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

Cellular and Mitochondrial Toxicity of Tolcapone, Entacapone, and New Nitrocatechol Derivatives

Nitrocatechols are the standard pharmacophore to develop potent tight-binding inhibitors of catechol O-methyltransferase (COMT), which can be used as coadjuvant drugs to manage Parkinson's disease. Tolcapone is the most potent drug of this class, but it has raised safety concerns due to its potential to induce liver damage. Tolcapone-induced hepatotoxicity has been attributed to the nitrocatechol moiety; however, other nitrocatechol-based COMT inhibitors, such as entacapone, are safe and do not damage the liver. There is a knowledge gap concerning which mechanisms and chemical properties govern the toxicity of nitrocatechol-based COMT inhibitors. Using a vast array of cell-based assays, we found that tolcapone-induced toxicity is caused by direct interference with mitochondria that does not depend on bioactivation by P450. Our findings also suggest that (a) lipophilicity is a key property in the toxic potential of nitrocatechols; (b) the presence of a carbonyl group directly attached to the nitrocatechol ring seems to increase the reactivity of the molecule, and (c) the presence of cyano moiety in double bond stabilizes the reactivity decreasing the cytotoxicity. Altogether, the fine balance between lipophilicity and the chemical nature of the C1 substituents of the nitrocatechol ring may explain the difference in the toxicological behavior observed between tolcapone and entacapone.

Rescuing a Troubled Tolcapone with PEGylated PLGA Nanoparticles: Design, Characterization, and Hepatotoxicity Evaluation

Tolcapone is an orally active catechol-O-methyltransferase (COMT) inhibitor used as adjuvant therapy in Parkinson's disease. However, it has a highly hepatotoxic profile, as recognized by the U.S. Food and Drug Administration. As a possible solution, nanoscience brought us several tools in the development of new functional nanomaterials with tunable physicochemical properties, which can be part of a solution to solve several drawbacks, including drug's short half-life and toxicity. This work aims to use PEGylated poly(lactic-co-glycolic acid) (PLGA) nanoparticles as a stable carrier with lower hydrodynamic size and polydispersity to encapsulate tolcapone in order to overcome its therapeutic drawbacks. Using the nanoprecipitation method, tolcapone-loaded nanoparticles with a DLC% of 5.7% were obtained (EE% of 47.0%) and subjected to a lyophilization optimization process to obtain a final shelf-stable formulation. Six different cryoprotectants in concentrations up to 10% (w/v) were tested. A formulation of PLGA nanoparticles with 3% hydroxypropyl-β-cyclodextrin (HPβCD) as a cryoprotectant (PLGA-HP@Tolc), presenting sub-200 nm sizes and low polydispersity (PdI < 0.200) was selected. Cytotoxicity assays, namely, MTT and SRB, were used to study the metabolic activity and cell density of tolcapone and PLGA-HP@Tolc-treated cells. In both assays, a hepatocarcinoma cell line (HepG2) growing in glucose or glucose-free media (galactose-supplemented medium) was used. The results demonstrated that the treatment with the PLGA-HP@Tolc formulation led to a decrease in cytotoxicity in comparison to free tolcapone-treated cells in both media tested. Moreover, the elected formulation also counteracted ATP-depletion and excessive ROS production induced by tolcapone. The results suggest that HPβCD might have a dual function in the formulation: cryoprotectant and anticytotoxic agent, protecting cells from tolcapone-induced damage. Using an in vitro COMT inhibition assay, the PLGA-HP@Tolc formulation demonstrated to inhibit COMT as efficiently as free tolcapone. Overall, the results suggest that tolcapone-loaded PLGA NPs could be an interesting alternative to free tolcapone, demonstrating the same in vitro efficacy in inhibiting COMT but with a safer cytotoxic profile.

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.

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.

