Drug-induced Liver Injury Compounds Research Articles

A computational framework to in silico screen for drug-induced hepatocellular toxicity.

Drug-induced liver injury (DILI) is the most common trigger for acute liver failure and the leading cause of attrition in drug development. In this study, we developed an in silico framework to screen drug-induced hepatocellular toxicity (INSIGHT) by integrating the post-treatment transcriptomic data from both rodent models and primary human hepatocytes. We first built an early prediction model using logistic regression with elastic net regularization for 123 compounds and established the INSIGHT framework that can screen for drug-induced hepatotoxicity. The 235 signature genes identified by INSIGHT were involved in metabolism, bile acid synthesis, and stress response pathways. Applying the INSIGHT to an independent transcriptomic dataset treated by 185 compounds predicted that 27 compounds show a high DILI risk, including zoxazolamine and emetine. Further integration with cell image data revealed that predicted compounds with high DILI risk can induce abnormal morphological changes in the endoplasmic reticulum and mitochondrion. Clustering analysis of the treatment-induced transcriptomic changes delineated distinct DILI mechanisms induced by these compounds. Our study presents a computational framework for a mechanistic understanding of long-term liver injury and the prospective prediction of DILI risk.

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury.

Drug-induced liver injury (DILI) remains the main reason for drug development attritions largely due to poor mechanistic understanding. Toxicogenomic to interrogate the mechanism of DILI has been broadly performed. Gene coregulation network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improve mechanistic interpretation of toxicogenomic data. Here we performed an extensive concentration time course response-toxicogenomic study in the HepG2 cell line exposed to 20 DILI compounds, 7 reference compounds for stress response pathways, and 10 agonists for cytokines and growth factor receptors. We performed whole transcriptome targeted RNA sequencing to more than 500 conditions and applied weighted gene coregulated network analysis to the transcriptomics data followed by the identification of gene coregulated networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress response gene coregulated networks. We correlated gene coregulated networks with cell death onset and causal relationships of 67 critical target genes of these modules with the onset of cell death was evaluated using RNA interference screening. We identified GTPBP2, HSPA1B, IRF1, SIRT1, and TSC22D3 as essential modulators of DILI compound-induced cell death. These genes were also induced by DILI compounds in PHH. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis.

Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, ...) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.

In vitro/in silico prediction of drug induced steatosis in relation to oral doses and blood concentrations by the Nile Red assay

The accumulation of lipid droplets in hepatocytes is a key feature of drug-induced liver injury (DILI) and can be induced by a subset of hepatotoxic compounds. In the present study, we optimized and evaluated an in vitro technique based on the fluorescent dye Nile Red, further named Nile Red assay to quantify lipid droplets induced by the exposure to chemicals. The Nile Red assay and a cytotoxicity test (CTB assay) were then performed on cells exposed concentration-dependently to 60 different compounds. Of these, 31 were known to induce hepatotoxicity in humans, and 13 were reported to also cause steatosis. In order to compare in vivo relevant blood concentrations, pharmacokinetic models were established for all compounds to simulate the maximal blood concentrations (Cmax) at therapeutic doses. The results showed that several hepatotoxic compounds induced an increase in lipid droplets at sub-cytotoxic concentrations. To compare how well (1) the cytotoxicity test alone, (2) the Nile Red assay alone, and (3) the combination of the cytotoxicity test and the Nile Red assay (based on the lower EC10 of both assays) allow the differentiation between hepatotoxic and non-hepatotoxic compounds, a previously established performance metric, the Toxicity Separation Index (TSI) was calculated. In addition, the Toxicity Estimation Index (TEI) was calculated to determine how well blood concentrations that cause an increased DILI risk can be estimated for hepatotoxic compounds. Our findings indicate that the combination of both assays improved the TSI and TEI compared to each assay alone. In conclusion, the study demonstrates that inclusion of the Nile Red assay into in vitro test batteries may improve the prediction of DILI compounds.

