High-Content Analysis/Screening for Predictive Toxicology: Application to Hepatotoxicity and Genotoxicity

Assessing the combinatorial cytotoxicity of the exogenous contamination with BDE-209, bisphenol A, and acrylamide via high-content analysis

Food is often exposed to multiple types of contaminants, and the coexistence of contaminants may have antagonistic, additive or synergistic effects. This study investigated the combinatorial toxicity of the three most widespread exogenous contaminants, decabrominated diphenyl ether (BDE-209), bisphenol A (BPA), and acrylamide (ACR) to HepG2 cells. A mathematical model (Chou-Talalay) and high-content analysis (HCA) were used to probe the nature of the contaminants' interactions and their cytotoxicity mechanisms, respectively. The results highlighted that for the individual pollutants, the cytotoxicity order was BDE-209> BPA > ACR, and varying combinations of contaminants exhibited additive/synergistic effects. In general, combining multiple contaminants significantly increased intracellular reactive oxygen species (ROS), Ca²⁺ flux, DNA damage and Caspase-3, and decreased mitochondrial membrane potential (MMP) and nucleus roundness, indicating that the additive or synergistic mechanism of the combined contaminations was disturbance to multiple organelles. This study emphasizes the complexity of human exposure to food contaminants and provides a scientific basis for formulating strict regulatory standards.

Comparison of Cellular Morphological Descriptors and Molecular Fingerprints for the Prediction of Cytotoxicity- and Proliferation-Related Assays

Cell morphology features, such as those from the Cell Painting assay, can be generated at relatively low costs and represent versatile biological descriptors of a system and thereby compound response. In this study, we explored cell morphology descriptors and molecular fingerprints, separately and in combination, for the prediction of cytotoxicity- and proliferation-related in vitro assay endpoints. We selected 135 compounds from the MoleculeNet ToxCast benchmark data set which were annotated with Cell Painting readouts, where the relatively small size of the data set is due to the overlap of required annotations. We trained Random Forest classification models using nested cross-validation and Cell Painting descriptors, Morgan and ErG fingerprints, and their combinations. While using leave-one-cluster-out cross-validation (with clusters based on physicochemical descriptors), models using Cell Painting descriptors achieved higher average performance over all assays (Balanced Accuracy of 0.65, Matthews Correlation Coefficient of 0.28, and AUC-ROC of 0.71) compared to models using ErG fingerprints (BA 0.55, MCC 0.09, and AUC-ROC 0.60) and Morgan fingerprints alone (BA 0.54, MCC 0.06, and AUC-ROC 0.56). While using random shuffle splits, the combination of Cell Painting descriptors with ErG and Morgan fingerprints further improved balanced accuracy on average by 8.9% (in 9 out of 12 assays) and 23.4% (in 8 out of 12 assays) compared to using only ErG and Morgan fingerprints, respectively. Regarding feature importance, Cell Painting descriptors related to nuclei texture, granularity of cells, and cytoplasm as well as cell neighbors and radial distributions were identified to be most contributing, which is plausible given the endpoint considered. We conclude that cell morphological descriptors contain complementary information to molecular fingerprints which can be used to improve the performance of predictive cytotoxicity models, in particular in areas of novel structural space.

High-Content Screening for the Detection of Drug-Induced Oxidative Stress in Liver Cells

Drug-induced liver injury (DILI) remains a major cause of drug development failure, post-marketing warnings and restriction of use. An improved understanding of the mechanisms underlying DILI is required for better drug design and development. Enhanced reactive oxygen species (ROS) levels may cause a wide spectrum of oxidative damage, which has been described as a major mechanism implicated in DILI. Several cell-based assays have been developed as in vitro tools for early safety risk assessments. Among them, high-content screening technology has been used for the identification of modes of action, the determination of the level of injury and the discovery of predictive biomarkers for the safety assessment of compounds. In this paper, we review the value of in vitro high-content screening studies and evaluate how to assess oxidative stress induced by drugs in hepatic cells, demonstrating the detection of pre-lethal mechanisms of DILI as a powerful tool in human toxicology.

