2.7% for single-agent treatment and 0.15-10% for trastuzumab-doxorubicin sequential treatment, covering the observations in clinical reports (0.50-1.0% and 1.5-8.3%, respectively).

CONCLUSIONS

In conclusion, the in vitro-in vivo translational platform is capable of predicting systolic dysfunction incidence almost merely depend on hiPSC-CMs, which could facilitate optimizing the treatment protocol of antineoplastic agents.

Quantitative Systems Toxicology Identifies Independent Mechanisms for Hepatotoxicity and Bilirubin Elevations Due to AKR1C3 Inhibitor BAY1128688

BAY1128688 is a selective inhibitor of AKR1C3, investigated recently in a trial that was prematurely terminated due to drug-induced liver injury. These unexpected observations prompted use of the quantitative systems toxicology model, DILIsym, to determine possible mechanisms of hepatotoxicity. Using mechanistic in vitro toxicity data as well as clinical exposure data, DILIsym predicted the potential for BAY1128688 to cause liver toxicity (elevations in serum alanine aminotransferase (ALT)) and elevations in serum bilirubin. Initial simulations overpredicted hepatotoxicity and bilirubin elevations, so the BAY1128688 representation within DILIsym underwent optimization. The liver partition coefficient Kp was altered to align simulated bilirubin elevations with those observed clinically. Altering the mode of bile acid canalicular and basolateral efflux inhibition was necessary to accurately predict ALT elevations. Optimization results support that bilirubin elevations observed early during treatment are due to altered bilirubin metabolism and transporter inhibition, which is independent of liver injury. The modeling further supports that on-treatment ALT elevations result from inhibition of bile acid transporters, particularly the bile salt excretory pump, leading to accumulation of toxic bile acids. The predicted dose-dependent intrinsic hepatotoxicity may increase patient susceptibility to an adaptive immune response, accounting for ALT elevations observed after completion of treatment. These BAY1128688 simulations provide insight into the mechanisms behind hepatotoxicity and bilirubin elevations and may inform the potential risk posed by future compounds.

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

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

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

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

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

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

Deciphering the Underlying Mechanisms of Formula Le-Cao-Shi Against Liver Injuries by Integrating Network Pharmacology, Metabonomics, and Experimental Validation

Le-Cao-Shi (LCS) has long been used as a folk traditional Chinese medicine formula against liver injuries, whereas its pharmacological mechanisms remain elusive. Our study aims to investigate the underlying mechanism of LCS in treating liver injuries via integrated network pharmacology, metabonomics, and experimental validation. By network pharmacology, 57 compounds were screened as candidate compounds based on ADME parameters from the LCS compound bank (213 compounds collected from the literature of three single herbs). According to online compound–target databases, the aforementioned candidate compounds were predicted to target 87 potential targets related to liver injuries. More than 15 pathways connected with these potential targets were considered vital pathways in collectively modulating liver injuries, which were found to be relevant to cancer, xenobiotic metabolism by cytochrome P450 enzymes, bile secretion, inflammation, and antioxidation. Metabonomics analysis by using the supernatant of the rat liver homogenate with UPLC-Q-TOF/MS demonstrated that 18 potential biomarkers could be regulated by LCS, which was closely related to linoleic acid metabolism, glutathione metabolism, cysteine and methionine metabolism, and glycerophospholipid metabolism pathways. Linoleic acid metabolism and glutathione metabolism pathways were two key common pathways in both network pharmacology and metabonomics analysis. In ELISA experiments with the CCl₄-induced rat liver injury model, LCS was found to significantly reduce the levels of inflammatory parameters, decrease liver malondialdehyde (MDA) levels, and enhance the activities of hepatic antioxidant enzymes, which validated that LCS could inhibit liver injuries through anti-inflammatory property and by suppressing lipid peroxidation and improving the antioxidant defense system. Our work could provide new insights into the underlying pharmacological mechanisms of LCS against liver injuries, which is beneficial for its further investigation and modernization.

