Minimizing DILI risk in drug discovery — A screening tool for drug candidates

Control compounds for preclinical drug-induced liver injury assessment: Consensus-driven systematic review by the ProEuroDILI network

BACKGROUND & AIMS

Idiosyncratic drug-induced liver injury (DILI) is a complex and unpredictable event caused by drugs, and herbal or dietary supplements. Early identification of human hepatotoxicity at preclinical stages remains a major challenge, in which the selection of validated in vitro systems and test drugs has a significant impact. In this systematic review, we analyzed the compounds used in hepatotoxicity assays and established a list of DILI-positive and -negative control drugs for validation of in vitro models of DILI, supported by literature and clinical evidence and endorsed by an expert committee from the COST Action ProEuroDILI Network (CA17112).

METHODS

Following 2020 PRISMA guidelines, original research articles focusing on DILI which used in vitro human models and performed at least one hepatotoxicity assay with positive and negative control compounds, were included. Bias of the studies was assessed by a modified 'Toxicological Data Reliability Assessment Tool'.

RESULTS

A total of 51 studies (out of 2,936) met the inclusion criteria, with 30 categorized as reliable without restrictions. Although there was a broad consensus on positive compounds, the selection of negative compounds lacked clarity. 2D monoculture, short exposure times and cytotoxicity endpoints were the most tested, although there was no consensus on drug concentrations.

CONCLUSIONS

Extensive analysis highlighted the lack of agreement on control compounds for in vitro DILI assessment. Following comprehensive in vitro and clinical data analysis together with input from the expert committee, an evidence-based consensus-driven list of 10 positive and negative control drugs for validation of in vitro models of DILI is proposed.

IMPACT AND IMPLICATIONS

Prediction of human toxicity early in the drug development process remains a major challenge, necessitating the development of more physiologically relevant liver models and careful selection of drug-induced liver injury (DILI)-positive and -negative control drugs to better predict the risk of DILI associated with new drug candidates. Thus, this systematic study has crucial implications for standardizing the validation of new in vitro models of DILI. By establishing a consensus-driven list of positive and negative control drugs, the study provides a scientifically justified framework for enhancing the consistency of preclinical testing, thereby addressing a significant challenge in early hepatotoxicity identification. Practically, these findings can guide researchers in evaluating safety profiles of new drugs, refining in vitro models, and informing regulatory agencies on potential improvements to regulatory guidelines, ensuring a more systematic and efficient approach to drug safety assessment.

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

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

Cyanide Trapping of Iminium Ion Reactive Metabolites: Implications for Clinical Hepatotoxicity

Reactive metabolite formation is a major mechanism of hepatotoxicity. Although reactive electrophiles can be soft or hard in nature, screening strategies have generally focused on the use of glutathione trapping assays to screen for soft electrophiles, with many data sets available to support their use. The use of a similar assay for hard electrophiles using cyanide as the trapping agent is far less common, and there is a lack of studies with sufficient supporting data. Using a set of 260 compounds with a defined hepatotoxicity status by the FDA, a comprehensive literature search yielded cyanide trapping data on an unbalanced set of 20 compounds that were all clinically hepatotoxic. Thus, a further set of 19 compounds was selected to generate cyanide trapping data, resulting in a more balanced data set of 39 compounds. Analysis of the data demonstrated that the cyanide trapping assay had high specificity (92%) and a positive predictive value (83%) such that hepatotoxic compounds would be confidently flagged. Structural analysis of the adducts formed revealed artifactual methylated cyanide adducts to also occur, highlighting the importance of full structural identification to confirm the nature of the adduct formed. The assay was demonstrated to add the most value for compounds containing typical structural alerts for hard electrophile formation: half of the severe hepatotoxins with these structural alerts formed cyanide adducts, while none of the severe hepatotoxins with no relevant structural alerts formed adducts. The assay conditions used included cytosolic enzymes (e.g., aldehyde oxidase) and an optimized cyanide concentration to minimize the inhibition of cytochrome P450 enzymes by cyanide. Based on the demonstrated added value of this assay, it is to be initiated for use at GSK as part of the integrated hepatotoxicity strategy, with its performance being reviewed periodically as more data is generated.

New in vitro screening system to detect drug-induced liver injury using a culture plate with low drug sorption and high oxygen permeability

Drug-induced liver injury (DILI) is a major factor underlying drug withdrawal from the market. Therefore, it is important to predict DILI during the early phase of drug discovery. Metabolic activation and mitochondrial toxicity are good indicators of the potential for DILI. However, hepatocyte function, including drug-metabolizing enzyme activity and mitochondrial function, reportedly decreases under conventional culture conditions; therefore, these conditions fail to precisely detect metabolic activation and mitochondrial toxicity-induced cell death. To resolve this issue, we employed a newly developed cell culture plate with high oxygen permeability and low drug sorption (4-polymethyl-1-pentene [PMP] plate). Under PMP plate conditions, cytochrome P450 (CYP) activity and mitochondrial function were increased in primary rat hepatocytes. Following l-buthionine-sulfoximine-induced glutathione depletion, acetaminophen-induced cell death significantly increased under PMP plate conditions. Additionally, 1-aminobenzotriazole reduced cell death. Moreover, mitochondrial toxicity due to mitochondrial complex inhibitors (ketoconazole, metformin, and phenformin) increased under PMP plate conditions. In summary, PMP plate conditions could improve CYP activity and mitochondrial function in primary rat hepatocytes and potentially detect metabolic activation and mitochondrial toxicity.

Perspectives of data science in preclinical safety assessment

The data landscape in preclinical safety assessment is fundamentally changing because of not only emerging new data types, such as human systems biology, or real-world data (RWD) from clinical trials, but also technological advancements in data-processing software and analytical tools based on deep learning approaches. The recent developments of data science are illustrated with use cases for the three factors: predictive safety (new in silico tools), insight generation (new data for outstanding questions); and reverse translation (extrapolating from clinical experience to resolve preclinical questions). Further advances in this field can be expected if companies focus on overcoming identified challenges related to a lack of platforms and data silos and assuring appropriate training of data scientists within the preclinical safety teams.