Models of Idiosyncratic Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a leading cause of attrition during the early and late stages of drug development and after a drug is marketed. DILI is generally classified as either intrinsic or idiosyncratic. Intrinsic DILI is dose dependent and predictable (e.g., acetaminophen toxicity). However, predicting the occurrence of idiosyncratic DILI, which has a very low incidence and is associated with severe liver damage, is difficult because of its complex nature and the poor understanding of its mechanism. Considering drug metabolism and pharmacokinetics, we established experimental animal models of DILI for 14 clinical drugs that cause idiosyncratic DILI in humans, which is characterized by the formation of reactive metabolites and the involvement of both innate and adaptive immunity. On the basis of the biomarker data obtained from the animal models, we developed a cell-based assay system that predicts the potential risks of drugs for inducing DILI. These findings increase our understanding of the mechanisms of DILI and may help predict and prevent idiosyncratic DILI due to certain drugs.

Use of the high-content imaging system equipment to evaluate in vitro infection by Leishmania braziliensis in response to sand fly Nyssomyia neivai saliva

Earlier research has shown that in vivo immunization with sand fly saliva protects the host against infection by parasites of genus Leishmania, and inoculation of saliva along with Leishmania promastigotes favors infection in the host. In this study, High-Content Imaging System was used to demonstrate in vitro that sand fly saliva also promotes infection by these parasites. THP-1 cells were cultured in 96-well microplates and challenged with three strains of Leishmania braziliensis plus four dilutions of Nyssomyia neivai salivary gland extract. High-Content Imaging System equipment (Operetta CLS, Perkin Elmer) was configured to automatically count both cells and parasites inside the microplates and subsequently calculate the Infection Index (II). Results demonstrate that the extract concentration of 1 gland showed greater infection than other dilutions. These findings suggest that sand fly N. neivai saliva has potential for increasing the parasite infection, reinforcing the importance of studying its components. A new method to evaluate Leishmania infection in vitro assays was also presented, broadening this area of study.

Biomimetic Gemcitabine-Lipid Prodrug Nanoparticles for Pancreatic Cancer

Gemcitabine (Gem) is a key drug for pancreatic cancer, yet limited by high systemic toxicity, low bioavailability and poor pharmacokinetic profiles. To overcome these limitations, Gem prodrug amphiphiles were synthesised with oleyl, linoleyl and phytanyl chains. Self-assembly and lyotropic mesophase behaviour of these amphiphiles were examined using polarised optical microscopy and Synchrotron SAXS (SSAXS). Gem-phytanyl was found to form liquid crystalline inverse cubic mesophase. This prodrug was combined with phospholipids and cholesterol to create biomimetic Gem-lipid prodrug nanoparticles (Gem-LPNP), verified by SSAXS and cryo-TEM to form liposomes. In vitro testing of the Gem-LPNP in several pancreatic cancer cell lines showed lower toxicity than Gem. However, in a cell line-derived pancreatic cancer mouse model Gem-LPNP displayed greater tumour growth inhibition than Gem using a fraction (<6 %) of the clinical dose and without any systemic toxicity. The easy production, improved efficacy and low toxicity of Gem-LPNP represents a promising new nanomedicine for pancreatic cancer.

Bioactivity screening of environmental chemicals using imaging-based high-throughput phenotypic profiling

The present study adapted an existing high content imaging-based high-throughput phenotypic profiling (HTPP) assay known as "Cell Painting" for bioactivity screening of environmental chemicals. This assay uses a combination of fluorescent probes to label a variety of organelles and measures a large number of phenotypic features at the single cell level in order to detect chemical-induced changes in cell morphology. First, a small set of candidate phenotypic reference chemicals (n = 14) known to produce changes in the cellular morphology of U-2 OS cells were identified and screened at multiple time points in concentration-response format. Many of these chemicals produced distinct cellular phenotypes that were qualitatively similar to those previously described in the literature. A novel workflow for phenotypic feature extraction, concentration-response modeling and determination of in vitro thresholds for chemical bioactivity was developed. Subsequently, a set of 462 chemicals from the ToxCast library were screened in concentration-response mode. Bioactivity thresholds were calculated and converted to administered equivalent doses (AEDs) using reverse dosimetry. AEDs were then compared to effect values from mammalian toxicity studies. In many instances (68%), the HTPP-derived AEDs were either more conservative than or comparable to the in vivo effect values. Overall, we conclude that the HTPP assay can be used as an efficient, cost-effective and reproducible screening method for characterizing the biological activity and potency of environmental chemicals for potential use in in vitro-based safety assessments.

Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies

Adverse drug reactions, particularly those that result in drug-induced liver injury (DILI), are a major cause of drug failure in clinical trials and drug withdrawals. Hepatotoxicity-mediated drug attrition occurs despite substantial investments of time and money in developing cellular assays, animal models, and computational models to predict its occurrence in humans. Underperformance in predicting hepatotoxicity associated with drugs and drug candidates has been attributed to existing gaps in our understanding of the mechanisms involved in driving hepatic injury after these compounds perfuse and are metabolized by the liver. Herein we assess in vitro, in vivo (animal), and in silico strategies used to develop predictive DILI models. We address the effectiveness of several two- and three-dimensional in vitro cellular methods that are frequently employed in hepatotoxicity screens and how they can be used to predict DILI in humans. We also explore how humanized animal models can recapitulate human drug metabolic profiles and associated liver injury. Finally, we highlight the maturation of computational methods for predicting hepatotoxicity, the untapped potential of artificial intelligence for improving in silico DILI screens, and how knowledge acquired from these predictions can shape the refinement of experimental methods.

Assessing cell-nanoparticle interactions by high content imaging of biocompatible iron oxide nanoparticles as potential contrast agents for magnetic resonance imaging

Stem cell tracking in cellular therapy and regenerative medicine is an urgent need, superparamagnetic iron oxide nanoparticles (IONPs) could be used as contrast agents in magnetic resonance imaging (MRI) that allows visualization of the implanted cells ensuring they reach the desired sites in vivo. Herein, we report the study of the interaction of 3,4-dihydroxyhydrocinnamic acid (DHCA) functionalized IONPs that have desirable properties for T2 - weighted MRI, with bone marrow-derived primary human mesenchymal stem cells (hMSCs). Using the multiparametric high-content imaging method, we evaluate cell viability, formation of reactive oxygen species, mitochondrial health, as well as cell morphology and determine that the hMSCs are minimally affected after labelling with IONPs. Their cellular uptake is visualized by transmission electron microscopy (TEM) and Prussian Blue staining, and quantified using an iron specific colourimetric method. In vitro and in vivo studies demonstrate that these IONPs are biocompatible and can produce significant contrast enhancement in T2-weighted MRI. Iron oxide nanoparticles are detected in vivo as hypointense regions in the liver up to two weeks post injection using 9.4 T MRI. These DHCA functionalized IONPs are promising contrast agents for stem cell tracking by T2-weighted MRI as they are biocompatible and show no evidence of cytotoxic effects on hMSCs.

A High-Content Live-Cell Viability Assay and Its Validation on a Diverse 12K Compound Screen

We have developed a new high-content cytotoxicity assay using live cells, called “ImageTOX.” We used a high-throughput fluorescence microscope system, image segmentation software, and the combination of Hoechst 33342 and SYTO 17 to simultaneously score the relative size and the intensity of the nuclei, the nuclear membrane permeability, and the cell number in a 384-well microplate format. We then performed a screen of 12,668 diverse compounds and compared the results to a standard cytotoxicity assay. The ImageTOX assay identified similar sets of compounds to the standard cytotoxicity assay, while identifying more compounds having adverse effects on cell structure, earlier in treatment time. The ImageTOX assay uses inexpensive commercially available reagents and facilitates the use of live cells in toxicity screens. Furthermore, we show that we can measure the kinetic profile of compound toxicity in a high-content, high-throughput format, following the same set of cells over an extended period of time.

Evolution of Novel 3D Culture Systems for Studies of Human Liver Function and Assessments of the Hepatotoxicity of Drugs and Drug Candidates

The pharmaceutical industry urgently needs reliable pre-clinical models to evaluate the efficacy and safety of new chemical entities before they enter the clinical trials. Development of in vitro model systems that emulate the functions of the human liver organ has been an elusive task. Cell lines exhibit a low drug-metabolizing capacity and primary liver cells rapidly dedifferentiate in culture, which restrict their usefulness substantially. Recently, the development of hepatocyte spheroid cultures has shown promising results. The proteome and transcriptome in the spheroids were similar to the liver tissue, and hepatotoxicity of selected substances was detected at in vivo-relevant concentrations.