Quantitative Systems Toxicology and Drug Development: The DILIsym Experience

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

OUP accepted manuscript

Calcitonin gene-related peptide (CGRP) signaling inhibitors have shown efficacy in both the acute and preventive treatment of migraine. Telcagepant, a first-generation CGRP receptor antagonist, was effective but failed in clinical trials due to hepatotoxicity. Subsequently, although 4 next-generation CGRP receptor antagonists (rimegepant, zavegepant, atogepant, and ubrogepant) were being advanced into late-stage clinical trials, due to telcagepant’s failure, more confidence in the liver safety of these compounds was needed. DILIsym v6A, a quantitative systems toxicology (QST) model of drug-induced liver injury (DILI), was used to model all 5 compounds and thus to compare the 4 next-generation CGRP receptor antagonists to telcagepant. In vitro experiments were performed to measure the potential for each compound to inhibit bile acid transporters, produce oxidative stress, and cause mitochondrial dysfunction. Physiologically based pharmacokinetic models were produced for each compound in order to appropriately estimate liver exposure. DILIsym predicted clinical elevations of liver enzymes and bilirubin for telcagepant, correctly predicting the observed DILI liability of the first-generation compound. By contrast, DILIsym predicted that each of the 4 next-generation compounds would be significantly less likely to cause DILI than telcagepant. Subsequent clinical trials have validated these predictions for each of the 4 compounds, and all 3 of the compounds submitted to FDA to date (rimegepant, ubrogepant, and atogepant) have since been approved by the FDA with no warning for hepatotoxicity. This work demonstrates the potential for QST modeling to prospectively differentiate between hepatotoxic and nonhepatotoxic molecules within the same class.

Discovery of an Oxycyclohexyl Acid Lysophosphatidic Acid Receptor 1 (LPA1) Antagonist BMS-986278 for the Treatment of Pulmonary Fibrotic Diseases

The oxycyclohexyl acid BMS-986278 (33) is a potent lysophosphatidic acid receptor 1 (LPA₁) antagonist, with a human LPA₁ K_b of 6.9 nM. The structure-activity relationship (SAR) studies starting from the LPA₁ antagonist clinical compound BMS-986020 (1), which culminated in the discovery of 33, are discussed. The detailed in vitro and in vivo preclinical pharmacology profiles of 33, as well as its pharmacokinetics/metabolism profile, are described. On the basis of its in vivo efficacy in rodent chronic lung fibrosis models and excellent overall ADME (absorption, distribution, metabolism, excretion) properties in multiple preclinical species, 33 was advanced into clinical trials, including an ongoing Phase 2 clinical trial in patients with lung fibrosis (NCT04308681).

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

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

Reproducing human and cross-species drug toxicities using a Liver-Chip

Nonclinical rodent and nonrodent toxicity models used to support clinical trials of candidate drugs may produce discordant results or fail to predict complications in humans, contributing to drug failures in the clinic. Here, we applied microengineered Organs-on-Chips technology to design a rat, dog, and human Liver-Chip containing species-specific primary hepatocytes interfaced with liver sinusoidal endothelial cells, with or without Kupffer cells and hepatic stellate cells, cultured under physiological fluid flow. The Liver-Chip detected diverse phenotypes of liver toxicity, including hepatocellular injury, steatosis, cholestasis, and fibrosis, and species-specific toxicities when treated with tool compounds. A multispecies Liver-Chip may provide a useful platform for prediction of liver toxicity and inform human relevance of liver toxicities detected in animal studies to better determine safety and human risk.

Liver toxicity of macrolide antibiotics in zebrafish

Macrolide antibiotics (macrolides) are among the most commonly prescribed antibiotics worldwide and are used for a wide range of infections, but macrolides also expose people to the risk of adverse events include hepatotoxicity. Here, we report the liver toxicity of macrolides with different structures in zebrafish. The absorption, distribution, metabolism, excretion and toxicology (ADMET) parameters of macrolide compounds were predicted and contrasted by utilizing in silico analysis. Fluorescence imaging and Oil Red O stain assays showed all the tested macrolide drugs induced liver degeneration, changed liver size and liver steatosis in larval zebrafish. Through RNA-seq analysis, we found seven co-regulated differentially expressed genes (co-DEGs) associated with metabolism, apoptosis and immune system biological processes, and two co-regulated significant pathways including amino sugar and nucleotide sugar metabolism and apoptosis signaling pathway. We found that only fosab of seven co-DEGs was in the two co-regulated significant pathways. fosab encoded proto-oncogene c-Fos, which was closely associated with liver diseases. The whole-mount in situ hybridization showed high transcription of c-Fos induced by macrolide compounds mainly in the liver region of zebrafish larvae. Cell Counting Kit-8 (CCK-8) and lactate dehydrogenase (LDH) leakage assays revealed that macrolides exerts significant cytotoxic effects on L02 cells. qRT-PCR and western blot analysis demonstrated macrolides also promoted human c-Fos expression in L02 cells. The c-Fos overexpression significantly reduced cell viability by using CCK-8 assay. These data indicate that hepatotoxicity induced by macrolides may be correlated with c-Fos expression activated by these compounds. This study may provide a biomarker for the further investigations on the mechanism of hepatotoxicity induced by macrolide drugs with different structures, and extend our understanding for improving rational clinical application of macrolides.