A Unique In Vitro Assay to Investigate ABCB4 Transport Function

ABCB4 is almost exclusively expressed in the liver, where it plays an essential role in bile formation by transporting phospholipids into the bile. ABCB4 polymorphisms and deficiencies in humans are associated with a wide spectrum of hepatobiliary disorders, attesting to its crucial physiological function. Inhibition of ABCB4 by drugs may lead to cholestasis and drug-induced liver injury (DILI), although compared with other drug transporters, there are only a few identified substrates and inhibitors of ABCB4. Since ABCB4 shares up to 76% identity and 86% similarity in the amino acid sequence with ABCB1, also known to have common drug substrates and inhibitors, we aimed to develop an ABCB4 expressing Abcb1-knockout MDCKII cell line for transcellular transport assays. This in vitro system allows the screening of ABCB4-specific drug substrates and inhibitors independently of ABCB1 activity. Abcb1KO-MDCKII-ABCB4 cells constitute a reproducible, conclusive, and easy to use assay to study drug interactions with digoxin as a substrate. Screening a set of drugs with different DILI outcomes proved that this assay is applicable to test ABCB4 inhibitory potency. Our results are consistent with prior findings concerning hepatotoxicity causality and provide new insights for identifying drugs as potential ABCB4 inhibitors and substrates.

Drug Metabolism of Hepatocyte-like Organoids and Their Applicability in In Vitro Toxicity Testing

Emerging advances in the field of in vitro toxicity testing attempt to meet the need for reliable human-based safety assessment in drug development. Intrahepatic cholangiocyte organoids (ICOs) are described as a donor-derived in vitro model for disease modelling and regenerative medicine. Here, we explored the potential of hepatocyte-like ICOs (HL-ICOs) in in vitro toxicity testing by exploring the expression and activity of genes involved in drug metabolism, a key determinant in drug-induced toxicity, and the exposure of HL-ICOs to well-known hepatotoxicants. The current state of drug metabolism in HL-ICOs showed levels comparable to those of PHHs and HepaRGs for CYP3A4; however, other enzymes, such as CYP2B6 and CYP2D6, were expressed at lower levels. Additionally, EC50 values were determined in HL-ICOs for acetaminophen (24.0−26.8 mM), diclofenac (475.5−>500 µM), perhexiline (9.7−>31.5 µM), troglitazone (23.1−90.8 µM), and valproic acid (>10 mM). Exposure to the hepatotoxicants showed EC50s in HL-ICOs comparable to those in PHHs and HepaRGs; however, for acetaminophen exposure, HL-ICOs were less sensitive. Further elucidation of enzyme and transporter activity in drug metabolism in HL-ICOs and exposure to a more extensive compound set are needed to accurately define the potential of HL-ICOs in in vitro toxicity testing.

Role of Hepatocyte Transporters in Drug-Induced Liver Injury (DILI)-In Vitro Testing

Bile acids and bile salts (BA/BS) are substrates of both influx and efflux transporters on hepatocytes. Canalicular efflux transporters, such as BSEP and MRP2, are crucial for the removal of BA/BS to the bile. Basolateral influx transporters, such as NTCP, OATP1B1/1B3, and OSTα/β, cooperate with canalicular transporters in the transcellular vectorial flux of BA/BS from the sinusoids to the bile. The blockage of canalicular transporters not only impairs the bile flow but also causes the intracellular accumulation of BA/BS in hepatocytes that contributes to, or even triggers, liver injury. In the case of BA/BS overload, the efflux of these toxic substances back to the blood via MRP3, MRP4, and OST α/β is considered a relief function. FXR, a key regulator of defense against BA/BS toxicity suppresses de novo bile acid synthesis and bile acid uptake, and promotes bile acid removal via increased efflux. In drug development, the early testing of the inhibition of these transporters, BSEP in particular, is important to flag compounds that could potentially inflict drug-induced liver injury (DILI). In vitro test systems for efflux transporters employ membrane vesicles, whereas those for influx transporters employ whole cells. Additional in vitro pharmaceutical testing panels usually include cellular toxicity tests using hepatocytes, as well as assessments of the mitochondrial toxicity and accumulation of reactive oxygen species (ROS). Primary hepatocytes are the cells of choice for toxicity testing, with HepaRG cells emerging as an alternative. Inhibition of the FXR function is also included in some testing panels. The molecular weight and hydrophobicity of the drug, as well as the steady-state total plasma levels, may positively correlate with the DILI potential. Depending on the phase of drug development, the physicochemical properties, dosing, and cut-off values of BSEP IC₅₀ ≤ 25-50 µM or total C_ss,plasma/BSEP IC₅₀ ≥ 0.1 may be an indication for further testing to minimize the risk of DILI liability.

A curated binary pattern multitarget dataset of focused ATP-binding cassette transporter inhibitors

Multitarget datasets that correlate bioactivity landscapes of small-molecules toward different related or unrelated pharmacological targets are crucial for novel drug design and discovery. ATP-binding cassette (ABC) transporters are critical membrane-bound transport proteins that impact drug and metabolite distribution in human disease as well as disease diagnosis and therapy. Molecular-structural patterns are of the highest importance for the drug discovery process as demonstrated by the novel drug discovery tool ‘computer-aided pattern analysis’ (‘C@PA’). Here, we report a multitarget dataset of 1,167 ABC transporter inhibitors analyzed for 604 molecular substructures in a statistical binary pattern distribution scheme. This binary pattern multitarget dataset (ABC_BPMDS) can be utilized for various areas. These areas include the intended design of (i) polypharmacological agents, (ii) highly potent and selective ABC transporter-targeting agents, but also (iii) agents that avoid clearance by the focused ABC transporters [e.g., at the blood-brain barrier (BBB)]. The information provided will not only facilitate novel drug prediction and discovery of ABC transporter-targeting agents, but also drug design in general in terms of pharmacokinetics and pharmacodynamics.

Measurement(s)	Influx • Efflux • Tracer • Transport velocity
Technology Type(s)	Fluorometry • Radioactivity • Plate reader • Flow cytometer • Tracer distribution
Factor Type(s)	half-maximal inhibition concentration
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	cell culture
Sample Characteristic - Location	Kingdom of Norway • Germany • Australia • Latvia

In vitro cell-based models of drug-induced hepatotoxicity screening: progress and limitation

Drug-induced liver injury (DILI) is one of the major causes of post-approval withdrawal of therapeutics. As a result, there is an increasing need for accurate predictive in vitro assays that reliably detect hepatotoxic drug candidates while reducing drug discovery time, costs, and the number of animal experiments. In vitro hepatocyte-based research has led to an improved comprehension of the underlying mechanisms of chemical toxicity and can assist the prioritization of therapeutic choices with low hepatotoxicity risk. Therefore, several in vitro systems have been generated over the last few decades. This review aims to comprehensively present the development and validation of 2D (two-dimensional) and 3D (three-dimensional) culture approaches on hepatotoxicity screening of compounds and highlight the main factors affecting predictive power of experiments. To this end, we first summarize some of the recognized hepatotoxicity mechanisms and related assays used to appraise DILI mechanisms and then discuss the challenges and limitations of in vitro models.