Relationship Between Gut Bacteria and Levodopa Metabolism

Parkinson's disease (PD) is one of the most common neurodegenerative diseases, characterized by the reduction of dopamine neurons in the substantia nigra. Levodopa, as a dopamine supplement, is the gold-standard therapeutic drug for PD. The metabolism of levodopa in the periphery not only decreases its bioavailability but also affects its efficacy. Thus, it is necessary to investigate how levodopa is metabolized. A growing number of studies have shown that intestinal bacteria, such as Enterococcus faecalis, Eggerthella lenta and Clostridium sporogenes, could metabolize levodopa in different ways. In addition, several pathways to reduce levodopa metabolism by gut microbiota were confirmed to improve levodopa efficacy. These pathways include aromatic amino acid decarboxylase (AADC) inhibitors, antibiotics, pH and (S)-α-fluoromethyltyrosine (AFMT). In this review, we have summarized the metabolic process of levodopa by intestinal bacteria and analyzed potential approaches to reduce the metabolism of levodopa by gut microbiota, thus improving the efficacy of levodopa.

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.

Machine Learning Models for Predicting Liver Toxicity

Liver toxicity is a major adverse drug reaction that accounts for drug failure in clinical trials and withdrawal from the market. Therefore, predicting potential liver toxicity at an early stage in drug discovery is crucial to reduce costs and the potential for drug failure. However, current in vivo animal toxicity testing is very expensive and time consuming. As an alternative approach, various machine learning models have been developed to predict potential liver toxicity in humans. This chapter reviews current advances in the development and application of machine learning models for prediction of potential liver toxicity in humans and discusses possible improvements to liver toxicity prediction.

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

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

Host bioenergetic parameters reveal cytotoxicity of anti-tuberculosis drugs undetected using conventional viability assays

High attrition rates in tuberculosis (TB) drug development have been largely attributed to safety, which is likely due to the use of endpoint assays measuring cell viability to detect drug cytotoxicity. In drug development for cancer, metabolic, and neurological disorders and for antibiotics, cytotoxicity is increasingly being assessed using extracellular flux (XF) analysis, which measures cellular bioenergetic metabolism in real time. Here, we adopt the XF platform to investigate the cytotoxicity of drugs currently used in TB treatment on the bioenergetic metabolism of HepG2 cells, THP-1 macrophages, and human monocyte-derived macrophages (hMDMs). We found that the XF analysis reveals earlier drug-induced effects on the cells’ bioenergetic metabolism prior to cell death, measured by conventional viability assays. Furthermore, each cell type has a distinct response to drug treatment, suggesting that more than one cell type should be considered to examine cytotoxicity in TB drug development. Interestingly, chemically unrelated drugs with different modes of action on Mycobacterium tuberculosis have similar effects on the bioenergetic parameters of the cells, thus discouraging the prediction of potential cytotoxicity based on chemical structure and mode of action of new chemical entities. The clustering of the drug-induced effects on the hMDM bioenergetic parameters are reflected in the clustering of the effects of the drugs on cytokine production in hMDMs, demonstrating concurrence between the effects of the drugs on the metabolism and functioning of the macrophages. These findings can be used as a benchmark to establish XF analysis as a new tool to assay cytotoxicity in TB drug development.