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

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

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

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

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

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

Comparison of the Hepatotoxic Potential of Two Treatments for Autosomal-Dominant Polycystic Kidney DiseaseUsing Quantitative Systems Toxicology Modeling

Purpose

Autosomal-dominant polycystic kidney disease (ADPKD) is an orphan disease with few current treatment options. The vasopressin V₂ receptor antagonist tolvaptan is approved in multiple countries for the treatment of ADPKD, however its use is associated with clinically significant drug-induced liver injury.

Methods

In prior studies, the potential for hepatotoxicity of tolvaptan was correctly predicted using DILIsym®, a quantitative systems toxicology (QST) mathematical model of drug-induced liver injury. In the current study, we evaluated lixivaptan, another proposed ADPKD treatment and vasopressin V₂ receptor antagonist, using DILIsym®. Simulations were conducted that assessed the potential for lixivaptan and its three main metabolites to cause hepatotoxicity due to three injury mechanisms: bile acid accumulation, mitochondrial dysfunction, and oxidative stress generation. Results of these simulations were compared to previously published DILIsym results for tolvaptan.

Results

No ALT elevations were predicted to occur at the proposed clinical dose for lixivaptan, in contrast to previously published simulation results for tolvaptan. As such, lixivaptan was predicted to have a markedly lower risk of hepatotoxicity compared to tolvaptan with respect to the hepatotoxicity mechanisms represented in DILIsym.

Conclusions

These results demonstrate the potential for using QST methods to differentiate drugs in the same class for their potential to cause hepatotoxicity.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2726-0) contains supplementary material, which is available to authorized users.

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

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

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

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

Can Bile Salt Export Pump Inhibition Testing in Drug Discovery and Development Reduce Liver Injury Risk? An International Transporter Consortium Perspective

Bile salt export pump (BSEP) inhibition has emerged as an important mechanism that may contribute to the initiation of human drug‐induced liver injury (DILI). Proactive evaluation and understanding of BSEP inhibition is recommended in drug discovery and development to aid internal decision making on DILI risk. BSEP inhibition can be quantified using in vitro assays. When interpreting assay data, it is important to consider in vivo drug exposure. Currently, this can be undertaken most effectively by consideration of total plasma steady state drug concentrations (C_ss,plasma). However, because total drug concentrations are not predictive of pharmacological effect, the relationship between total exposure and BSEP inhibition is not causal. Various follow‐up studies can aid interpretation of in vitro BSEP inhibition data and may be undertaken on a case‐by‐case basis. BSEP inhibition is one of several mechanisms by which drugs may cause DILI, therefore, it should be considered alongside other mechanisms when evaluating possible DILI risk.

Blood-Bile Barrier: Morphology, Regulation, and Pathophysiology

The term blood-bile barrier (BBlB) refers to the physical structure within a hepatic lobule that compartmentalizes and hence segregates sinusoidal blood from canalicular bile. Thus, this barrier provides physiological protection in the liver, shielding the hepatocytes from bile toxicity and restricting the mixing of blood and bile. BBlB is primarily composed of tight junctions; however, adherens junction, desmosomes, gap junctions, and hepatocyte bile transporters also contribute to the barrier function of the BBlB. Recent findings also suggest that disruption of BBlB is associated with major hepatic diseases characterized by cholestasis and aberrations in BBlB thus may be a hallmark of many chronic liver diseases. Several molecular signaling pathways have now been shown to play a role in regulating the structure and function and eventually contribute to regulation of the BBlB function within the liver. In this review, we will discuss the structure and function of the BBlB, summarize the methods to assess the integrity and function of BBlB, discuss the role of BBlB in liver pathophysiology, and finally, discuss the mechanisms of BBlB regulation. Collectively, this review will demonstrate the significance of the BBlB in both liver homeostasis and hepatic dysfunction.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