Clinical Pharmacokinetics and Pharmacodynamics of the Selective Progesterone Receptor Modulator Vilaprisan: A Comprehensive Overview

Vilaprisan is a highly potent selective progesterone receptor modulator in development for the treatment of symptomatic uterine fibroids and endometriosis. Its pharmacokinetics are characterized by rapid absorption, almost complete bioavailability, and dose-proportional exposure. The intrinsic factors of age, bodyweight, and race have no clinically relevant effect on the pharmacokinetics and pharmacodynamics of vilaprisan and do not warrant a dose adjustment. Similarly, vilaprisan can be used in patients with mild or moderate renal or hepatic impairment without dose adjustment, but its use is not recommended in patients with severe organ impairment. Vilaprisan has no perpetrator potential on cytochrome P450 (CYP) enzymes or transporters and therefore restrictions in the concomitant use of their substrates are not required. Nonetheless, because it is a sensitive CYP3A4 substrate itself, concomitant use of vilaprisan with strong CYP3A inhibitors or inducers is not recommended. However, there is no risk for QTc prolongation when vilaprisan and a strong CYP3A inhibitor are administered concomitantly, as indicated by a vilaprisan concentration–QTc response analysis across all studies with triplicate electrocardiogram measurements. Furthermore, due to its mode of action, vilaprisan is also not recommended to be used together with progestin-containing oral contraceptives. Vilaprisan shows a steep exposure–response relationship for inducing amenorrhea in patients with uterine fibroids experiencing heavy menstrual bleeding. Based on simulations, a dose of 2 mg/day is expected to induce a maximum bleeding reduction and was thus selected for phase III.

Development and Application of a Transcriptomic Signature of Bioactivation in an Advanced In Vitro Liver Model to Reduce Drug-induced Liver Injury Risk Early in the Pharmaceutical Pipeline

Early risk assessment of drug-induced liver injury (DILI) potential for drug candidates remains a major challenge for pharmaceutical development. We have previously developed a set of rat liver transcriptional biomarkers in short-term toxicity studies to inform the potential of drug candidates to generate a high burden of chemically reactive metabolites that presents higher risk for human DILI. Here, we describe translation of those NRF1-/NRF2-mediated liver tissue biomarkers to an in vitro assay using an advanced micropatterned coculture system (HEPATOPAC) with primary hepatocytes from male Wistar Han rats. A 9-day, resource-sparing and higher throughput approach designed to identify new chemical entities with lower reactive metabolite-forming potential was qualified for internal decision making using 93 DILI-positive and -negative drugs. This assay provides 81% sensitivity and 90% specificity in detecting hepatotoxicants when a positive test outcome is defined as the bioactivation signature score of a test drug exceeding the threshold value at an in vitro test concentration that falls within 3-fold of the estimated maximum drug concentration at the human liver inlet following highest recommended clinical dose administrations. Using paired examples of compounds from distinct chemical series and close structural analogs, we demonstrate that this assay can differentiate drugs with lower DILI risk. The utility of this in vitro transcriptomic approach was also examined using human HEPATOPAC from a single donor, yielding 68% sensitivity and 86% specificity when the aforementioned criteria are applied to the same 93-drug test set. Routine use of the rat model has been adopted with deployment of the human model as warranted on a case-by-case basis. This in vitro transcriptomic signature-based strategy can be used early in drug discovery to derisk DILI potential from chemically reactive metabolites by guiding structure-activity relationship hypotheses and candidate selection.

Tetrahydrofuran-Based Transient Receptor Potential Ankyrin 1 (TRPA1) Antagonists: Ligand-Based Discovery, Activity in a Rodent Asthma Model, and Mechanism-of-Action via Cryogenic Electron Microscopy

Transient receptor potential ankyrin 1 (TRPA1) is a nonselective calcium-permeable ion channel highly expressed in the primary sensory neurons functioning as a polymodal sensor for exogenous and endogenous stimuli and has generated widespread interest as a target for inhibition due to its implication in neuropathic pain and respiratory disease. Herein, we describe the optimization of a series of potent, selective, and orally bioavailable TRPA1 small molecule antagonists, leading to the discovery of a novel tetrahydrofuran-based linker. Given the balance of physicochemical properties and strong in vivo target engagement in a rat AITC-induced pain assay, compound 20 was progressed into a guinea pig ovalbumin asthma model where it exhibited significant dose-dependent reduction of inflammatory response. Furthermore, the structure of the TRPA1 channel bound to compound 21 was determined via cryogenic electron microscopy to a resolution of 3 Å, revealing the binding site and mechanism of action for this class of antagonists.

Cell-based high-throughput screening for the evaluation of reactive metabolite formation potential

Here, we established a high-throughput in vitro assay system to predict reactive metabolite (RM) formation. First, we performed the glutathione (GSH) consumption assay to monitor GSH levels as an index of RM formation potential using HepaRG cells pretreated with 500 μM D,L-buthionine-(S,R)-sulfoximine (BSO) and then treated with ticlopidine and diclofenac. Both drugs, under GSH-reduced conditions, significantly decreased relative cellular GSH content by 70% and 34%, respectively, compared with that in cells not pretreated with BSO. Next, we examined the correlation between GSH consumption and covalent binding assays; the results showed good correlation (correlation coefficient = 0.818). We then optimized the test compound concentration for evaluating RM formation potential using 76 validation compound sets, and the highest sensitivity (53%) was observed at 100 μM. Finally, using HepG2 cells, PXB-cells, and human primary hepatocytes, we examined the cell types suitable for evaluating RM formation potential. The expression of CYP3A4 was highest in HepaRG cells, suggesting the highest sensitivity (56.4%) of the GSH consumption assay. Moreover, a co-culture model of PXB-cells and HepaRG cells showed high sensitivity (72.7%) with sufficient specificity (85.7%). Thus, the GSH consumption assay can be used to effectively evaluate RM formation potential in the early stages of drug discovery.