Test systems in drug discovery for hazard identification and risk assessment of human drug-induced liver injury

INTRODUCTION

The liver is an important target for drug-induced toxicities. Early detection of hepatotoxic drugs requires use of well-characterized test systems, yet current knowledge, gaps and limitations of tests employed remains an important issue for drug development. Areas Covered: The current state of the science, understanding and application of test systems in use for the detection of drug-induced cytotoxicity, mitochondrial toxicity, cholestasis and inflammation is summarized. The test systems highlighted herein cover mostly in vitro and some in vivo models and endpoint measurements used in the assessment of small molecule toxic liabilities. Opportunities for research efforts in areas necessitating the development of specific tests and improved mechanistic understanding are highlighted. Expert Opinion: Use of in vitro test systems for safety optimization will remain a core activity in drug discovery. Substantial inroads have been made with a number of assays established for human Drug-induced Liver Injury. There nevertheless remain significant gaps with a need for improved in vitro tools and novel tests to address specific mechanisms of human Drug-Induced Liver Injury. Progress in these areas will necessitate not only models fit for application, but also mechanistic understanding of how chemical insult on the liver occurs in order to identify translational and quantifiable readouts for decision-making.

Enniatin B and beauvericin are common in Danish cereals and show high hepatotoxicity on a high-content imaging platform

Mycotoxins are fungi-born metabolites that can contaminate foods through mould-infected crops. They are a significant food/feed-safety issue across the globe and represent a substantial financial burden for the world economy. Moreover, with a changing climate and fungal biota, there is now much discussion about emerging mycotoxins that are measurable at significant levels in crops world-wide. Unfortunately, we still know very little about the bioavailability and toxic potentials of many of these less characterized mycotoxins, including the large family of enniatins. In this study, we present new occurrence data for enniatin A, A1, B, B1 and beauvericin in four Danish crops: oat, wheat, and barley from the 2010 harvest, and rye from 2011 harvest. The occurrence of the four enniatins were B > B1 > A1 > A. Enniatin B was detected in 100% of tested samples regardless of crop type. In addition to occurrence data, we report a proof-of-concept study using a human-relevant high-content hepatotoxicity, or "quadroprobe," assay to screen mycotoxins for their cytotoxic potential. The assay was sensitive for most cytotoxic compounds in the 0.009-100 µM range. Among eight tested mycotoxins (enniatin B, beauvericin, altenariol, deoxynivalenol, aflatoxin B1, andrastin A, citrinin, and penicillic acid), enniatin B and beauvericin showed significant cytotoxicity at a concentration lower than that for aflatoxin B1, which is the archetypal acute hepatotoxic and liver-carcinogenic mycotoxin. Hence, the quadroprobe hepatotoxicity assay may become a valuable assessment tool for toxicity assessment of mycotoxins in the future. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1658-1664, 2017.

In Vitro and In Vivo Experimental Hepatotoxic Models in Liver Research: Applications to the Assessment of Potential Hepatoprotective Drugs

This mini-review highlights our and others’ experience about in vitro and in vivo models that are being used to follow up events of liver injuries under various hepatotoxic agents and potential hepatoprotective drugs. Due to limitations of the outcomes in each model, we focus primarily on two models. First, a developed perfusion method for isolated immobilized hepatocytes that improves the process of oxygenation and helps in end-product removal is of considerable value in improving cell maintenance. This cellular model is presented as a short-term research-scale laboratory bioreactor with various physiological, biochemical, molecular, toxicological and pharmacological applications. Second, the in vivo model of D-galactosamine and lipopolysaccharide (D-GalN/LPS) combination-induced liver damage is described with some details. Recently, we have revealed that resveratrol and other natural polyphenols attenuate D-GalN/LPS-induced hepatitis. Moreover, we reported that D-GalN/LPS down-regulates sirtuin 1 in rat liver. Therefore, we discuss here the role of sirtuin 1 modulation in hepatoprotection. A successful development of pharmacotherapy for liver diseases depends on the suitability of in vitro and in vivo hepatic injury systems. Several models are available to screen the hepatotoxic or hepatoprotective activity of any substance. It is important to combine different methods for confirmation of the findings.