In-silico approach for drug induced liver injury prediction: Recent advances

Drug induced liver injury (DILI) is the prime cause of liver disfunction which may lead to mild non-specific symptoms to more severe signs like hepatitis, cholestasis, cirrhosis and jaundice. Not only the prescription medications, but the consumption of herbs and health supplements have also been reported to cause these adverse reactions resulting into high mortality rates and post marketing withdrawal of drugs. Due to the continuously increasing DILI incidences in recent years, robust prediction methods with high accuracy, specificity and sensitivity are of priority. Bioinformatics is the emerging field of science that has been used in the past few years to explore the mechanisms of DILI. The major emphasis of this review is the recent advances of in silico tools for the diagnostic and therapeutic interventions of DILI. These tools have been developed and widely used in the past few years for the prediction of pathways induced from both hepatotoxic as well as hepatoprotective Chinese drugs and for the identification of DILI specific biomarkers for prognostic purpose. In addition to this, advanced machine learning models have been developed for the classification of drugs into DILI causing and non-DILI causing. Moreover, development of 3 class models over 2 class offers better understanding of multi-class DILI risks and at the same time providing authentic prediction of toxicity during drug designing before clinical trials.

Maximizing the impact of microphysiological systems with in vitro-in vivo translation

Microphysiological systems (MPS) hold promise for improving therapeutic drug approval rates by providing more physiological, human-based, in vitro assays for preclinical drug development activities compared to traditional in vitro and animal models. Here, we first summarize why MPSs are needed in pharmaceutical development, and examine how MPS technologies can be utilized to improve preclinical efforts. We then provide the perspective that the full impact of MPS technologies will be realized only when robust approaches for in vitro-in vivo (MPS-to-human) translation are developed and utilized, and explain how the burgeoning field of quantitative systems pharmacology (QSP) can fill that need.

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

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

Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies

Adverse drug reactions, particularly those that result in drug-induced liver injury (DILI), are a major cause of drug failure in clinical trials and drug withdrawals. Hepatotoxicity-mediated drug attrition occurs despite substantial investments of time and money in developing cellular assays, animal models, and computational models to predict its occurrence in humans. Underperformance in predicting hepatotoxicity associated with drugs and drug candidates has been attributed to existing gaps in our understanding of the mechanisms involved in driving hepatic injury after these compounds perfuse and are metabolized by the liver. Herein we assess in vitro, in vivo (animal), and in silico strategies used to develop predictive DILI models. We address the effectiveness of several two- and three-dimensional in vitro cellular methods that are frequently employed in hepatotoxicity screens and how they can be used to predict DILI in humans. We also explore how humanized animal models can recapitulate human drug metabolic profiles and associated liver injury. Finally, we highlight the maturation of computational methods for predicting hepatotoxicity, the untapped potential of artificial intelligence for improving in silico DILI screens, and how knowledge acquired from these predictions can shape the refinement of experimental methods.

Intravital Multiphoton Microscopy with Fluorescent Bile Salts in Rats as an In Vivo Biomarker for Hepatobiliary Transport Inhibition

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it mediates the elimination of monovalent bile salts into the bile. Inhibition of BSEP is considered a susceptibility factor for drug-induced liver injury that often goes undetected during nonclinical testing. Although in vitro assays exist for screening BSEP inhibition, a reliable and specific method for confirming Bsep inhibition in vivo would be a valuable follow up to a BSEP screening strategy, helping to put a translatable context around in vitro inhibition data, incorporating processes such as metabolism, protein binding, and other exposure properties that are lacking in most in vitro BSEP models. Here, we describe studies in which methods of quantitative intravital microscopy were used to identify dose-dependent effects of two known BSEP/Bsep inhibitors, 2-[4-[4-(butylcarbamoyl)-2-[(2,4-dichlorophenyl)sulfonylamino]phenoxy]-3-methoxyphenyl]acetic acid (AMG-009) and bosentan, on hepatocellular transport of the fluorescent bile salts cholylglycyl amidofluorescein and cholyl-lysyl-fluorescein in rats. Results of these studies demonstrate that the intravital microscopy approach is capable of detecting Bsep inhibition at drug doses well below those found to increase serum bile acid levels, and also indicate that basolateral efflux transporters play a significant role in preventing cytosolic accumulation of bile acids under conditions of Bsep inhibition in rats. Studies of this kind can both improve our understanding of exposures needed to inhibit Bsep in vivo and provide unique insights into drug effects in ways that can improve our ability interpret animal studies for the prediction of human drug hepatotoxicity.