Characterizing the reproducibility in using a liver microphysiological system for assaying drug toxicity, metabolism, and accumulation

Liver microphysiological systems (MPSs) are promising models for predicting hepatic drug effects. Yet, after a decade since their introduction, MPSs are not routinely used in drug development due to lack of criteria for ensuring reproducibility of results. We characterized the feasibility of a liver MPS to yield reproducible outcomes of experiments assaying drug toxicity, metabolism, and intracellular accumulation. The ability of the liver MPS to reproduce hepatotoxic effects was assessed using trovafloxacin, which increased lactate dehydrogenase (LDH) release and reduced cytochrome P450 3A4 (CYP3A4) activity. These observations were made in two test sites and with different batches of Kupffer cells. Upon culturing equivalent hepatocytes in the MPS, spheroids, and sandwich cultures, differences between culture formats were detected in CYP3A4 activity and albumin production. Cells in all culture formats exhibited different sensitivities to hepatotoxicant exposure. Hepatocytes in the MPS were more functionally stable than those of other culture platforms, as CYP3A4 activity and albumin secretion remained prominent for greater than 18 days in culture, whereas functional decline occurred earlier in spheroids (12 days) and sandwich cultures (7 days). The MPS was also demonstrated to be suitable for metabolism studies, where CYP3A4 activity, troglitazone metabolites, diclofenac clearance, and intracellular accumulation of chloroquine were quantified. To ensure reproducibility between studies with the MPS, the combined use of LDH and CYP3A4 assays were implemented as quality control metrics. Overall results indicated that the liver MPS can be used reproducibly in general drug evaluation applications. Study outcomes led to general considerations and recommendations for using liver MPSs. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Microphysiological systems (MPSs) have been designed to recreate organ- or tissue-specific characteristics of extracellular microenvironments that enhance the physiological relevance of cells in culture. Liver MPSs enable long-lasting and stable culture of hepatic cells by culturing them in three-dimensions and exposing them to fluid flow. WHAT QUESTION DID THIS STUDY ADDRESS? What is the functional performance relative to other cell culture platforms and the reproducibility of a liver MPS for assessing drug development and evaluation questions, such as toxicity, metabolism, and pharmacokinetics? WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? The liver MPS systematically detected the toxicity of trovafloxacin. When compared with spheroids and sandwich cultures, this system had a more stable function and different sensitivity to troglitazone, tamoxifen, and digoxin. Quantifying phase II metabolism of troglitazone and intracellular accumulation of chloroquine demonstrated the potential use of the liver MPS for studying drug metabolism and pharmacokinetics. Quality control criteria for assessing chip function were key for reliably using the liver MPS. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? Due to its functional robustness and physiological relevance (3D culture, cells expose to fluid flow and co-culture of different cell types), the liver MPS can, in a reproducible manner: (i) detect inflammatory-induced drug toxicity, as demonstrated with trovafloxacin, (ii) detect the toxicity of other drugs, such as troglitazone, tamoxifen, and digoxin, with different effects than those detected in spheroids and sandwich cultures, (iii) enable studies of hepatic function that rely on prolonged cellular activity, and (iv) detect phase II metabolites and drug accumulation to potentially support the interpretation of clinical data. The integration of MPSs in drug development will be facilitated by careful evaluation of performance and reproducibility as performed in this study.

A Critical Perspective on 3D Liver Models for Drug Metabolism and Toxicology Studies

The poor predictability of human liver toxicity is still causing high attrition rates of drug candidates in the pharmaceutical industry at the non-clinical, clinical, and post-marketing authorization stages. This is in part caused by animal models that fail to predict various human adverse drug reactions (ADRs), resulting in undetected hepatotoxicity at the non-clinical phase of drug development. In an effort to increase the prediction of human hepatotoxicity, different approaches to enhance the physiological relevance of hepatic in vitro systems are being pursued. Three-dimensional (3D) or microfluidic technologies allow to better recapitulate hepatocyte organization and cell-matrix contacts, to include additional cell types, to incorporate fluid flow and to create gradients of oxygen and nutrients, which have led to improved differentiated cell phenotype and functionality. This comprehensive review addresses the drug-induced hepatotoxicity mechanisms and the currently available 3D liver in vitro models, their characteristics, as well as their advantages and limitations for human hepatotoxicity assessment. In addition, since toxic responses are greatly dependent on the culture model, a comparative analysis of the toxicity studies performed using two-dimensional (2D) and 3D in vitro strategies with recognized hepatotoxic compounds, such as paracetamol, diclofenac, and troglitazone is performed, further highlighting the need for harmonization of the respective characterization methods. Finally, taking a step forward, we propose a roadmap for the assessment of drugs hepatotoxicity based on fully characterized fit-for-purpose in vitro models, taking advantage of the best of each model, which will ultimately contribute to more informed decision-making in the drug development and risk assessment fields.

[The trends in predicting drug-induced liver injury]

Drug-induced liver injury (DILI) is the major reason for the discontinuation of new drug development and the withdrawal of drugs from the market. Hence, the evaluation systems which predict the onset of DILI in the pre-clinical stage are needed. To date, many researchers have conducted the mechanism of DILI, but the DILI prediction is poor because of the complexity of DILI. In this regard, based on the information obtained from basic research and clinical case, several pharmaceutical companies have been developed DILI prediction methods with high sensitivity and specificity by combining multiple targets. Another reason for low predictability is derived from the conventional culture method which causes a rapid decrease in hepatocyte function. To overcome these problems, the construction of a high-level in vitro evaluation system has been developed and applied to DILI evaluation. On the other hand, these in vitro evaluation methods require a lot of labor and cost so, in silico prediction methods have also been constructed in recent years. Based on this point, this article reviews the trends in DILI prediction systems in the non-clinical stage.

In vitro assessment of farnesoid X receptor antagonism to predict drug-induced liver injury risk

Drug-induced liver injury (DILI) continues to be a major cause of drug attrition and restrictive labeling. Given the importance of farnesoid X receptor (FXR) in bile acid homeostasis, drug-related FXR antagonism may be an important mechanism of DILI. However, a comprehensive assessment of this phenomenon broadly in the context of DILI is lacking. As such, we used an orthogonal approach comprising a FXR target gene assay in primary human hepatocytes and a commercially available FXR reporter assay to investigate the potential FXR antagonistic effects of an extensive test set of 159 compounds with and without association with clinical DILI. Data were omitted from analysis based on the presence of cytotoxicity to minimize false positive assay signals and other complications in data interpretation. Based on the experimental approaches employed and corresponding data, the prevalence of FXR antagonism was relatively low across this broad DILI test set, with 16-24% prevalence based on individual assay results or combined signals in both assays. Moreover, FXR antagonism was not highly predictive for identifying clinically relevant hepatotoxicants retrospectively, where FXR antagonist classification alone had minimal to moderate predictive value as represented by positive and negative likelihood ratios of 2.24-3.84 and 0.72-0.85, respectively. The predictivity did not increase significantly when considering only compounds with high clinical exposure (maximal or efficacious plasma exposures > 1.0 μM). In contrast, modest gains in predictive value of FXR antagonism were observed considering compounds that also inhibit bile salt export pump. In addition, we have identified novel FXR antagonistic effects of well-studied hepatotoxic drugs, including bosentan, tolcapone and ritonavir. In conclusion, this work represents a comprehensive evaluation of FXR antagonism in the context of DILI, including its overall predictivity and challenges associated with detecting this phenomenon in vitro.