Targeting COVID-19 in Parkinson's Patients: Drugs Repurposed

The last couple of months have witnessed the world in a state of virtual standstill. The SARS-CoV-2 virus has overtaken the globe to economic and social lockdown. Many patients with COVID-19 have compromised immunity, especially in an aged population suffering from Parkinson 's disease (PD). Alteration in dopaminergic neurons and deficiency of dopamine in PD patients are the most common symptoms affecting 1% population above the age of 60 years. The compromised immune system and inflammatory manifestation in PD patients make them an easy target. The most common drugs under trial for COVID-19 are remdesivir, favipiravir, chloroquine and hydroxychloroquine, azithromycin along with adjunct drugs like amantadine with some monoclonal antibodies. Presently, clinically US FDA approved drugs in PD include Levodopa, catechol-O-methyl transferase (COMT) inhibitors, (Entacapone and Tolcapone), dopamine agonists (Bromocriptine, Ropinirole, Pramipexole, and Rotigotine), monoamine oxidase B (MAO-B) inhibitors (Selegiline and Rasagiline), amantadine and antimuscarinic drugs. The drugs have established mechanisms of action on PD patients with known pharmacodynamics and pharmacokinetic properties along with dose and adverse effects. Conclusion and relevance of this review focus on the drugs that can be tried on PD patients with SAR CoV-2 infection, in particular, amantadine that has been approved by all the developed countries as a common drug possessing both antiviral properties by downregulation of CTSL, lysosomal pathway disturbance and change in pH necessary to uncoat the viral proteins and anti- Parkinson properties. To deal with the significant prognostic adverse effect of SARS-CoV-2 on PD, the present-day treatment options, clinical presentation and various mechanisms are the need of the hour.

Inhibition of catechol-O-methyltransferase by natural pentacyclic triterpenes: structure-activity relationships and kinetic mechanism

Inhibitors of COMT are clinically used for the treatment of Parkinson's disease. Here, we report the first natural pentacyclic triterpenoid-type COMT inhibitors and their structure-activity relationships and inhibition mechanism. The most potent compounds were found to be oleanic acid, betulinic acid and celastrol with IC₅₀ values of 3.89-5.07 μM, that acted as mixed (uncompetitive plus non-competitive) inhibitors of COMT, representing a new skeleton of COMT inhibitor. Molecular docking suggested that they can specifically recognise and bind with the unique hydrophobic residues surrounding the catechol pocket. Furthermore, oleanic acid and betulinic acid proved to be less disruptive of mitochondrial membrane potential (MMP) compared to tolcapone, thus reducing the risk of liver toxicity. These findings could be used to produce an ideal lead compound and to guide synthetic efforts in generating related derivatives for further preclinical testing.

The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development

Human-derived in vitro models can provide high-throughput efficacy and toxicity data without a species gap in drug development. Challenges are still encountered regarding the full utilisation of massive data in clinical settings. The lack of translated methods hinders the reliable prediction of clinical outcomes. Therefore, in this study, in silico models were proposed to tackle these obstacles from in vitro to in vivo translation, and the current major cell culture methods were introduced, such as human-induced pluripotent stem cells (hiPSCs), 3D cells, organoids, and microphysiological systems (MPS). Furthermore, the role and applications of several in silico models were summarised, including the physiologically based pharmacokinetic model (PBPK), pharmacokinetic/pharmacodynamic model (PK/PD), quantitative systems pharmacology model (QSP), and virtual clinical trials. These credible translation cases will provide templates for subsequent in vitro to in vivo translation. We believe that synergising high-quality in vitro data with existing models can better guide drug development and clinical use.

Oxidative Stress in Drug-Induced Liver Injury (DILI): From Mechanisms to Biomarkers for Use in Clinical Practice

Idiosyncratic drug-induced liver injury (DILI) is a type of hepatic injury caused by an uncommon drug adverse reaction that can develop to conditions spanning from asymptomatic liver laboratory abnormalities to acute liver failure (ALF) and death. The cellular and molecular mechanisms involved in DILI are poorly understood. Hepatocyte damage can be caused by the metabolic activation of chemically active intermediate metabolites that covalently bind to macromolecules (e.g., proteins, DNA), forming protein adducts-neoantigens-that lead to the generation of oxidative stress, mitochondrial dysfunction, and endoplasmic reticulum (ER) stress, which can eventually lead to cell death. In parallel, damage-associated molecular patterns (DAMPs) stimulate the immune response, whereby inflammasomes play a pivotal role, and neoantigen presentation on specific human leukocyte antigen (HLA) molecules trigger the adaptive immune response. A wide array of antioxidant mechanisms exists to counterbalance the effect of oxidants, including glutathione (GSH), superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPX), which are pivotal in detoxification. These get compromised during DILI, triggering an imbalance between oxidants and antioxidants defense systems, generating oxidative stress. As a result of exacerbated oxidative stress, several danger signals, including mitochondrial damage, cell death, and inflammatory markers, and microRNAs (miRNAs) related to extracellular vesicles (EVs) have already been reported as mechanistic biomarkers. Here, the status quo and the future directions in DILI are thoroughly discussed, with a special focus on the role of oxidative stress and the development of new biomarkers.

