Development of an in vitro liver toxicity prediction model based on longer term primary rat hepatocyte culture

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.

Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis

Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mild-moderate asthma after integrating the results from GSE69683 and GSE27011 datasets. The enrichment analysis indicated that 202 DEGs were associated with metabolism- and immune-related processes. 10 hub genes were identified by Cytoscape and five of these genes’ AUC (area under the curve) values were greater than 0.6 in GSE69683. The AUC value reached to 0.701 when combined SEC61A1 and ALDH18A1 expression. The expression of the five hub genes was verified in an external dataset. The network analysis revealed that transcription factor (TF) WT1, ZEB1, RERE, FOSL1, and miR-20a may be involved in the development of asthma. In addition, we found cyclosporine and acetaminophen could interact with these hub genes and may be negatively associated with most of the five hub genes according to previous reports. Overall, key genes were identified between mild-moderate and severe asthmatics, which contributed to the understanding of the development of asthma.

Classification of Cholestatic and Necrotic Hepatotoxicants Using Transcriptomics on Human Precision-Cut Liver Slices

Human toxicity screening is an important stage in the development of safe drug candidates. Hepatotoxicity is one of the major reasons for the withdrawal of drugs from the market because the liver is the major organ involved in drug metabolism, and it can generate toxic metabolites. There is a need to screen molecules for drug-induced hepatotoxicity in humans at an earlier stage. Transcriptomics is a technique widely used to screen molecules for toxicity and to unravel toxicity mechanisms. To date, the majority of such studies were performed using animals or animal cells, with concomitant difficulty in interpretation due to species differences, or in human hepatoma cell lines or cultured hepatocytes, suffering from the lack of physiological expression of enzymes and transporters and lack of nonparenchymal cells. The aim of this study was to classify known hepatotoxicants on their phenotype of toxicity in humans using gene expression profiles ex vivo in human precision-cut liver slices (PCLS). Hepatotoxicants known to induce either necrosis (n = 5) or cholestasis (n = 5) were used at concentrations inducing low (<30%) and medium (30-50%) cytotoxicity, based on ATP content. Random forest and support vector machine algorithms were used to classify hepatotoxicants using a leave-one-compound-out cross-validation method. Optimized biomarker sets were compared to derive a consensus list of markers. Classification correctly predicted the toxicity phenotype with an accuracy of 70-80%. The classification is slightly better for the low than for the medium cytotoxicity. The consensus list of markers includes endoplasmic reticulum stress genes, such as C2ORF30, DNAJB9, DNAJC12, SRP72, TMED7, and UBA5, and a sodium/bile acid cotransporter (SLC10A7). This study shows that human PCLS are a useful model to predict the phenotype of drug-induced hepatotoxicity. Additional compounds should be included to confirm the consensus list of markers, which could then be used to develop a biomarker PCR-array for hepatotoxicity screening.

In silico assessment of adverse drug reactions and associated mechanisms

During recent years, various in silico approaches have been developed to estimate chemical and biological drug features, for example chemical fragments, protein targets, pathways, among others, that correlate with adverse drug reactions (ADRs) and explain the associated mechanisms. These features have also been used for the creation of predictive models that enable estimation of ADRs during the early stages of drug development. In this review, we discuss various in silico approaches to predict these features for a certain drug, estimate correlations with ADRs, establish causal relationships between selected features and ADR mechanisms and create corresponding predictive models.