Strategies to Mitigate the Bioactivation of Aryl Amines

The bioactivation of xenobiotics to yield reactive metabolites can lead to tolerability and toxicity concerns within a drug discovery program. Development of strategies for mitigating the metabolic liability of commonly encountered toxicophores, such as anilines, relies on an understanding of the relative tendency of these functionalities to undergo bioactivation. In this report, we present the first systematic study of the structure-activity relationships of the bioactivation of aryl amine fragments (molecular weight < 250 Da) using a glutathione (GSH) trapping assay in the presence of human liver microsomes and the reduced form of nicotinamide adenine dinucleotide phosphate. This study demonstrates that conversion of anilines to nitrogen-containing heteroarylamines results in a lower abundance of GSH conjugates in the order phenyl > pyrimidine ≈ pyridine > pyridazine. Introduction of electron-withdrawing functionality on the aromatic ring had a less pronounced effect on the extent of GSH conjugation. Examination of more drug-like compounds sourced from in-house drug discovery programs revealed similar trends in bioactivation between matched pairs containing (hetero)aryl amines. This study provides medicinal chemists with insights and qualitative guidance for the minimization of risks related to aryl amine metabolism.

Drug Induced Liver Injury (DILI). Mechanisms and Medicinal Chemistry Avoidance/Mitigation Strategies

Adverse drug reactions (ADRs) are a common cause of attrition in drug discovery and development and drug-induced liver injury (DILI) is a leading cause of preclinical and clinical drug terminations. This perspective outlines many of the known DILI mechanisms and assessment methods used to evaluate and mitigate DILI risk. Literature assessments and retrospective analyses using verified DILI-associated drugs from the Liver Tox Knowledge Base (LTKB) have been used to derive the predictive value of each end point, along with combination approaches of multiple methods. In vitro assays to assess inhibition of the bile salt export pump (BSEP), mitotoxicity, reactive metabolite (RM) formation, and hepatocyte cytolethality, along with physicochemical properties and clinical dose provide useful DILI predictivity. This Perspective also highlights some of the strategies used by medicinal chemists to reduce DILI risk during the optimization of drug candidates.

Assessing Toxicity with Human Cell-Based In Vitro Methods

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

The evolution of strategies to minimise the risk of human drug-induced liver injury (DILI) in drug discovery and development

Early identification of toxicity associated with new chemical entities (NCEs) is critical in preventing late-stage drug development attrition. Liver injury remains a leading cause of drug failures in clinical trials and post-approval withdrawals reflecting the poor translation between traditional preclinical animal models and human clinical outcomes. For this reason, preclinical strategies have evolved over recent years to incorporate more sophisticated human in vitro cell-based models with multi-parametric endpoints. This review aims to highlight the evolution of the strategies adopted to improve human hepatotoxicity prediction in drug discovery and compares/contrasts these with recent activities in our lab. The key role of human exposure and hepatic drug uptake transporters (e.g. OATPs, OAT2) is also elaborated.

Liver microphysiological systems development guidelines for safety risk assessment in the pharmaceutical industry

The liver is critical to consider during drug development because of its central role in the handling of xenobiotics, a process which often leads to localized and/or downstream tissue injury. Our ability to predict human clinical safety outcomes with animal testing is limited due to species differences in drug metabolism and disposition, while traditional human in vitro liver models often lack the necessary in vivo physiological fidelity. To address this, increasing numbers of liver microphysiological systems (MPS) are being developed, however the inconsistency in their optimization and characterization often leads to models that do not possess critical levels of baseline performance that is required for many pharmaceutical industry applications. Herein we provide a guidance on best approaches to benchmark liver MPS based on 3 stages of characterization that includes key performance metrics and a 20 compound safety test set. Additionally, we give an overview of frequently used liver injury safety assays, describe the ideal MPS model, and provide a perspective on currently best suited MPS contexts of use. This pharmaceutical industry guidance has been written to help MPS developers and end users identify what could be the most valuable models for safety risk assessment.

Quantitative evaluation of hepatic and intestinal induction of CYP3A in clinical practice

This is the first report quantitatively evaluating the clinical induction of CYP3A in the liver and the intestine.To evaluate hepatic induction, we collected literature data on endogenous biomarkers of hepatic CYP3A induction which we then used to calculate the fold-induction (inducer-mediated change in biomarker level). Literature data on decreases in the area under the curve (AUC) of alfentanil, a CYP3A substrate, caused by CYP3A inducers were also collected. We used the hepatic intrinsic clearance of alfentanil to calculate the hepatic induction ratio (inducer-mediated change in intrinsic clearance). For intestinal induction, the intestinal bioavailability (F_g) of alfentanil was used to calculate the intestinal induction ratio. We determined in vivo maximum induction (E_max) and the average unbound plasma concentration (C_av,u) required for half the maximum induction (EC₅₀) for inducers using an E_max model analysis.In our results, fold-induction was comparable to the induction ratio at several inducer concentrations, and almost the maximum induction was achieved by a therapeutic dose. Induction ratios in the intestine were similar to the liver.Our findings suggest that, by knowing only hepatic induction ratios for common inducers, we can quantitatively predict the decreases in the AUC of substrates by CYP3A induction.

Predictivity/Translatability of Toxicities Observed in Nonclinical Toxicology Studies to Clinical Safety Outcomes in Drug Development: Case Examples

Nonclinical toxicology studies are conducted to characterize the potential toxicities and establish a safe starting dose for new drugs in clinical studies, but the question remains as to how predictable/translatable the nonclinical safety findings are to humans. In many cases, there is good concordance between nonclinical species and patients. However, there are cases for which there is a lack of predictivity or translatability that led to early termination of clinical studies due to unanticipated toxicities or early termination of programs before making it to the clinic due to unacceptable nonclinical toxicities assumed to be translatable. A few case examples of safety findings that are translatable versus safety findings that are not translatable and why they are not translateable were presented as a symposium at the 38th Annual Meeting of the American College of Toxicology in Palm Springs, California, and are discussed in this article.