Sandwich-Cultured Hepatocytes as a Tool to Study Drug Disposition and Drug-Induced Liver Injury

Sandwich-cultured hepatocytes (SCH) are metabolically competent and have proper localization of basolateral and canalicular transporters with functional bile networks. Therefore, this cellular model is a unique tool that can be used to estimate biliary excretion of compounds. SCH have been used widely to assess hepatobiliary disposition of endogenous and exogenous compounds and metabolites. Mechanistic modeling based on SCH data enables estimation of metabolic and transporter-mediated clearances, which can be used to construct physiologically based pharmacokinetic models for prediction of drug disposition and drug-drug interactions in humans. In addition to pharmacokinetic studies, SCH also have been used to study cytotoxicity and perturbation of biological processes by drugs and hepatically generated metabolites. Human SCH can provide mechanistic insights underlying clinical drug-induced liver injury (DILI). In addition, data generated in SCH can be integrated into systems pharmacology models to predict potential DILI in humans. In this review, applications of SCH in studying hepatobiliary drug disposition and bile acid-mediated DILI are discussed. An example is presented to show how data generated in the SCH model were used to establish a quantitative relationship between intracellular bile acids and cytotoxicity, and how this information was incorporated into a systems pharmacology model for DILI prediction.

Advances in Engineered Liver Models for Investigating Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a major cause of drug attrition. Testing drugs on human liver models is essential to mitigate the risk of clinical DILI since animal studies do not always suffice due to species-specific differences in liver pathways. While primary human hepatocytes (PHHs) can be cultured on extracellular matrix proteins, a rapid decline in functions leads to low sensitivity (<50%) in DILI prediction. Semiconductor-driven engineering tools now allow precise control over the hepatocyte microenvironment to enhance and stabilize phenotypic functions. The latest platforms coculture PHHs with stromal cells to achieve hepatic stability and enable crosstalk between the various liver cell types towards capturing complex cellular mechanisms in DILI. The recent introduction of induced pluripotent stem cell-derived human hepatocyte-like cells can potentially allow a better understanding of interindividual differences in idiosyncratic DILI. Liver models are also being coupled to other tissue models via microfluidic perfusion to study the intertissue crosstalk upon drug exposure as in a live organism. Here, we review the major advances being made in the engineering of liver models and readouts as they pertain to DILI investigations. We anticipate that engineered human liver models will reduce drug attrition, animal usage, and cases of DILI in humans.

Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

Drug-induced liver injury (DILI) is a major cause of late-stage clinical drug attrition, market withdrawal, black-box warnings, and acute liver failure. Consequently, it has been an area of focus for toxicologists and clinicians for several decades. In spite of considerable efforts, limited improvements in DILI prediction have been made and efforts to improve existing preclinical models or develop new test systems remain a high priority. While prediction of intrinsic DILI has improved, identifying compounds with a risk for idiosyncratic DILI (iDILI) remains extremely challenging because of the lack of a clear mechanistic understanding and the multifactorial pathogenesis of idiosyncratic drug reactions. Well-defined clinical diagnostic criteria and risk factors are also missing. This paper summarizes key data interpretation challenges, practical considerations, model limitations, and the need for an integrated risk assessment. As demonstrated through selected initiatives to address other types of toxicities, opportunities exist however for improvement, especially through better concerted efforts at harmonization of current, emerging and novel in vitro systems or through the establishment of strategies for implementation of preclinical DILI models across the pharmaceutical industry. Perspectives on the incorporation of newer technologies and the value of precompetitive consortia to identify useful practices are also discussed.

In vitro toxicity of cationic micelles and liposomes in cultured human hepatocyte (HepG2) and lung epithelial (A549) cell lines

The aim of this study was to compare the effects of cationic micelle and liposome drug delivery systems on liver and lung cells in a toxicological in vitro screening model, with observations on cytotoxicity and genotoxicity. A screening battery was established for assessment of a broad range of parameters related to adverse effects. Clear concentration response effects were observed related to impairment of mitochondrial function, membrane integrity and oxidative stress markers, but no effect was observed on genotoxicity. The adverse effects were highest for the liposomes. The High Content Screening seems optimal for initial screening of adverse effects, and combined with standard cytotoxicity measurements initial screening can be performed for predictive toxicological screening.

