Prediction of the Liver Safety Profile of a First-in-Class Myeloperoxidase Inhibitor Using Quantitative Systems Toxicology Modeling.

The novel myeloperoxidase inhibitor verdiperstat was developed as a treatment for neuroinflammatory and neurodegenerative diseases. During development, a computational prediction of verdiperstat liver safety was performed using DILIsym v8A, a quantitative systems toxicology (QST) model of liver safety.A physiologically-based pharmacokinetic (PBPK) model of verdiperstat was constructed in GastroPlus 9.8, and outputs for liver and plasma time courses of verdiperstat were input into DILIsym. In vitro experiments measured the likelihood that verdiperstat would inhibit mitochondrial function, inhibit bile acid transporters, and generate reactive oxygen species (ROS); these results were used as inputs into DILIsym, with two alternate sets of parameters used in order to fully explore the sensitivity of model predictions. Verdiperstat dosing protocols up to 600 mg BID were simulated for up to 48 weeks using a simulated population (SimPops) in DILIsym.Verdiperstat was predicted to be safe, with only very rare, mild liver enzyme increases as a potential possibility in highly sensitive individuals. Subsequent Phase 3 clinical trials found that ALT elevations in the verdiperstat treatment group were generally similar to those in the placebo group. This validates the DILIsym simulation results and demonstrates the power of QST modeling to predict the liver safety profile of novel therapeutics.

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.

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

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

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

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

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.

Mechanisms of hepatotoxicity associated with the monocyclic ß-lactam antibiotic BAL30072.

BAL30072 is a new monocyclic ß-lactam antibiotic under development which provides a therapeutic option for the treatment of severe infections caused by multi-drug-resistant Gram-negative bacteria. Despite the absence of liver toxicity in preclinical studies in rats and marmosets and in single dose clinical studies in humans, increased transaminase activities were observed in healthy subjects in multiple-dose clinical studies. We, therefore, initiated a comprehensive program to find out the mechanisms leading to hepatocellular injury using HepG2 cells (human hepatocellular carcinoma cell line), HepaRG cells (inducible hepatocytes derived from a human hepatic progenitor cell line), and human liver microtissue preparations. Our investigations demonstrated a concentration- and time-dependent reduction of the ATP content of BAL30072-treated HepG2 cells and liver microtissues. BAL30072 impaired oxygen consumption by HepG2 cells at clinically relevant concentrations, inhibited complexes II and III of the mitochondrial electron transport chain, increased the production of reactive oxygen species (ROS), and reduced the mitochondrial membrane potential. Furthermore, BAL 30072 impaired mitochondrial fatty acid metabolism, inhibited glycolysis, and was associated with hepatocyte apoptosis. Co-administration of N-acetyl-L-cysteine partially protected hepatocytes from BAL30072-mediated toxicity, underscoring the role of oxidative damage in the observed hepatocellular toxicity. In conclusion, BAL30072 is toxic for liver mitochondria and inhibits glycolysis at clinically relevant concentrations. Impaired hepatic mitochondrial function and inhibition of glycolysis can explain liver injury observed in human subjects receiving long-term treatment with this compound.

Linking physiology to toxicity using DILIsym®, a mechanistic mathematical model of drug-induced liver injury.

The drug development industry faces multiple challenges in the realization of safe effective drugs. Computational modeling approaches can be used to support these efforts. One approach, mechanistic modeling, is new to the realm of drug safety. It holds the promise of not only predicting toxicity for novel compounds, but also illuminating the mechanistic underpinnings of toxicity. To increase the scientific community's familiarity with mechanistic modeling in drug safety, this article seeks to provide perspective on the type of data used, how they are used and where they are lacking. Examples are derived from the development of DILIsym(®) software, a mechanistic model of drug-induced liver injury (DILI). DILIsym(®) simulates the mechanistic interactions and events from compound administration through the progression of liver injury and regeneration. Modeling mitochondrial toxicity illustrates the type and use of in vitro data to represent biological interactions, as well as insights on key differences between in vitro and in vivo conditions. Modeling bile acid toxicity illustrates a case in which the over-arching mechanism is well accepted, but many mechanistic details are lacking. Modeling was used to identify measurements predicted to strongly impact toxicity. Finally, modeling innate immune responses illustrates the importance of time-series data, particularly in the presence of positive and negative feedback loops, as well as the need for data from different animal species for better translation. These concepts are germane to most mechanistic models, although the details will vary. The use of mechanistic models is expected to improve the rational design of new drugs.

Quantitative Systems Toxicology Modeling Informed Safe Dose Selection of Emvododstat in Acute Myeloid Leukemia Patients.