Integration of temporal single cell cellular stress response activity with logic-ODE modeling reveals activation of ATF4-CHOP axis as a critical predictor of drug-induced liver injury

Drug-induced liver injury (DILI) is the most prevalent adversity encountered in drug development and clinical settings leading to urgent needs to understand the underlying mechanisms. In this study, we have systematically investigated the dynamics of the activation of cellular stress response pathways and cell death outcomes upon exposure of a panel of liver toxicants using live cell imaging of fluorescent reporter cell lines. We established a comprehensive temporal dynamic response profile of a large set of BAC-GFP HepG2 cell lines representing the following components of stress signaling: i) unfolded protein response (UPR) [ATF4, XBP1, BIP and CHOP]; ii) oxidative stress [NRF2, SRXN1, HMOX1]; iii) DNA damage [P53, P21, BTG2, MDM2]; and iv) NF-κB pathway [A20, ICAM1]. We quantified the single cell GFP expression as a surrogate for endogenous protein expression using live cell imaging over > 60 h upon exposure to 14 DILI compounds at multiple concentrations. Using logic-based ordinary differential equation (Logic-ODE), we modelled the dynamic profiles of the different stress responses and extracted specific descriptors potentially predicting the progressive outcomes. We identified the activation of ATF4-CHOP axis of the UPR as the key pathway showing the highest correlation with cell death upon DILI compound perturbation. Knocking down main components of the UPR provided partial protection from compound-induced cytotoxicity, indicating a complex interplay among UPR components as well as other stress pathways. Our results suggest that a systematic analysis of the temporal dynamics of ATF4-CHOP axis activation can support the identification of DILI risk for new candidate drugs.

Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features.

As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional safety testing methods, since the predictive power of most of the existing frameworks is insufficiently effective to address this pharmacological issue. In our study, we employ a natural language processing (NLP) inspired computational framework using convolutional neural networks and molecular fingerprint-embedded features. Our development set and independent test set have 1597 and 322 compounds, respectively. These samples were collected from previous studies and matched with established chemical databases for structural validity. Our study comes up with an average accuracy of 0.89, Matthews’s correlation coefficient (MCC) of 0.80, and an AUC of 0.96. Our results show a significant improvement in the AUC values compared to the recent best model with a boost of 6.67%, from 0.90 to 0.96. Also, based on our findings, molecular fingerprint-embedded featurizer is an effective molecular representation for future biological and biochemical studies besides the application of classic molecular fingerprints.

Characterization of a long-term mouse primary liver 3D tissue model recapitulating innate-immune responses and drug-induced liver toxicity.

Three-dimensional liver in vitro systems have recently attracted a lot of attention in drug development. These systems help to gain unprecedented insights into drug-induced liver injury (DILI), as they more closely reproduce liver biology, and as drug effects can be studied in isolated and controllable microenvironments. Many groups established human-based in vitro models but so far neglected the animal equivalent, although the availability of both models would be desirable. Animal in vitro models enable back- and forward translation of in vitro and in vivo findings, bridge the gap between rodent in vivo and human in vitro scenarios, and ultimately support the interpretation of data generated with preclinical species and humans. Since mice are often used in drug development and physiologically relevant in vitro systems are lacking, we established, for the first time, a mouse liver model that encompasses primary parenchymal and non-parenchymal cells with preserved viability and functionality over three weeks. Using our three-dimensional liver spheroids, we were able to predict the toxicity of known DILI compounds, demonstrated the interaction cascades between the different cell types and showed evidence of drug-induced steatosis and cholestasis. In summary, our mouse liver spheroids represent a valuable in vitro model that can be applied to study DILI findings, reported from mouse studies, and offers the potential to detect immune-mediated drug-induced liver toxicity.

Three-Dimensional Spheroids With Primary Human Liver Cells and Differential Roles of Kupffer Cells in Drug-Induced Liver Injury

Drug-induced liver injury (DILI) remains a challenge and a leading risk for drug discovery. Three-dimensional liver spheroids made from primary human hepatocytes (PHHs) with, or without, other liver cell types can provide more physiological relevance. In comparison to conventional 2-dimensional monolayer culture, our tests with 100 drugs of known DILI status indicate that PHH spheroids are significantly more sensitive in detecting drug-induced hepatotoxicity. To evaluate the role of Kupffer cells (KCs) in drug-induced liver toxicity, we have established conditions for generating co-culture spheroids with PHH and KCs. Inflammatory responses as shown by interleukin 6 secretion can be recapitulated in co-culture spheroids when treated with endotoxin lipopolysaccharides. KCs potentiated the cytotoxicity induced by trovafloxacin in co-culture spheroids at 48 h, but the differences between PHH spheroids and co-culture spheroids became less obvious after a 5-day treatment. Interestingly, a protective role of KCs was shown in co-culture spheroids treated with both acetaminophen and lipopolysaccharides. Additional tests with 14 DILI compounds comparing PHH spheroids and co-culture spheroids showed differential roles of KCs that were compound dependent. In summary, these 3-dimensional liver spheroid models are useful tools to understand the complex mechanisms underlying DILI.

Network pharmacology based investigation into the bioactive compounds and molecular mechanisms of Schisandrae Chinensis Fructus against drug-induced liver injury.