Role of Glucuronidation and P450 Oxidation in the Bioactivation of Bromfenac

Bromfenac is a nonsteroidal anti-inflammatory drug that was approved in the United States in 1997. It was withdrawn from clinical use less than one year later, in 1998, due to hepatotoxicity. We investigate the potential of bromfenac to be metabolized to reactive intermediates to further the current understanding of bromfenac bioactivation. Incubations were conducted with hepatocytes and human, rat, and cynomolgus liver microsomes fortified with cofactors and N-acetylcysteine. One thioether adduct of hydroxylated bromfenac and three thioether adducts of hydroxylated bromfenac indolinone were detected in extracts following incubations in liver microsomes fortified with NADPH and UDPGA. These findings demonstrate a bioactivation pathway for bromfenac and contribute to the body of evidence that could advance the understanding of the toxicity associated with bromfenac.

In vitro to in vivo extrapolation for high throughput prioritization and decision making

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Clearance and Liver Partitioning of OATP and OCT Substrates in Cynomolgus Monkeys

In the present investigations, we evaluate in vitro hepatocyte uptake and partitioning for the prediction of in vivo clearance and liver partitioning. Monkeys were intravenously co-dosed with rosuvastatin and bosentan, substrates of the organic anion transporting polypeptides (OATPs), and metformin, a substrate of organic cation transporter 1 (OCT1). Serial plasma and liver samples were collected over time. Liver and plasma unbound fraction was determined using equilibrium dialysis. In vivo unbound partitioning (Kp_u,u) for rosuvastatin, bosentan, and metformin, calculated from total concentrations in the liver and plasma, were 243, 553, and 15, respectively. A physiologically based pharmacokinetic monkey model that incorporates active and passive hepatic uptake was developed to fit plasma and liver concentrations. In addition, a two-compartment model was used to fit in vitro hepatic uptake curves in suspended monkey hepatocyte to determine active uptake, passive diffusion, and intracellular unbound fraction parameters. At steady-state in the model, in vitro Kp_u,u was determined. The results demonstrated that in vitro values under-predicted in vivo active uptake for rosuvastatin, bosentan, and metformin by 6.7-, 28-, and 1.5-fold, respectively, while passive diffusion was over-predicted. In vivo Kp_u,u values were under-predicted from in vitro data by 30-, 79-, and 3-fold. In conclusion, active uptake and liver partitioning in monkeys for OATP substrates were greatly under-predicted from in vitro hepatocyte uptake, while OCT-mediated uptake and partitioning scaled reasonably well from in vitro, demonstrating substrate- and transporter-dependent scaling factors. The combination of in vitro experimental and modeling approaches proved useful for assessing prediction of in vivo intracellular partitioning.

Drug-induced liver injury: recent advances in diagnosis and risk assessment

Idiosyncratic drug-induced liver injury (IDILI) is a rare but potentially severe adverse drug reaction that should be considered in patients who develop laboratory criteria for liver injury secondary to the administration of a potentially hepatotoxic drug. Although currently used liver parameters are sensitive in detecting DILI, they are neither specific nor able to predict the patient's subsequent clinical course. Genetic risk assessment is useful mainly due to its high negative predictive value, with several human leucocyte antigen alleles being associated with DILI. New emerging biomarkers which could be useful in assessing DILI include total keratin18 (K18) and caspase-cleaved keratin18 (ccK18), macrophage colony-stimulating factor receptor 1, high mobility group box 1 and microRNA-122. From the numerous in vitro test systems that are available, monocyte-derived hepatocytes generated from patients with DILI show promise in identifying the DILI-causing agent from among a panel of coprescribed drugs. Several computer-based algorithms are available that rely on cumulative scores of known risk factors such as the administered dose or potential liabilities such as mitochondrial toxicity, inhibition of the bile salt export pump or the formation of reactive metabolites. A novel DILI cluster score is being developed which predicts DILI from multiple complimentary cluster and classification models using absorption-distribution-metabolism-elimination-related as well as physicochemical properties, diverse substructural descriptors and known structural liabilities. The provision of more advanced scientific and regulatory guidance for liver safety assessment will depend on validating the new diagnostic markers in the ongoing DILI registries, biobanks and public-private partnerships.

