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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-017-2002-1) contains supplementary material, which is available to authorized users.

Idiosyncratic adverse drug reactions (IADRs) in humans can result in a broad range of clinically significant toxicities leading to attrition during drug development as well as postlicensing withdrawal or labeling. IADRs arise from both drug and patient related mechanisms and risk factors. Drug related risk factors, resulting from parent compound or metabolites, may involve multiple contributory mechanisms including organelle toxicity, effects related to compound disposition, and/or immune activation. In the current study, we evaluate an in vitro approach, which explored both cellular effects and covalent binding (CVB) to assess IADR risks for drug candidates using 36 drugs which caused different patterns and severities of IADRs in humans. The cellular effects were tested in an in vitro Panel of five assays which quantified (1) toxicity to THLE cells (SV40 T-antigen-immortalized human liver epithelial cells), which do not express P450s, (2) toxicity to a THLE cell line which selectively expresses P450 3A4, (3) cytotoxicity in HepG2 cells in glucose and galactose media, which is indicative of mitochondrial injury, (4) inhibition of the human bile salt export pump, BSEP, and (5) inhibition of the rat multidrug resistance associated protein 2, Mrp2. In addition, the CVB Burden was estimated by determining the CVB of radiolabeled compound to human hepatocytes and factoring in both the maximum prescribed daily dose and the fraction of metabolism leading to CVB. Combining the aggregated results from the in vitro Panel assays with the CVB Burden data discriminated, with high specificity (78%) and sensitivity (100%), between 27 drugs, which had severe or marked IADR concern, and 9 drugs, which had low IADR concern, we propose that this integrated approach has the potential to enable selection of drug candidates with reduced propensity to cause IADRs in humans.

Primary human hepatocytes (PHHs) are commonly used for in vitro studies of drug-induced liver injury. However, when cultured as 2D monolayers, PHH lose crucial hepatic functions within hours. This dedifferentiation can be ameliorated when PHHs are cultured in sandwich configuration (2Dsw), particularly when cultures are regularly re-overlaid with extracellular matrix, or as 3D spheroids. In this study, the 6 participating laboratories evaluated the robustness of these 2 model systems made from cryopreserved PHH from the same donors considering both inter-donor and inter-laboratory variability and compared their suitability for use in repeated-dose toxicity studies using 5 different hepatotoxins with different toxicity mechanisms. We found that expression levels of proteins involved in drug absorption, distribution, metabolism, and excretion, as well as catalytic activities of 5 different CYPs, were significantly higher in 3D spheroid cultures, potentially affecting the exposure of the cells to drugs and their metabolites. Furthermore, global proteomic analyses revealed that PHH in 3D spheroid configuration were temporally stable whereas proteomes from the same donors in 2Dsw cultures showed substantial alterations in protein expression patterns over the 14 days in culture. Overall, spheroid cultures were more sensitive to the hepatotoxic compounds investigated, particularly upon long-term exposures, across testing sites with little inter-laboratory or inter-donor variability. The data presented here suggest that repeated-dosing regimens improve the predictivity of in vitro toxicity assays, and that PHH spheroids provide a sensitive and robust system for long-term mechanistic studies of drug-induced hepatotoxicity, whereas the 2Dsw system has a more dedifferentiated phenotype and lower sensitivity to detect hepatotoxicity.

Water-insoluble organic compounds are often used in aqueous environments in various pharmaceutical and consumer products. To overcome insolubility, the particles are dispersed in a medium during product formation, but large particles that are formed may affect product performance and safety. Many techniques have been used to produce nanodispersions-dispersions with nanometre-scale dimensions-that have properties similar to solutions. However, making nanodispersions requires complex processing, and it is difficult to achieve stability over long periods. Here we report a generic method for producing organic nanoparticles with a combination of modified emulsion-templating and freeze-drying. The dry powder composites formed using this method are highly porous, stable and form nanodispersions upon simple addition of water. Aqueous nanodispersions of Triclosan (a commercial antimicrobial agent) produced with this approach show greater activity than organic/aqueous solutions of Triclosan.