To investigate the against Drug-induced liver injury ingredients and their functional mechanisms in S. Chinensis Fructus. Liquid chromatograph-mass spectrometry analysis was performed on S. Chinensis Fructus extrac. The "Components-Target-Disease" network model was constructed by network pharmacology-based approaches. String analysis was performed to reveal enrichment of these target proteins, protein-protein interactions, pathways and related diseases. And experiment of APAP-induced drug-induced liver injury was to be verified. Cytoscape was used to determine the potential protein targets for these components in S. Chinensis Fructus, indicating that 17 against Drug-induced liver injury compounds in S. Chinensis Fructus regulate 52 diabetes-related proteins in 15 signal pathways and involve 14 core key targets. Verification experiment results that S. Chinensis Fructus prevented the elevation of serum biochemical parameters including aspartate aminotransferase (AST), alanine aminotransferase (ALT), purine nucleoside phosphorylase (PNP) and alkaline phosphatase (ALP) against acute liver failure. Additionally, S. Chinensis Fructus reduced the content of malondialdehyde (MDA), increased the levels of the Superoxide dismutase (SOD) and Glutathione (GSH), and inhibited the production of proinflammatory cytokines in APAP-induced hepatotoxicity. The mechanisms of S. Chinensis Fructus against Drug-induced liver injury were involved in the regulation of multiple targets, especially affecting the ErbB signaling pathways. The active ingredients of S. Chinensis Fructus may play a role against Drug-induced liver injury by participating in the regulation of inflammatory factors, oxidative stress.

Insights into mechanisms and severity of drug-induced liver injury via computational systems toxicology approach

Liver is the central place for drug metabolism. Drug-induced liver injury (DILI) is hence inevitable, and has become one of the leading causes for drug failure in development and drug withdrawal from the market. Due to lack of reliable preclinical and in vivo toxicology test conditions, it is time-consuming, laborious and costly to interpret the mechanisms of DILI through bioassays. In this paper, we developed a computational systems toxicology approach to investigate the molecular mechanisms of DILI. Totally 1478 DILI compounds were collected, together with 1067 known targets for 896 DILI compounds. Then, 173 new potential targets of these compounds were predicted by our bSDTNBI (balanced substructure-drug-target network-based inference) method. After network analysis, 145 primary genes were found to relate with hepatotoxicity and have higher expression in liver, among which 26 genes were predicted by our method, such as CYP2E1, GSTA1, EPHX1, ADH1B, ADH1C, ALDH2, F7, and IL2. A scoring function, DILI-Score, was further proposed to assess the hepatotoxic severity of a given compound. Finally, as case studies, we analyzed the mechanisms of DILI from the perspective of off-targets, and found out the pivotal genes for liver injuries induced by tyrosine kinase inhibitors and TAK-875. This work would be helpful for better understanding mechanisms of DILI and provide clues for reducing risk of DILI.

Model-based identification of TNF\u03b1-induced IKK\u03b2-mediated and I\u03baB\u03b1-mediated regulation of NF\u03baB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.

The Identification of Pivotal Transcriptional Factors Mediating Cell Responses to Drugs With Drug-Induced Liver Injury Liabilities.

Drug-induced liver injury (DILI) is a leading cause of drug attrition during drug development and a common reason for drug withdrawal from the market. The poor predictability of conventional animal-based approaches necessitates the development of alternative testing approaches. A body of evidence associates DILI with the induction of stress-response genes in liver cells. Here, we set out to identify signal transduction pathways predominantly involved in the regulation of gene transcription by DILI drugs. To this end, we employed ATTAGENE's cell-based multiplexed reporter assay, the FACTORIAL transcription factor (TF), that enables quantitative assessment of the activity of multiple stress-responsive TFs in a single well of cells. Homogeneous reporter system enables quantitative functional assessment of multiple transcription factors. Nat. Methods 5, 253-260). Using this assay, we assessed TF responses of the human hepatoma cell line HepG2 to a panel of 64 drug candidates, including 23 preclinical DILI and 11 clinical DILI compounds and 30 nonhepatotoxic compounds from a diverse physicochemical property space. We have identified 16 TF families that specifically responded to DILI drugs, including nuclear factor (erythroid-derived 2)-like 2 antioxidant response element, octamer, hypoxia inducible factor 1 alpha, farnesoid-X receptor, TCF/beta-catenin, aryl hydrocarbon receptor, activator protein-1, E2F, early growth response-1, metal-response transcription factor 1, sterol regulatory element-binding protein, paired box protein, peroxisome proliferator-activated receptor, liver X receptor, interferone regulating factor, and P53, and 2 promoters that responded to multiple TFs (cytomegalovirus and direct repeat 3/vitamin D receptor). Some of TFs identified here also have previously defined role in pathogenesis of liver diseases. These data demonstrate the utility of cost-effective, animal-free, TF profiling assay for detecting DILI potential of drug candidates at early stages of drug development.