Refining Liver Safety Risk Assessment: Application of Mechanistic Modeling and Serum Biomarkers to Cimaglermin Alfa (GGF2) Clinical Trials

Cimaglermin alfa (GGF2) is a recombinant human protein growth factor in development for heart failure. Phase I trials were suspended when two cimaglermin alfa‐treated subjects experienced concomitant elevations in serum aminotransferases and total bilirubin, meeting current US Food and Drug Administration criteria for a serious liver safety signal (i.e., “Hy's Law”). We assayed mechanistic biomarkers in archived clinical trial serum samples which confirmed the hepatic origin of the aminotransferase elevations in these two subjects and identified apoptosis as the major mode of hepatocyte death. Using a mathematical model of drug‐induced liver injury (DILIsym) and a simulated population, we estimated that the maximum hepatocyte loss in these two subjects was <13%, which would not result in liver dysfunction sufficient to significantly increase serum bilirubin levels. We conclude that the two subjects should not be considered Hy's Law cases and that mechanistic biomarkers and modeling can aid in refining liver safety risk assessment in clinical trials.

Evaluation of New Chemical Entities as Substrates of Liver Transporters in the Pharmaceutical Industry: Response to Regulatory Requirements and Future Steps

This article discusses the evaluation of drug candidates as hepatic transporter substrates. Recently, research on the applications of hepatic transporters in the pharmaceutical industry has improved to meet the requirements of the regulatory guidelines for the evaluation of drug interactions. To identify the risk of transporter-mediated drug-drug interactions at an early stage of drug development, we used a strategy of reviewing the in vivo animal pharmacokinetics and tissue distribution data obtained in the discovery stage together with the in vitro data obtained for regulatory submission. In the context of nonclinical evaluation of new chemical entities as medicines, we believe that transporter studies are emerging as a key strategy to predict their pharmacological and toxicological effects. In combination with the recent progress in systems approaches, the estimation of effective concentrations in the target tissues, by using mathematical models to describe the transporter-mediated distribution and elimination, has enabled us to identify promising compounds for clinical development at the discovery stage.

Pre-clinical and clinical investigations of metabolic zonation in liver diseases: The potential of microphysiology systems

The establishment of metabolic zonation within a hepatic lobule ascribes specific functions to hepatocytes based on unique, location-dependent gene expression patterns. Recently, there have been significant developments in the field of metabolic liver zonation. A little over a decade ago, the role of β-catenin signaling was identified as a key regulator of gene expression and function in pericentral hepatocytes. Since then, additional molecules have been identified that regulate the pattern of Wnt/β-catenin signaling within a lobule and determine gene expression and function in other hepatic zones. Currently, the molecular basis of metabolic zonation in the liver appears to be a 'push and pull' between signaling pathways. Such compartmentalization not only provides an efficient assembly line for hepatocyte functions but also can account for restricting the initial hepatic damage and pathology from some hepatotoxic drugs to specific zones, possibly enabling effective regeneration and restitution responses from unaffected cells. Careful analysis and experimentation have also revealed that many pathological conditions in the liver lobule are spatially heterogeneous. We will review current research efforts that have focused on examination of the role and regulation of such mechanisms of hepatocyte adaptation and repair. We will discuss how the pathological organ-specific microenvironment affects cell signaling and metabolic liver zonation, especially in steatosis, viral hepatitis, and hepatocellular carcinoma. We will discuss how the use of new human microphysiological platforms will lead to a better understanding of liver disease progression, diagnosis, and therapies. In conclusion, we aim to provide insights into the role and regulation of metabolic zonation and function using traditional and innovative approaches. Impact statement Liver zonation of oxygen tension along the liver sinusoids has been identified as a critical liver microenvironment that impacts specific liver functions such as intermediary metabolism of amino acids, lipids, and carbohydrates, detoxification of xenobiotics and as sites for initiation of liver diseases. To date, most information on the role of zonation in liver disease including, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC) have been obtained from animal models. It is now possible to complement animal studies with human liver, microphysiology systems (MPS) containing induced pluripotent stem cells engineered to create disease models where it is also possible to control the in vitro liver oxygen microenvironment to define the role of zonation on the mechanism(s) of disease progression. The field now has the tools to investigate human liver disease progression, diagnosis, and therapeutic development.