Assessment of the impact of mitochondrial genotype upon drug-induced mitochondrial dysfunction in platelets derived from healthy volunteers

Mitochondrial DNA (mtDNA) is highly polymorphic and encodes 13 proteins which are critical to the production of ATP via oxidative phosphorylation. As mtDNA is maternally inherited and undergoes negligible recombination, acquired mutations have subdivided the human population into several discrete haplogroups. Mitochondrial haplogroup has been found to significantly alter mitochondrial function and impact susceptibility to adverse drug reactions. Despite these findings, there are currently limited models to assess the effect of mtDNA variation upon susceptibility to adverse drug reactions. Platelets offer a potential personalised model of this variation, as their anucleate nature offers a source of mtDNA without interference from the nuclear genome. This study, therefore, aimed to determine the effect of mtDNA variation upon mitochondrial function and drug-induced mitochondrial dysfunction in a platelet model. The mtDNA haplogroup of 383 healthy volunteers was determined using next-generation mtDNA sequencing (Illumina MiSeq). Subsequently, 30 of these volunteers from mitochondrial haplogroups H, J, T and U were recalled to donate fresh, whole blood from which platelets were isolated. Platelet mitochondrial function was tested at basal state and upon treatment with compounds associated with both mitochondrial dysfunction and adverse drug reactions, flutamide, 2-hydroxyflutamide and tolcapone (10–250 μM) using extracellular flux analysis. This study has demonstrated that freshly-isolated platelets are a practical, primary cell model, which is amenable to the study of drug-induced mitochondrial dysfunction. Specifically, platelets from donors of haplogroup J have been found to have increased susceptibility to the inhibition of complex I-driven respiration by 2-hydroxyflutamide. At a time when individual susceptibility to adverse drug reactions is not fully understood, this study provides evidence that inter-individual variation in mitochondrial genotype could be a factor in determining sensitivity to mitochondrial toxicants associated with costly adverse drug reactions.

Analytical methodologies for sensing catechol-O-methyltransferase activity and their applications

Mammalian catechol-O-methyltransferases (COMT) are an important class of conjugative enzymes, which play a key role in the metabolism and inactivation of catechol neurotransmitters, catechol estrogens and a wide range of endobiotics and xenobiotics that bear the catechol group. Currently, COMT inhibitors are used in combination with levodopa for the treatment of Parkinson's disease in clinical practice. The crucial role of COMT in human health has raised great interest in the development of more practical assays for highly selective and sensitive detection of COMT activity in real samples, as well as for rapid screening and characterization of COMT inhibitors as drug candidates. This review summarizes recent advances in analytical methodologies for sensing COMT activity and their applications. Several lists of biochemical assays for measuring COMT activity, including the probe substrates, along with their analytical conditions and kinetic parameters, are presented. Finally, the challenges and future perspectives in the field, such as visualization of COMT activity in vivo and in situ, are highlighted. Collectively, this review article overviews the practical assays for measuring COMT activities in complex biological samples, which will strongly facilitate the investigations on the relevance of COMT to human diseases and promote the discovery of COMT inhibitors via high-throughput screening.