Nanomedicine strategies have produced many commercial products. However, no orally dosed HIV nanomedicines are available clinically to patients. Although nanosuspensions of drug particles have demonstrated many benefits, experimentally achieving >25 wt% of drug relative to stabilizers is highly challenging. In this study, the emulsion-templated freeze-drying technique for nanoparticles formation is applied for the first time to optimize a nanodispersion of the leading non-nucleoside reverse transcriptase inhibitor efavirenz, using clinically acceptable polymers and surfactants. Dry monoliths containing solid drug nanoparticles with extremely high drug loading (70 wt% relative to polymer and surfactant stabilizers) are stable for several months and reconstitute in aqueous media to provide nanodispersions with z-average diameters of 300 nm. The solid drug nanoparticles exhibit reduced cytoxicity and increased in vitro transport through model gut epithelium. In vivo studies confirm bioavailability benefits with an approximately four-fold higher pharmacokinetic exposure after oral administration to rodents, and predictive modeling suggests dose reduction with the new formulation may be possible.

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.

Drug-induced liver injury (DILI) is a major cause of failed drug development, withdrawal and restricted usage. Therefore screening assays which aid selection of candidate drugs with reduced propensity to cause DILI are required. We have investigated the toxicity of 144 drugs, 108 of which caused DILI, using assays identified in the literature as having some predictivity for hepatotoxicity. The validated assays utilised either HepG2 cells, HepG2 cells in the presence of rat S9 fraction or isolated human hepatocytes. All parameters were quantified by multiplexed and automated high content fluorescence microscopy, at appropriate time points after compound administration (4, 24 or 48h). The individual endpoint which identified drugs that caused DILI with greatest precision was maximal fold induction in CM-H2DFFDA staining in hepatocytes after 24h (41% sensitivity, 86% specificity). However, hierarchical clustering analysis of all endpoints provided the most sensitive identification of drugs which caused DILI (58% sensitivity, 75% specificity). We conclude that multi-parametric high content cell toxicity assays can enable in vitro detection of drugs that have high propensity to cause DILI in vivo but that many DILI compounds exhibit few in vitro signals when evaluated using these assays.

Drug-induced liver injury remains a frequent reason for drug withdrawal. Accordingly, more predictive and translational models are required to assess human hepatotoxicity risk. This study presents a comprehensive evaluation of two promising models to assess mechanistic hepatotoxicity, microengineered Organ-Chips and 3D hepatic spheroids, which have enhanced liver phenotype, metabolic activity and stability in culture not attainable with conventional 2D models. Sensitivity of the models to two hepatotoxins, acetaminophen (APAP) and fialuridine (FIAU), was assessed across a range of cytotoxicity biomarkers (ATP, albumin, miR-122, α-GST) as well as their metabolic functionality by quantifying APAP, FIAU and CYP probe substrate metabolites. APAP and FIAU produced dose-and time-dependent increases in miR-122 and α-GST release as well as decreases in albumin secretion in both Liver-Chips and hepatic spheroids. Metabolic turnover of CYP probe substrates, APAP and FIAU, was maintained over the 10-day exposure period at concentrations where no cytotoxicity was detected and APAP turnover decreased at concentrations where cytotoxicity was detected. With APAP, the most sensitive biomarkers were albumin in the Liver-Chips (EC 50 5.6 mM, day 1) and miR-122 and ATP in the liver spheroids (14-fold and EC 50 2.9 mM, respectively, day 3). With FIAU, the most sensitive biomarkers were albumin in the Liver-Chip (EC 50 126 µM) and miR-122 (15-fold) in the liver spheroids, both on day 7. In conclusion, both models exhibited integrated toxicity and metabolism, and broadly similar sensitivity to the hepatotoxicants at relevant clinical concentrations, demonstrating the utility of these models for improved hepatotoxicity risk assessment.