Predicting Drug-Induced Liver Injury with Bayesian Machine Learning

Drug induced liver injury (DILI) can require significant risk management in drug development and on occasion can cause morbidity or mortality, leading to drug attrition. Optimizing candidates preclinically can minimize hepatotoxicity risk, but it is difficult to predict due to multiple etiologies encompassing DILI, often with multifactorial and overlapping mechanisms. In addition to epidemiological risk factors, physicochemical properties, dose, disposition, lipophilicity, and hepatic metabolic function are also relevant for DILI risk. Better human-relevant, predictive models are required to improve hepatotoxicity risk assessment in drug discovery. Our hypothesis is that integrating mechanistically relevant hepatic safety assays with Bayesian machine learning will improve hepatic safety risk prediction. We present a quantitative and mechanistic risk assessment for candidate nomination using data from in vitro assays (hepatic spheroids, BSEP, mitochondrial toxicity, and bioactivation), together with physicochemical (cLogP) and exposure (Cmax_total) variables from a chemically diverse compound set (33 no/low-, 40 medium-, and 23 high-severity DILI compounds). The Bayesian model predicts the continuous underlying DILI severity and uses a data-driven prior distribution over the parameters to prevent overfitting. The model quantifies the probability that a compound falls into either no/low-, medium-, or high-severity categories, with a balanced accuracy of 63% on held-out samples, and a continuous prediction of DILI severity along with uncertainty in the prediction. For a binary yes/no DILI prediction, the model has a balanced accuracy of 86%, a sensitivity of 87%, a specificity of 85%, a positive predictive value of 92%, and a negative predictive value of 78%. Combining physiologically relevant assays, improved alignment with FDA recommendations, and optimal statistical integration of assay data leads to improved DILI risk prediction.

Measures of BSEP Inhibition In Vitro Are Not Useful Predictors of DILI

Inhibition of the bile salt export pump (BSEP) by a drug has been implicated as a risk factor for a drug's potential to cause drug-induced liver injury (DILI) and is thought to be an important mechanism leading to DILI. For a wide variety of drugs a correlation has been observed between the potency of in vitro BSEP inhibition and its propensity to cause DILI in humans. These findings were interpreted to suggest that BSEP inhibition could be an important mechanism to help explain how some drugs initiate DILI. Because the Biopharmaceutics Drug Disposition Classification System (BDDCS) can be useful in characterizing and predicting some important transporter effects in terms of drug-drug interactions, we evaluated the information provided by BDDCS in order to understand the inhibition propensity of BSEP. Here we analyze the relationship between a compound's ability to inhibit BSEP function and cause liver injury in humans using a compilation of published DILI datasets that have screened for BSEP inhibitors, other hepatic transporters and other mechanism-based toxicity key events. Our results demonstrate that there is little support for in vitro BSEP inhibition being universally DILI predictive. Rather we show that most potent BSEP inhibitors are BDDCS class 2 drugs, which we have demonstrated previously is the BDDCS class most likely to be DILI related. Since BDDCS class is not related to any proposed DILI mechanistic hypotheses, we maintain that if measures of BSEP inhibition alone or together with inhibition of other transporters cannot be differentiated from class 2 assignment, there is no support for in vitro BSEP inhibition being DILI predictive.

LC-MS/MS based detection and characterization of covalent glutathione modifications formed by reactive drug of abuse metabolites

Conjugation with the tripeptide glutathione (GSH) is a common mechanism of detoxification of many endogenous and exogenous compounds. This phenomenon typically occurs through the formation of a covalent bond between the nucleophilic free thiol moiety of GSH and an electrophilic site on the compound of interest. While GSH adducts have been identified for many licit drugs, there is a lack of information on the ability of drugs of abuse to adduct GSH. The present study utilized a metabolic assay with GSH as a nucleophilic trapping agent to bind reactive drug metabolites formed in situ. Extracted ion MS spectra were collected via LC-QqQ-MS/MS for all potentially significant ions and examined for fragmentation common to GSH-containing compounds, followed by confirmation of adduction and structural characterization performed by LC-QTOF-MS/MS. In addition to the two positive controls, of the 14 drugs of abuse tested, 10 exhibited GSH adduction, with several forming multiple adducts, resulting in a total of 22 individual identified adducts. A number of these are previously unreported in the literature, including those for diazepam, naltrexone, oxycodone and Δ⁹-THC.

Impact of Physicochemical Properties on Dose and Hepatotoxicity of Oral Drugs

A database containing maximum daily doses of 1841 marketed oral drugs was used to examine the influence of physicochemical properties on dose and hepatotoxicity (drug induced liver injury, DILI). Drugs in the highest ∼20% dose range had significantly reduced mean lipophilicity and molecular weight, increased fractional surface area, increased % of acids, and decreased % of bases versus drugs in the lower ∼60% dose range. Drugs in the ∼20-40% dose range had intermediate mean properties, similar to the mean values for the full drug set. Drugs that are both large and highly lipophilic almost invariably do not have doses in the upper ∼20% range. The results show that oral druglike physicochemical properties are different according to these dose ranges, and this is consistent with maintenance of acceptable safety profiles as efficacious exposure increases. Verified DILI annotations from a compilation of >1000 approved drugs (Chen, M.; et al. Drug Discov. Today, 2016, 21, 648 ) were used. The drugs classified as "No DILI" ( n = 163) had significantly lower dose and lipophilicity, and higher Fsp3 (fraction of carbon atoms that are sp³ hybridized) versus the "Most DILI" ( n = 163) drugs. The percentages of acids were reduced and bases increased in the "No DILI" versus the "Most DILI" groups. Drugs classified as "Less DILI" or "Ambiguous DILI" had intermediate mean values of dose, lipophilicity, Fsp3, and % acids and bases. The impact of lipophilicity and Fsp3 on DILI increases in the upper 20% versus the lower 80% dose range, and a simple decision tree model predicted "No DILI" versus "Most DILI" outcomes with 82% accuracy. The model correctly classified 19 of 22 drugs (86%) that failed in development due to human hepatotoxicity. Because many oral drugs lacking DILI annotations are predicted to be "Most DILI", the model is best used preclinically in conjunction with experimental DILI mitigation.

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification

Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have achieved only minimal success. Several studies have shown total administered dose alone or in combination with drug lipophilicity to be correlated with a higher risk of DILI. However, it would be best to have a predictive DILI methodology early in drug development, long before the clinical dose is known. Here we discuss the extent to which Biopharmaceutics Drug Disposition Classification System (BDDCS) defining characteristics, independent of knowing actual drug pharmacokinetics/pharmacodynamics and dose, can be used to evaluate prior published predictive proposals. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity, and that all of the short-lived published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensively metabolized compounds are at higher risk of developing DILI is confirmed, but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs.

CONCLUSION

Our published analyses suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms, although BDDCS classification itself is not sufficiently predictive. Almost all of the predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs, although some early data with microliver platforms enabling long-enduring metabolic competency show promising results.