In vitro kinetics of amiodarone and its major metabolite in two human liver cell models after acute and repeated treatments

The limited value of in vitro toxicity data for the in vivo extrapolation has been often attributed to the lack of kinetic data. Here the in vitro kinetics of amiodarone (AMI) and its mono-N-desethyl (MDEA) metabolite was determined and modelled in primary human hepatocytes (PHH) and HepaRG cells, after single and repeated administration of clinically relevant concentrations. AMI bioavailability was influenced by adsorption to the plastic and the presence of protein in the medium (e.g. 10% serum protein reduced the uptake by half in HepaRG cells). The cell uptake was quick (within 3h), AMI metabolism was efficient and a dynamic equilibrium was reached in about a week after multiple dosing. In HepaRG cells the metabolic clearance was higher than in PHH and increased over time, as well as CYP3A4. The interindividual variability in MDEA production in PHHs was not proportional to the differences in CYP3A4 activities, suggesting the involvement of other CYPs and/or AMI-related CYP inhibition. After repeated treatment AMI showed a slight potential for bioaccumulation, whereas much higher intracellular MDEA levels accumulated over time, especially in the HepaRG cells, associated with occurrence of phospholipidosis. The knowledge of in vitro biokinetics is important to transform an actual in vitro concentration-effect into an in vivo dose-effect relationship by using appropriate modelling, thus improving the in vitro-to-in vivo extrapolation.

Mathematical modeling of the in vitro hepatic disposition of mycophenolic acid and its glucuronide in sandwich-cultured human hepatocytes

In recent years, it has become increasingly important to test the safety of circulating metabolites of novel drugs as part of drug discovery and development programs. Accordingly, it is essential to develop suitable methods for identifying the major metabolites and their disposition in animal species and in humans. Mycophenolic acid (MPA), a selective inosine-5'-monophosphate dehydrogenase (IMPDH) inhibitor, is metabolized by glucuronidation and enterohepatic circulation of MPA-glucuronides is an important factor in the continuous systemic exposure of MPA. In humans, about 90% of the administered MPA dose is finally excreted as MPA phenyl-glucuronide (MPAG) in urine. Notably, the plasma concentration of MPAG is much higher than that of MPA. These factors suggest that, after its formation in hepatocytes, MPAG is excreted into bile and is also transported across the basolateral membrane to enter the circulation. In the present study, we performed metabolic/hepatobiliary transport studies of MPA and MPAG using sandwich-cultured human hepatocytes (SCHH) and constructed mathematical models of their hepatic disposition. We also performed vesicular transport studies to identify which human multidrug resistance-associated proteins (MRPs) are involved in the transport of MPAG from hepatocytes. MPAG was a preferred substrate for the biliary excretion transporter MRP2 and the hepatic basolateral transporters MRP3 and MRP4 in conventional and metabolic/hepatobiliary transport studies using SCHH and vesicular transport studies using human MRP-expressing membrane vesicles. The resulting mathematical model suggested that the basolateral transport plays an important role in the hepatic disposition of MPAG formed in hepatocytes. Our findings suggest that mathematical modeling of metabolic/hepatobiliary transport studies using SCH will provide useful information for determining the fate of metabolites formed in hepatocytes.

Drug safety testing paradigm, current progress and future challenges: an overview

Early assessment of the toxicity potential of new molecules in pharmaceutical industry is a multi-dimensional task involving predictive systems and screening approaches to aid in the optimization of lead compounds prior to their entry into development phase. Due to the high attrition rate in the pharma industry in last few years, it has become imperative for the nonclinical toxicologist to focus on novel approaches which could be helpful for early screening of drug candidates. The need is that the toxicologists should change their classical approach to a more investigative approach. This review discusses the developments that allow toxicologists to anticipate safety problems and plan ways to address them earlier than ever before. This includes progress in the field of in vitro models, surrogate models, molecular toxicology, 'omics' technologies, translational safety biomarkers, stem-cell based assays and preclinical imaging. The traditional boundaries between teams focusing on efficacy/ safety and preclinical/ clinical aspects in the pharma industry are disappearing, and translational research-centric organizations with a focused vision of bringing drugs forward safely and rapidly are emerging. Today's toxicologist should collaborate with medicinal chemists, pharmacologists, and clinicians and these value-adding contributions will change traditional toxicologists from side-effect identifiers to drug development enablers.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME

This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.