Predicting Drug-Induced Cholestasis with the Help of Hepatic Transporters-An in Silico Modeling Approach

Cholestasis represents one out of three types of drug induced liver injury (DILI), which comprises a major challenge in drug development. In this study we applied a two-class classification scheme based on k-nearest neighbors in order to predict cholestasis, using a set of 93 two-dimensional (2D) physicochemical descriptors and predictions of selected hepatic transporters' inhibition (BSEP, BCRP, P-gp, OATP1B1, and OATP1B3). In order to assess the potential contribution of transporter inhibition, we compared whether the inclusion of the transporters' inhibition predictions contributes to a significant increase in model performance in comparison to the plain use of the 93 2D physicochemical descriptors. Our findings were in agreement with literature findings, indicating a contribution not only from BSEP inhibition but a rather synergistic effect deriving from the whole set of transporters. The final optimal model was validated via both 10-fold cross validation and external validation. It performs quite satisfactorily resulting in 0.686 ± 0.013 for accuracy and 0.722 ± 0.014 for area under the receiver operating characteristic curve (AUC) for 10-fold cross-validation (mean ± standard deviation from 50 iterations).

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

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

Functional human induced hepatocytes (hiHeps) with bile acid synthesis and transport capacities: A novel in vitro cholestatic model

Drug-induced cholestasis is a leading cause of drug withdrawal. However, the use of primary human hepatocytes (PHHs), the gold standard for predicting cholestasis in vitro, is limited by their high cost and batch-to-batch variability. Mature hepatocyte characteristics have been observed in human induced hepatocytes (hiHeps) derived from human fibroblast transdifferentiation. Here, we evaluated whether hiHeps could biosynthesize and excrete bile acids (BAs) and their potential as PHH alternatives for cholestasis investigations. Quantitative real-time PCR (qRT-PCR) and western blotting indicated that hiHeps highly expressed BA synthases and functional transporters. Liquid chromatography tandem mass spectrometry (LC-MS/MS) showed that hiHeps produced normal intercellular unconjugated BAs but fewer conjugated BAs than human hepatocytes. When incubated with representative cholestatic agents, hiHeps exhibited sensitive drug-induced bile salt export pump (BSEP) dysfunction, and their response to cholestatic agent-mediated cytotoxicity correlated well with that of PHHs (r² = 0.8032). Deoxycholic acid (DCA)-induced hepatotoxicity in hiHeps was verified by elevated aspartate aminotransferase (AST) and γ-glutamyl-transferase (γ-GT) levels. Mitochondrial damage and cell death suggested DCA-induced toxicity in hiHeps, which were attenuated by hepatoprotective drugs, as in PHHs. For the first time, hiHeps were reported to biosynthesize and excrete BAs, which could facilitate predicting cholestatic hepatotoxicity and screening potential therapeutic drugs against cholestasis.

The role of quantitative systems pharmacology modeling in the prediction and explanation of idiosyncratic drug-induced liver injury

Idiosyncratic drug-induced liver injury (iDILI) is a serious concern in drug development. The rarity and multifactorial nature of iDILI makes it difficult to predict and explain. Recently, human leukocyte antigen (HLA) allele associations have provided strong support for a role of an adaptive immune response in the pathogenesis of many iDILI cases; however, it is likely that an adaptive immune attack requires several preceding events. Quantitative systems pharmacology (QSP), an in silico modeling technique that leverages known physiology and the results of in vitro experiments in order to make predictions about how drugs affect biological processes, is proposed as a potentially useful tool for predicting and explaining critical events that likely precede immune-mediated iDILI, as well as the immune attack itself. DILIsym, a QSP platform for drug-induced liver injury, has demonstrated success in predicting the presence of delayed hepatocellular stress events that likely precede the iDILI cascade, and has successfully predicted hepatocellular stress likely underlying iDILI attributed to troglitazone and tolvaptan. The incorporation of a model of the adaptive immune system into DILIsym would represent and important advance. In summary, QSP methods can play a key role in the future prediction and understanding of both immune-mediated and non-immune-mediated iDILI.

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

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