Improved functional and histochemical outcomes in l-DOPA plus tolcapone treated VMAT2-deficient mice

Parkinson disease is typically treated with L-3,4-dihydroxyphenylalanine (or levodopa) co-prescribed with concentration stabilizers to prevent undesired motor fluctuations. However, the beneficial role of the chronic combined therapy on disease progression has not been thoroughly explored. We hypothesized that tolcapone, a catechol-O-methyl-transferase inhibitor, co-administered with levodopa may offer beneficial long-term disease-modifying effects through its dopamine stabilization actions. Here, we followed vesicular monoamine transporter 2-deficient and wild-type mice treated twice daily per os with vehicle, levodopa (20 mg/kg), tolcapone (15 mg/kg) or levodopa (12.5 mg/kg) + tolcapone (15 mg/kg) for 17 weeks. We assessed open field, bar test and rotarod performances at baseline and every 4th week thereafter, corresponding to OFF-medication weeks. Finally, we collected coronal sections from the frontal caudate-putamen and determined the reactivity level of dopamine transporter. Vesicular monoamine transporter 2-deficient mice responded positively to chronic levodopa + tolcapone intervention in the bar test during OFF-periods. Neither levodopa nor tolcapone interventions offered significant improvements on their own. Similarly, chronic levodopa + tolcapone intervention was associated with partially rescued dopamine transporter levels, whereas animals treated solely with levodopa or tolcapone did not present this effect. Interestingly, 4-month progression of bar test scores correlated significantly with dopamine-transporter-label density. Overall, we observed a moderate functional and histopathological improvement effect by chronic dopamine replacement when combined with tolcapone in vesicular monoamine transporter 2-deficient mice. Altogether, chronic stabilization of dopamine levels by catechol-O-methyl-transferase inhibition, besides its intended immediate actions, arises as a potential long-term beneficial approach during the progression of Parkinson disease.

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.

Mechanistic Investigations Support Liver Safety of Ubrogepant

Small-molecule calcitonin gene-related peptide (CGRP) receptor antagonists have demonstrated therapeutic efficacy for the treatment of migraine. However, previously investigated CGRP receptor antagonists, telcagepant and MK-3207, were discontinued during clinical development because of concerns about drug-induced liver injury. A subsequent effort to identify novel CGRP receptor antagonists less likely to cause hepatotoxicity led to the development of ubrogepant. The selection of ubrogepant, following a series of mechanistic studies conducted with MK-3207 and telcagepant, was focused on key structural modifications suggesting that ubrogepant was less prone to forming reactive metabolites than previous compounds. The potential for each drug to cause liver toxicity was subsequently assessed using a quantitative systems toxicology approach (DILIsym) that incorporates quantitative assessments of mitochondrial dysfunction, disruption of bile acid homeostasis, and oxidative stress, along with estimates of dose-dependent drug exposure to and within liver cells. DILIsym successfully modeled liver toxicity for telcagepant and MK-3207 at the dosing regimens used in clinical trials. In contrast, DILIsym predicted no hepatotoxicity during treatment with ubrogepant, even at daily doses up to 1000 mg (10-fold higher than the approved clinical dose of 100 mg). These predictions are consistent with clinical trial experience showing that ubrogepant has lower potential to cause hepatotoxicity than has been observed with telcagepant and MK-3207.

Multiparametric assessment of mitochondrial respiratory inhibition in HepG2 and RPTEC/TERT1 cells using a panel of mitochondrial targeting agrochemicals