Individual serum bile acid profiling in rats aids in human risk assessment of drug-induced liver injury due to BSEP inhibition

Drug-induced liver injury (DILI) has been the most frequent cause of post-marketing drug withdrawals in the last 50years. The multifactorial nature of events that precede severe liver injury in human patients is difficult to model in rodents due to a variety of confounding or contributing factors that include disease state, concurrent medications, and translational species differences. In retrospective analyses, a consistent risk factor for DILI has been the inhibition of the Bile Salt Export Pump (BSEP). One compound known for potent BSEP inhibition and severe DILI is troglitazone. The purpose of the current study is to determine if serum profiling of 19 individual bile acids by liquid chromatography-mass spectrometry (LC/MS) can detect perturbations in bile acid homeostasis in rats after acute intravenous (IV) administration of vehicle or 5, 25, or 50mg/kg troglitazone. Minimal serum transaminase elevations (approximately two-fold) were observed with no evidence of microscopic liver injury. However, marked changes in individual serum bile acids occurred, with dose-dependent increases in the majority of the bile acids profiled. When compared to predose baseline values, tauromuricholic acid and taurocholic acid had the most robust increase in serum levels and dynamic range, with a maximum fold increase from baseline of 34-fold and 29-fold, respectively. Peak bile acid increases occurred within 2hours (h) after dosing and returned to baseline values before 24h. In conclusion, serum bile acid profiling can potentially identify a mechanistic risk of clinical DILI that could be poorly detected by traditional toxicity endpoints.

A rapid mitochondrial toxicity assay utilizing rapidly changing cell energy metabolism

Drug-induced liver injury is a major cause of safety-related drug-marketing withdrawals. Several drugs have been reported to disrupt mitochondrial function, resulting in hepatotoxicity. The development of a simple and effective in vitro assay to identify the potential for mitochondrial toxicity is thus desired to minimize the risk of causing hepatotoxicity and subsequent drug withdrawal. An in vitro test method called the "glucose-galactose" assay is often used in drug development but requires prior-culture of cells over several passages for mitochondrial adaptation, thereby restricting use of the assay. Here, we report a rapid version of this method with the same predictability as the original method. We found that replacing the glucose in the medium with galactose resulted in HepG2 cells immediately shifting their energy metabolism from glycolysis to oxidative phosphorylation due to drastic energy starvation; in addition, the intracellular concentration of ATP was reduced by mitotoxicants when glucose in the medium was replaced with galactose. Using our proposed rapid method, mitochondrial dysfunction in HepG2 cells can be evaluated by drug exposure for one hour without a pre-culture step. This rapid assay for mitochondrial toxicity may be more suitable for high-throughput screening than the original method at an early stage of drug development.

Drug rechallenge following drug-induced liver injury

Drug-induced hepatocellular injury is identified internationally by alanine aminotransferase (ALT) levels equal to or exceeding 5× the upper limit of normal (ULN) appearing within 3 months of drug initiation, after alternative causes are excluded. Upon withdrawing the suspect drug, ALT generally decrease by 50% or more. With drug readministration, a positive rechallenge has recently been defined by an ALT level of 3-5× ULN or greater. Nearly 50 drugs are associated with positive rechallenge after drug-induced liver injury (DILI): antimicrobials; and central nervous system, cardiovascular and oncology therapeutics. Drugs associated with high rates of positive rechallenge exhibit multiple risk factors: daily dose >50 mg, an increased incidence of ALT elevations in clinical trials, immunoallergic clinical injury, and mitochondrial impairment in vitro. These drug factors interact with personal genetic, immune, and metabolic factors to influence positive rechallenge rates and outcomes. Drug rechallenge following drug-induced liver injury is associated with up to 13% mortality in prospective series of all prescribed drugs. In recent oncology trials, standardized systems have enabled safer drug rechallenge with weekly liver chemistry monitoring during the high-risk period and exclusion of patients with hypersensitivity. However, high positive rechallenge rates with other innovative therapeutics suggest that caution should be taken with rechallenge of high-risk drugs.

CONCLUSION

For critical medicines, drug rechallenge may be appropriate when 1) no safer alternatives are available, 2) the objective benefit exceeds the risk, and 3) patients are fully informed and consent, can adhere to follow-up, and alert providers to hepatitis symptoms. To better understand rechallenge outcomes and identify key risk factors for positive rechallenge, additional data are needed from controlled clinical trials, prospective registries, and large health care databases. (Hepatology 2017;66:646-654).

Synergistic Cytotoxicity from Drugs and Cytokines In Vitro as an Approach to Classify Drugs According to Their Potential to Cause Idiosyncratic Hepatotoxicity: A Proof-of-Concept Study

Idiosyncratic drug-induced liver injury (IDILI) typically occurs in a small fraction of patients and has resulted in removal of otherwise efficacious drugs from the market. Current preclinical testing methods are ineffective in predicting which drug candidates have IDILI liability. Recent results suggest that immune mediators such as tumor necrosis factor-α (TNF) and interferon-γ (IFN) interact with drugs that cause IDILI to kill hepatocytes. This proof-of-concept study was designed to test the hypothesis that drugs can be classified according to their ability to cause IDILI in humans using classification modeling with covariates derived from concentration-response relationships that describe cytotoxic interaction with cytokines. Human hepatoma (HepG2) cells were treated with drugs associated with IDILI or with drugs lacking IDILI liability and cotreated with TNF and/or IFN. Detailed concentration-response relationships were determined for calculation of parameters such as the maximal cytotoxic effect, slope, and EC₅₀ for use as covariates for classification modeling using logistic regression. These parameters were incorporated into multiple classification models to identify combinations of covariates that most accurately classified the drugs according to their association with human IDILI. Of 14 drugs associated with IDILI, almost all synergized with TNF to kill HepG2 cells and were successfully classified by statistical modeling. IFN enhanced the toxicity mediated by some IDILI-associated drugs in the presence of TNF. In contrast, of 10 drugs with little or no IDILI liability, none synergized with inflammatory cytokines to kill HepG2 cells and were classified accordingly. The resulting optimal model classified the drugs with extraordinary selectivity and specificity.