Clinical investigation of emvododstat for the treatment of solid tumors was halted after two patients who were heavily treated with other anticancer therapies experienced drug-induced liver failure. However, preclinical investigations supported that emvododstat at lower doses might be effective in treating acute myeloid leukemia (AML) and against severe acute respiratory syndrome-coronavirus 2 as a dihydroorotate dehydrogenase inhibitor. Therefore, a quantitative systems toxicology model, DILIsym, was used to predict liver safety of the proposed dosing of emvododstat in AML clinical trials. In vitro mechanistic toxicity data of emvododstat and its desmethyl metabolite were integrated with in vivo exposure within DILIsym to predict hepatotoxicity responses in a simulated human population. DILIsym simulations predicted alanine aminotransferase elevations observed in prior emvododstat clinical trials in patients with solid tumors, but not in the prospective AML clinical trial with the proposed dosing regimens. Exposure predictions based on physiologically-based pharmacokinetic modeling suggested that reduced doses of emvododstat would produce clinical exposures that would be efficacious to treat AML. In the AML clinical trial, only eight patients experienced aminotransferase elevations, all of which were mild (grade 1), all resolving within a short period of time, and no patient showed symptoms of hepatotoxicity, confirming the prospective prediction of liver safety. Overall, retrospective DILIsym simulations adequately predicted the liver safety liabilities of emvododstat in solid tumor trials and prospective simulations predicted the liver safety of reduced doses in an AML clinical trial. The modeling was critical to enabling regulatory approval to proceed with the AML clinical trial wherein the predicted liver safety was confirmed.

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.

Mechanistic investigation of liver injury induced by BMS-932481, an experimental ɣ-secretase modulator.

BMS-932481 was designed to modulate ɣ-secretase activity to produce shorter and less amyloidogenic peptides, potentially averting liabilities associated with complete enzymatic inhibition. Although it demonstrated the intended pharmacology in the clinic, BMS-932481 unexpectedly caused drug-induced liver injury (DILI) in a multiple ascending dose study characterized by dose- and exposure-dependence, delayed onset manifestation, and a high incidence of hepatocellular damage. Retrospective studies investigating the disposition and probable mechanisms of toxicity of BMS-932481 are presented here. These included a mass balance study in bile-duct-cannulated rats and a metabolite profiling study in human hepatocytes, which together demonstrated oxidative metabolism followed by biliary elimination as the primary means of disposition. Additionally, minimal protein covalent binding in hepatocytes and lack of bioactivation products excluded reactive metabolite formation as a probable toxicological mechanism. However, BMS-932481 and 3 major oxidative metabolites were found to inhibit the bile salt export pump (BSEP) and multidrug resistance protein 4 (MRP4) in vitro. Considering human plasma concentrations, the IC50 values against these efflux transporters were clinically meaningful, particularly in the high dose cohort. Active uptake into human hepatocytes in vitro suggested the potential for hepatic levels of BMS-932481 to be elevated further above plasma concentrations, enhancing DILI risk. Conversely, measures of mitochondrial functional decline in hepatocytes treated with BMS-932481 were minimal or modest, suggesting limited contributions to DILI. Collectively, these findings suggested that repeat administration of BMS-932481 likely resulted in high hepatic concentrations of BMS-932481 and its metabolites, which disrupted bile acid transport via BSEP and MRP4, elevating serum biomarkers of liver injury.

An analysis of N-acetylcysteine treatment for acetaminophen overdose using a systems model of drug-induced liver injury.

N-acetylcysteine (NAC) is the treatment of choice for acetaminophen poisoning; standard 72-h oral or 21-h intravenous protocols are most frequently used. There is controversy regarding which protocol is optimal and whether the full treatment course is always necessary. It would be challenging to address these questions in a clinical trial. We used DILIsym, a mechanistic simulation of drug-induced liver injury, to investigate optimal NAC treatment after a single acetaminophen overdose for an average patient and a sample population (n = 957). For patients presenting within 24 h of ingestion, we found that the oral NAC protocol preserves more hepatocytes than the 21-h intravenous protocol. In various modeled scenarios, we found that the 21-h NAC infusion is often too short, whereas the full 72-h oral course is often unnecessary. We found that there is generally a good correlation between the time taken to reach peak serum alanine aminotransferase (ALT) and the time taken to clear N-acetyl-p-benzoquinone imine (NAPQI) from the liver. We also found that the most frequently used treatment nomograms underestimate the risk for patients presenting within 8 h of overdose ingestion. V(max) for acetaminophen bioactivation to NAPQI was the most important variable in the model in determining interpatient differences in susceptibility. In conclusion, DILIsym predicts that the oral NAC treatment protocol, or an intravenous protocol with identical dosing, is superior to the 21-h intravenous protocol and ALT is the optimal available biomarker for discontinuation of the therapy. The modeling also suggests that modification of the current treatment nomograms should be considered.

In vitro to in vivo extrapolation and species response comparisons for drug-induced liver injury (DILI) using DILIsym™: a mechanistic, mathematical model of DILI.