Evidence is mounting for the central role of mitochondrial dysfunction in several pathologies including metabolic diseases, accelerated ageing, neurodegenerative diseases and in certain xenobiotic-induced organ toxicity. Assessing mitochondrial perturbations is not trivial and the outcomes of such investigations are dependent on the cell types used and assays employed. Here we systematically investigated the effect of electron transport chain (ETC) inhibitors on multiple mitochondrial-related parameters in two human cell types, HepG2 and RPTEC/TERT1. Cells were exposed to a broad range of concentrations of 20 ETC-inhibiting agrochemicals and capsaicin, consisting of inhibitors of NADH dehydrogenase (Complex I, CI), succinate dehydrogenase (Complex II, CII) and cytochrome bc1 complex (Complex III, CIII). A battery of tests was utilised, including viability assays, lactate production, mitochondrial membrane potential (MMP) and the Seahorse bioanalyser, which simultaneously measures extracellular acidification rate [ECAR] and oxygen consumption rate [OCR]. CI inhibitors caused a potent decrease in OCR, decreased mitochondrial membrane potential, increased ECAR and increased lactate production in both cell types. Twenty-fourhour exposure to CI inhibitors decreased viability of RPTEC/TERT1 cells and 3D spheroid-cultured HepG2 cells in the presence of glucose. CI inhibitors decreased 2D HepG2 viability only in the absence of glucose. CII inhibitors had no notable effects in intact cells up to 10 µM. CIII inhibitors had similar effects to the CI inhibitors. Antimycin A was the most potent CIII inhibitor, with activity in the nanomolar range. The proposed CIII inhibitor cyazofamid demonstrated a mitochondrial uncoupling signal in both cell types. The study presents a comprehensive example of a mitochondrial assessment workflow and establishes measurable key events of ETC inhibition.

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.

Partitioning of Catechol Derivatives in Lipid Membranes: Implications for Substrate Specificity to Catechol-O-methyltransferase

We have utilized multiparametric surface plasmon resonance and impendance-based quartz crystal microbalance instruments to study the distribution coefficients of catechol derivatives in cell model membranes. Our findings verify that the octanol-water partitioning coefficient is a poor descriptor of the total lipid affinity for small molecules which show limited lipophilicity in the octanol-water system. Notably, 3-methoxytyramine, the methylated derivative of the neurotransmitter dopamine, showed substantial affinity to the lipids despite its nonlipophilic nature predicted by octanol-water partitioning. The average ratio of distribution coefficients between 3-methoxytyramine and dopamine was 8.0. We also found that the interactions between the catechols and the membranes modeling the cell membrane outer leaflet are very weak, suggesting a mechanism other than the membrane-mediated mechanism of action for the neurotransmitters at the postsynaptic site. The average distribution coefficient for these membranes was one-third of the average value for pure phosphatidylcholine membranes, calculated using all compounds. In the context of our previous work, we further theorize that membrane-bound enzymes can utilize membrane headgroup partitioning to find their substrates. This could explain the differences in enzyme affinity between soluble and membrane-bound isoforms of catechol-O-methyltransferase, an essential enzyme in catechol metabolism.

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

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

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

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

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.

Drug-Induced Liver Injury: Biomarkers, Requirements, Candidates, and Validation

The hepatotoxicity of drugs is the main cause of drug withdrawal from the pharmaceutical market and interruption of the development of new molecules. Biomarkers are useful in several situations. In case of suspected drug-induced liver injury (DILI), biomarkers can be used to confirm liver damage, its severity, prognosis, confirm drug causality, or define the type of DILI. In this review, we will first present the currently used biomarkers and candidate biomarkers for the future. The current biomarkers are certainly very helpful including with the assistance of diagnostic method such the Roussel Uclaf Causality Assessment Method, but provide a limited information for the early detection of liver injury, the role of specific drug and the prediction of DILI. Some biomarkers are promising but they are not yet available for routine use. Studies are still needed to confirm their interest, particularly in comparison to Roussel Uclaf Causality Assessment Method.

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.