High content analysis assay for prediction of human hepatotoxicity in HepaRG and HepG2 cells

Drug-induced liver injury (DILI) results in the termination of drug development or withdrawal of a drug from the market. The establishment of a predictive, high-throughput preclinical test system to evaluate potential clinical DILI is therefore required. Here, we established a high content analysis (HCA) assay in human hepatocyte cell lines such as the HepaRG with normal expression levels of CYP enzymes and HepG2 with extremely low expression levels of CYP enzymes. Clinical DILI or non-DILI compounds were evaluated for reactive oxygen species (ROS) production, glutathione (GSH) consumption, and mitochondrial membrane potential (MMP) attenuation. A proportion of DILI compounds induced ROS generation, GSH depletion, and MMP dysfunction, which was consistent with reported mechanisms of DILI of these compounds. In particular, DILI compounds that deplete GSH via reactive metabolites exhibited a more marked decrease in intracellular GSH or increase in ROS production in HepaRG cells than in HepG2 cells. Comparison of the two cell lines with different levels of CYP expression might help clarify the contribution of metabolism to hepatocyte toxicity. These results suggest that the HCA assay in HepaRG and HepG2 cells might help improve the accuracy of evaluating clinical DILI potential during drug screening.

Morphological and Functional Characterization and Assessment of iPSC-Derived Hepatocytes for In Vitro Toxicity Testing.

Drug-induced liver injury (DILI) remains a great challenge and a major concern during late-stage drug development. Induced pluripotent stem cells (iPSC) represent an exciting alternative invitro model system to explore the role of genetic diversity in DILI, especially when derived from patients who have experienced drug-induced hepatotoxicity. The development and validation of the iPSC-derived hepatocytes as an invitro cell-based model of DILI is an essential first step in creating more predictive tools for understanding patient-specific hepatotoxic responses to drug treatment. In this study, we performed extensive morphological and functional analyses on iPSC-derived hepatocytes from a commercial source. iPSC-derived hepatocytes exhibit many of the key morphological and functional features of primary hepatocytes, including membrane polarity and production of glycogen, lipids, and key hepatic proteins, such as albumin, asialoglycoprotein receptor and α1-antitrypsin. They maintain functional activity for many drug-metabolizing enzyme pathways and possess active efflux capacity of marker substrates into bile canalicular compartments. Whole genome-wide array analysis of multiple batches of iPSC-derived cells showed that their transcriptional profiles are more similar to those from neonatal and adult hepatocytes than those from fetal liver. Results from experiments using prototype DILI compounds, such as acetaminophen and trovafloxacin, indicate that these cells are able to reproduce key characteristic metabolic and adaptive responses attributed to the drug-induced hepatotoxic effects invivo. Overall, this novel system represents a promising new tool for understanding the underlying mechanisms of idiosyncratic DILI and for screening new compounds for DILI-related liabilities.

Activation of the Nrf2 response by intrinsic hepatotoxic drugs correlates with suppression of NF-κB activation and sensitizes toward TNFα-induced cytotoxicity.

Drug-induced liver injury (DILI) is an important problem both in the clinic and in the development of new safer medicines. Two pivotal adaptation and survival responses to adverse drug reactions are oxidative stress and cytokine signaling based on the activation of the transcription factors Nrf2 and NF-κB, respectively. Here, we systematically investigated Nrf2 and NF-κB signaling upon DILI-related drug exposure. Transcriptomics analyses of 90 DILI compounds in primary human hepatocytes revealed that a strong Nrf2 activation is associated with a suppression of endogenous NF-κB activity. These responses were translated into quantitative high-content live-cell imaging of induction of a selective Nrf2 target, GFP-tagged Srxn1, and the altered nuclear translocation dynamics of a subunit of NF-κB, GFP-tagged p65, upon TNFR signaling induced by TNFα using HepG2 cells. Strong activation of GFP-Srxn1 expression by DILI compounds typically correlated with suppression of NF-κB nuclear translocation, yet reversely, activation of NF-κB by TNFα did not affect the Nrf2 response. DILI compounds that provided strong Nrf2 activation, including diclofenac, carbamazepine and ketoconazole, sensitized toward TNFα-mediated cytotoxicity. This was related to an adaptive primary protective response of Nrf2, since loss of Nrf2 enhanced this cytotoxic synergy with TNFα, while KEAP1 downregulation was cytoprotective. These data indicate that both Nrf2 and NF-κB signaling may be pivotal in the regulation of DILI. We propose that the NF-κB-inhibiting effects that coincide with a strong Nrf2 stress response likely sensitize liver cells to pro-apoptotic signaling cascades induced by intrinsic cytotoxic pro-inflammatory cytokines.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-015-1536-3) contains supplementary material, which is available to authorized users.