Drug-induced liver injury (DILI) is not only a major concern for all patients requiring drug therapy, but also for the pharmaceutical industry. Many new in vitro assays and pre-clinical animal models are being developed to help screen compounds for the potential to cause DILI. This study demonstrates that mechanistic, mathematical modeling offers a method for interpreting and extrapolating results. The DILIsym™ model (version 1A), a mathematical representation of DILI, was combined with in vitro data for the model hepatotoxicant methapyrilene (MP) to carry out an in vitro to in vivo extrapolation. In addition, simulations comparing DILI responses across species illustrated how modeling can aid in selecting the most appropriate pre-clinical species for safety testing results relevant to humans. The parameter inputs used to predict DILI for MP were restricted to in vitro inputs solely related to ADME (absorption, distribution, metabolism, elimination) processes. MP toxicity was correctly predicted to occur in rats, but was not apparent in the simulations for humans and mice (consistent with literature). When the hepatotoxicity of MP and acetaminophen (APAP) was compared across rats, mice, and humans at an equivalent dose, the species most susceptible to APAP was not susceptible to MP, and vice versa. Furthermore, consideration of variability in simulated population samples (SimPops™) provided confidence in the predictions and allowed examination of the biological parameters most predictive of outcome. Differences in model sensitivity to the parameters were related to species differences, but the severity of DILI for each drug/species combination was also an important factor.

Comparing the Liver Safety Profiles of 4 Next-Generation CGRP Receptor Antagonists to the Hepatotoxic CGRP Inhibitor Telcagepant Using Quantitative Systems Toxicology Modeling.

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.

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.

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.

Interaction of cationic drugs with liposomes.

Interactions between cationic drugs and anionic liposomes were studied by measuring binding of drugs and the effect of binding on liposome permeability. The measurements were analyzed in the context of a continuum model based on electrostatic interactions and a Langmuir isotherm. Experiments and modeling indicate that, although electrostatic interactions are important, the fraction of drug sequestered in the double-layer is negligible. The majority of drug enters the bilayer with the charged regions interacting with the charged lipid head groups and the lipophilic regions associated with the bilayer. The partitioning of the drug can be described by a Langmuir isotherm with the electrostatic interactions increasing the sublayer concentration of the drug. The binding isotherms are similar for all tricyclic antidepressants (TCA). Bupivacaine (BUP) binds significantly less compared to TCA because its structure is such that the charged region has minimal interactions with the lipid heads once the BUP molecule partitions inside the bilayer. Conversely, the TCAs are linear with distinct hydrophilic and lipophilic regions, allowing the lipophilic regions to lie inside the bilayer and the hydrophilic regions to protrude out. This conformation maximizes the permeability of the bilayer, leading to an increased release of a hydrophilic fluorescent dye from liposomes.

Bupivacaine binding to pegylated liposomes.

BACKGROUND: Local anesthetic drugs, such as bupivacaine, can cause severe toxicity. Lipid emulsions have been proposed and used clinically for treating such cases. Liposomes may be an alternative for overdose treatment because of their unique structures and surface charges, which allows them to act as high affinity drug "sinks" and remove bupivacaine from solution. METHODS: We conducted in vitro experiments with unilamellar and multilamellar anionic, polymer-coated liposomes to determine the amount of bupivacaine bound to liposomes in buffer solutions as a means of assessing the liposome-drug affinity. Binding experiments were also done in human serum to determine the liposomes' ability to compete with serum proteins for binding drug molecules. RESULTS: Unilamellar liposomes sequestered 60%-65% and 77%-85% of bupivacaine from buffer at 1.45 and 2.9 mg lipid/mL, respectively. The increased lipid loading increased the drug uptake at all drug concentrations measured (P = 0.001, 0.002, <0.001, and 0.003 for 5, 20, 35, and 50 microM, respectively). Multilamellar liposomes bound more drug per unit mass, with 71%-90% of the total bupivacaine bound at a phospholipid concentration of 1.45 mg lipid/mL. When comparing unilamellar and multilamellar liposomes at 1.45 mg lipid/mL, the multilamellar liposomes were significantly better at 3 of the 4 drug concentrations measured (P = 0.002, 0.001, 0.001, and 0.08 for 5, 20, 35, and 50 microM, respectively). In human serum samples, unilamellar liposomes (2.9 mg lipid/mL) reduced the unbound (free) drug by 36% (P = 0.037), 56% (P = 0.022), 47% (P = 0.042), and 50% (P = 0.018) for bupivacaine concentrations of 5, 20, 35, and 50 microM, respectively. CONCLUSIONS: The anionic, pegylated liposomes exhibit high binding for bupivacaine, both in buffer and in human serum. These results suggest that an IV injection of liposomes could be useful for the treatment of bupivacaine toxicity through drug redistribution.

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 (Ki) was critical to accurate predictions. In addition, simulations conducted on a sensitive subset of individuals (SimCohorts) revealed that when either BSEP or ETC inhibition was inactive, ALT elevations were not predicted to occur, suggesting that the two mechanisms operate synergistically to produce the observed clinical response. These results demonstrate how utilizing QST methods to interpret in vitro experimental results can lead to an improved understanding of the clinically relevant mechanisms underlying drug-induced toxicity.

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

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

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

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