Predicting drug-induced liver injury: The importance of data curation

Drug-induced liver injury (DILI) is a major issue for both patients and pharmaceutical industry due to insufficient means of prevention/prediction. In the current work we present a 2-class classification model for DILI, generated with Random Forest and 2D molecular descriptors on a dataset of 966 compounds. In addition, predicted transporter inhibition profiles were also included into the models. The initially compiled dataset of 1773 compounds was reduced via a 2-step approach to 966 compounds, resulting in a significant increase (p-value < 0.05) in model performance. The models have been validated via 10-fold cross-validation and against three external test sets of 921, 341 and 96 compounds, respectively. The final model showed an accuracy of 64% (AUC 68%) for 10-fold cross-validation (average of 50 iterations) and comparable values for two test sets (AUC 59%, 71% and 66%, respectively). In the study we also examined whether the predictions of our in-house transporter inhibition models for BSEP, BCRP, P-glycoprotein, and OATP1B1 and 1B3 contributed in improvement of the DILI mode. Finally, the model was implemented with open-source 2D RDKit descriptors in order to be provided to the community as a Python script.

Navigating tissue chips from development to dissemination: A pharmaceutical industry perspective

Tissue chips are poised to deliver a paradigm shift in drug discovery. By emulating human physiology, these chips have the potential to increase the predictive power of preclinical modeling, which in turn will move the pharmaceutical industry closer to its aspiration of clinically relevant and ultimately animal-free drug discovery. Despite the tremendous science and innovation invested in these tissue chips, significant challenges remain to be addressed to enable their routine adoption into the industrial laboratory. This article describes the main steps that need to be taken and highlights key considerations in order to transform tissue chip technology from the hands of the innovators into those of the industrial scientists. Written by scientists from 13 pharmaceutical companies and partners at the National Institutes of Health, this article uniquely captures a consensus view on the progression strategy to facilitate and accelerate the adoption of this valuable technology. It concludes that success will be delivered by a partnership approach as well as a deep understanding of the context within which these chips will actually be used. Impact statement The rapid pace of scientific innovation in the tissue chip (TC) field requires a cohesive partnership between innovators and end users. Near term uptake of these human-relevant platforms will fill gaps in current capabilities for assessing important properties of disposition, efficacy and safety liabilities. Similarly, these platforms could support mechanistic studies which aim to resolve challenges later in development (e.g. assessing the human relevance of a liability identified in animal studies). Building confidence that novel capabilities of TCs can address real world challenges while they themselves are being developed will accelerate their application in the discovery and development of innovative medicines. This article outlines a strategic roadmap to unite innovators and end users thus making implementation smooth and rapid. With the collective contributions from multiple international pharmaceutical companies and partners at National Institutes of Health, this article should serve as an invaluable resource to the multi-disciplinary field of TC development.

Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury

Drug-induced liver injury (DILI) continues to be a major source of clinical attrition, precautionary warnings, and post-market withdrawal of drugs. Accordingly, there is a need for more predictive tools to assess hepatotoxicity risk in drug discovery. Three-dimensional (3D) spheroid hepatic cultures have emerged as promising tools to assess mechanisms of hepatotoxicity, as they demonstrate enhanced liver phenotype, metabolic activity, and stability in culture not attainable with conventional two-dimensional hepatic models. Increased sensitivity of these models to drug-induced cytotoxicity has been demonstrated with relatively small panels of hepatotoxicants. However, a comprehensive evaluation of these models is lacking. Here, the predictive value of 3D human liver microtissues (hLiMT) to identify known hepatotoxicants using a panel of 110 drugs with and without clinical DILI has been assessed in comparison to plated two-dimensional primary human hepatocytes (PHH). Compounds were treated long-term (14 days) in hLiMT and acutely (2 days) in PHH to assess drug-induced cytotoxicity over an 8-point concentration range to generate IC₅₀ values. Regardless of comparing IC₅₀ values or exposure-corrected margin of safety values, hLiMT demonstrated increased sensitivity in identifying known hepatotoxicants than PHH, while specificity was consistent across both assays. In addition, hLiMT out performed PHH in correctly classifying hepatotoxicants from different pharmacological classes of molecules. The hLiMT demonstrated sufficient capability to warrant exploratory liver injury biomarker investigation (miR-122, HMGB1, α-GST) in the cell-culture media. Taken together, this study represents the most comprehensive evaluation of 3D spheroid hepatic cultures up to now and supports their utility for hepatotoxicity risk assessment in drug discovery.

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.

Evaluation of DILI Predictive Hypotheses in Early Drug Development

Drug-induced liver injury (DILI) is a leading cause of drug failure in clinical trials and a major reason for drug withdrawals. DILI has been shown to be dependent on both daily dose and extent of hepatic metabolism. Yet, early in drug development daily dose is unknown. Here, we perform a comprehensive analysis of the published hypotheses that attempt to predict DILI, including a new analysis of the Biopharmaceutics Drug Disposition Classification System (BDDCS) in evaluating the severity of DILI warnings in drug labels approved by the FDA and the withdrawal status due to adverse drug reactions (ADRs). Our analysis confirms that higher doses ≥50 mg/day lead to increased DILI potential, but this property alone is not sufficient to predict the DILI potential. We evaluate prior attempts to categorize DILI such as Rule of 2, BSEP inhibition, and measures of key mechanisms of toxicity compared to BDDCS classification. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity and that all of the published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensive metabolized compounds are at higher risk of developing DILI is confirmed but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs. We do not propose that the BDDCS classification, which does not require knowledge of the clinical dose, is sufficiently predictive/accurate of DILI potential for new molecular entities but suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms.

CONCLUSION

The most successful approaches to predict DILI potential all include a measure of dose, yet there is a quantifiable uncertainty associated with the predicted dose early in drug development. Here, we compare the possibility of predicting DILI potential using the BDDCS classification versus previously published methods and note that many hypothesized predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs.

Revisiting the Metabolism and Bioactivation of Ketoconazole in Human and Mouse Using Liquid Chromatography-Mass Spectrometry-Based Metabolomics

Although ketoconazole (KCZ) has been used worldwide for 30 years, its metabolic characteristics are poorly described. Moreover, the hepatotoxicity of KCZ limits its therapeutic use. In this study, we used liquid chromatography–mass spectrometry-based metabolomics to evaluate the metabolic profile of KCZ in mouse and human and identify the mechanisms underlying its hepatotoxicity. A total of 28 metabolites of KCZ, 11 of which were novel, were identified in this study. Newly identified metabolites were classified into three categories according to the metabolic positions of a piperazine ring, imidazole ring, and N-acetyl moiety. The metabolic characteristics of KCZ in human were comparable to those in mouse. Moreover, three cyanide adducts of KCZ were identified in mouse and human liver microsomal incubates as “flags” to trigger additional toxicity study. The oxidation of piperazine into iminium ion is suggested as a biotransformation responsible for bioactivation. In summary, the metabolic characteristics of KCZ, including reactive metabolites, were comprehensively understood using a metabolomics approach.