Drug-Induced Endoplasmic Reticulum and Oxidative Stress Responses Independently Sensitize Toward TNFα-Mediated Hepatotoxicity

Drug-induced liver injury (DILI) is an important clinical problem. Here, we used a genomics approach to in detail investigate the hypothesis that critical drug-induced toxicity pathways act in synergy with the pro-inflammatory cytokine tumor necrosis factor α (TNFα) to cause cell death of liver HepG2 cells. Transcriptomics of the cell injury stress response pathways initiated by two hepatoxicants, diclofenac and carbamazepine, revealed the endoplasmic reticulum (ER) stress/translational initiation signaling and nuclear factor-erythroid 2 (NF-E2)-related factor 2 (Nrf2) antioxidant signaling as two major affected pathways, which was similar to that observed for the majority of ∼80 DILI compounds in primary human hepatocytes. Compounds displaying weak or no TNFα synergism, namely ketoconazole, nefazodone, and methotrexate, failed to synchronously induce both pathways. The ER stress induced was primarily related to protein kinase R-like ER kinase (PERK) and activating transcription factor 4 (ATF4) activation and subsequent expression of C/EBP homologous protein (CHOP), which was all independent of TNFα signaling. Identical ATF4 dependent transcriptional programs were observed in primary human hepatocytes as well as primary precision-cut human liver slices. Targeted RNA interference studies revealed that whereas ER stress signaling through inositol-requiring enzyme 1α (IRE1α) and activating transcription factor 6 (ATF6) acted cytoprotective, activation of the ER stress protein kinase PERK and subsequent expression of CHOP was pivotal for the onset of drug/TNFα-induced apoptosis. Whereas inhibition of the Nrf2-dependent adaptive oxidative stress response enhanced the drug/TNFα cytotoxicity, Nrf2 signaling did not affect CHOP expression. Both hepatotoxic drugs enhanced expression of the translational initiation factor EIF4A1, which was essential for CHOP expression and drug/TNFα-mediated cell killing. Our data support a model in which enhanced drug-induced translation initiates PERK-mediated CHOP signaling in an EIF4A1 dependent manner, thereby sensitizing toward caspase-8-dependent TNFα-induced apoptosis.

Evaluation of the use of imaging parameters for the detection of compound-induced hepatotoxicity in 384-well cultures of HepG2 cells and cryopreserved primary human hepatocytes

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.

Use of Micropatterned Cocultures to Detect Compounds That Cause Drug-Induced Liver Injury in Humans

Because drug-induced liver injury (DILI) remains a major reason for late-stage drug attrition, predictive assays are needed that can be deployed throughout the drug discovery process. Clinical DILI can be predicted with a sensitivity of ~50% and a false positive (FP) rate of ~5% using 24-h cultures of sandwich-cultured primary human hepatocytes and imaging of four cell injury endpoints (Xu et al., 2008). We hypothesized that long-term drug dosing in a functionally stable model of primary hepatocytes (micropatterned cocultures [MPCCs]) could provide for increased predictivity over short-term dosing paradigms. We used MPCCs with either primary human or rat hepatocytes to understand possible species differences along with standard endpoints (glutathione levels, ATP levels, albumin, and urea secretion) to test 45 drugs either known or not known to cause clinical DILI. Human MPCCs correctly detected 23 of 35 compounds known to cause DILI (65.7% sensitivity), with a FP rate of 10% for the 10 negative compounds tested. Rat MPCCs correctly detected 17 of 35 DILI compounds (48.6% sensitivity) and had a higher FP rate than human MPCCs (20 vs. 10%). For an additional 19 drugs with the most DILI concern, human MPCCs displayed a sensitivity of 100% when at least two hepatocyte donors were used for testing. Furthermore, MPCCs were able to detect relative clinical toxicities of structural drug analogs. In conclusion, MPCCs showed superiority over conventional short-term cultures for predictions of clinical DILI, and human MPCCs were more predictive for human liabilities than their rat counterparts.