A Physiology-Based Model of Human Bile Acid Metabolism for Predicting Bile Acid Tissue Levels After Drug Administration in Healthy Subjects and BRIC Type 2 Patients

Drug-induced liver injury (DILI) is a matter of concern in the course of drug development and patient safety, often leading to discontinuation of drug-development programs or early withdrawal of drugs from market. Hepatocellular toxicity or impairment of bile acid (BA) metabolism, known as cholestasis, are the two clinical forms of DILI. Whole-body physiology-based modelling allows a mechanistic investigation of the physiological processes leading to cholestasis in man. Objectives of the present study were: (1) the development of a physiology-based model of the human BA metabolism, (2) population-based model validation and characterisation, and (3) the prediction and quantification of altered BA levels in special genotype subgroups and after drug administration. The developed physiology-based bile acid (PBBA) model describes the systemic BA circulation in humans and includes mechanistically relevant active and passive processes such as the hepatic synthesis, gallbladder emptying, transition through the gastrointestinal tract, reabsorption into the liver, distribution within the whole body, and excretion via urine and faeces. The kinetics of active processes were determined for the exemplary BA glycochenodeoxycholic acid (GCDCA) based on blood plasma concentration-time profiles. The robustness of our PBBA model was verified with population simulations of healthy individuals. In addition to plasma levels, the possibility to estimate BA concentrations in relevant tissues like the intracellular space of the liver enhance the mechanistic understanding of cholestasis. We analysed BA levels in various tissues of Benign Recurrent Intrahepatic Cholestasis type 2 (BRIC2) patients and our simulations suggest a higher susceptibility of BRIC2 patients toward cholestatic DILI due to BA accumulation in the liver. The effect of drugs on systemic BA levels were simulated for cyclosporine A (CsA). Our results confirmed the higher risk of DILI after CsA administration in healthy and BRIC2 patients. The presented PBBA model enhances our mechanistic understanding underlying cholestasis and drug-induced alterations of BA levels in blood and organs. The developed PBBA model might be applied in the future to anticipate potential risk of cholestasis in patients.

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.

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.

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

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

In vitro screening of cell bioenergetics to assess mitochondrial dysfunction in drug development

Drug-induced mitochondrial toxicity is considered as a common cellular mechanism that can induce a variety of organ toxicities. In the present manuscript, 17 in vitro mitochondrial toxic drugs, reported to induce Drug-Induced Liver Injury (DILI) and 6 non-mitochondrial toxic drugs (3 with DILI and 3 without DILI concern), were tested in HepG2 cells using a bioenergetics system. The 17 mitochondrial toxic drugs represent a wide variety of mitochondrial dysfunctions as well as DILI and include 4 pairs of drugs which are structurally related but associated with different DILI concerns in human. Cell bioenergetics were measured using the XF96e analyzer which simultaneous monitor oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), indirect measurements of oxidative phosphorylation and glycolysis, respectively. OCR associated with ATP production, maximal respiration, proton leak and spare respiratory capacity, were also assessed. Duplicate experiments resulted in a sensitivity of 82% (14/17) and specificity of 83% (5/6). The addition of stressors improved specificity considerably. Cut-offs, statistics and rules are clearly discussed to facilitate the use of this assay for screening purposes. Overall, the authors consider that this assay should be part of the battery of safety screening assays at early stages of drug development.

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.

Systems Pharmacology Model of Gastrointestinal Damage Predicts Species Differences and Optimizes Clinical Dosing Schedules

Gastrointestinal (GI) adverse events (AEs) are frequently dose limiting for oncology agents, requiring extensive clinical testing of alternative schedules to identify optimal dosing regimens. Here, we develop a translational mathematical model to predict these clinical AEs starting from preclinical GI toxicity data. The model structure incorporates known biology and includes stem cells, daughter cells, and enterocytes. Published data, including cellular numbers and division times, informed the system parameters for humans and rats. The drug‐specific parameters were informed with preclinical histopathology data from rats treated with irinotecan. The model fit the rodent irinotecan‐induced pathology changes well. The predicted time course of enterocyte loss in patients treated with weekly doses matched observed AE profiles. The model also correctly predicts a lower level of AEs for every 3 weeks (Q3W), as compared to the weekly schedule.

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.

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

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

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.

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.