[Establishment of animal models of drug-induced liver injury and analysis of possible mechanisms]

Drug-induced liver injury (DILI) is one of leading causes of attrition during both early and late stages of drug development and postmarketing. DILI is generally classified into the intrinsic and idiosyncratic types. Intrinsic DILI is dose dependent and predictable as exemplified by acetaminophen toxicity. However, the occurrence of idiosyncratic DILI with very low incidence and severe liver damage is difficult to predict because of the complex nature of DILI and poor understanding of its mechanism. In this review, we summarize current knowledge and our accumulated experimental findings on the pathogenic mechanisms of DILI focusing on the reactive metabolites of drugs formed by drug-metabolizing enzymes and immune- and inflammation-related responses. Considering drug metabolism and pharmacokinetics, we have established nonclinical animal models of DILI for 10 types of clinical drug known to cause idiosyncratic DILI in humans. Using animal models, it has been shown that the formation of reactive metabolites and both innate and adaptive immunity are involved in the pathogenesis of drug hepatotoxicity. Based on information on biomarkers obtained from animal models, we developed a cell-based system that predicts the potential DILI risks of drugs. The results of these studies increased our understanding of the mechanisms of DILI and help to predict and prevent idiosyncratic DILI caused by drug candidates.

Inhibition of bile canalicular network formation in rat sandwich cultured hepatocytes by drugs associated with risk of severe liver injury

Idiosyncratic drug-induced liver injury is a clinical concern with serious consequences. Although many preclinical screening methods have been proposed, it remains difficult to identify compounds associated with this rare but potentially fatal liver condition. Here, we propose a novel assay system to assess the risk of liver injury. Rat primary hepatocytes were cultured in a sandwich configuration, which enables the formation of a typical bile canalicular network. From day 2 to 3, test drugs, mostly selected from a list of cholestatic drugs, were administered, and the length of the network was semi-quantitatively measured by immunofluorescence. Liver injury risk information was collected from drug labels and was compared with in vitro measurements. Of 23 test drugs examined, 15 exhibited potent inhibition of bile canalicular network formation (<60% of control). Effects on cell viability were negligible or minimal as confirmed by lactate dehydrogenase leakage and cellular ATP content assays. For the potent 15 drugs, IC50 values were determined. Finally, maximum daily dose divided by the inhibition constant gave good separation of the highest risk of severe liver toxicity drugs such as troglitazone, benzbromarone, flutamide, and amiodarone from lower risk drugs. In conclusion, inhibitory effect on the bile canalicular network formation observed in in vitro sandwich cultured hepatocytes evaluates a new aspect of drug toxicity, particularly associated with aggravation of liver injury.

Recent advances in quantitative high throughput and high content data analysis

INTRODUCTION

High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens.

AREAS COVERED

This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data.

EXPERT OPINION

As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

Novel approaches to pulmonary arterial hypertension drug discovery

INTRODUCTION

Pulmonary arterial hypertension (PAH) is a rare disorder associated with abnormally elevated pulmonary pressures that, if untreated, leads to right heart failure and premature death. The goal of drug development for PAH is to develop effective therapies that halt, or ideally, reverse the obliterative vasculopathy that results in vessel loss and obstruction of blood flow to the lungs.

AREAS COVERED

This review summarizes the current approach to candidate discovery in PAH and discusses the currently available drug discovery methods that should be implemented to prioritize targets and obtain a comprehensive pharmacological profile of promising compounds with well-defined mechanisms.

EXPERT OPINION

To improve the successful identification of leading drug candidates, it is necessary that traditional pre-clinical studies are combined with drug screening strategies that maximize the characterization of biological activity and identify relevant off-target effects that could hinder the clinical efficacy of the compound when tested in human subjects. A successful drug discovery strategy in PAH will require collaboration of clinician scientists with medicinal chemists and pharmacologists who can identify compounds with an adequate safety profile and biological activity against relevant disease mechanisms.

Multiparametric Cell Cycle Analysis Using the Operetta High-Content Imager and Harmony Software with PhenoLOGIC

High-content imaging is a powerful tool for determining cell phenotypes at the single cell level. Characterising the effect of small molecules on cell cycle distribution is important for understanding their mechanism of action especially in oncology drug discovery but also for understanding potential toxicology liabilities. Here, a high-throughput phenotypic assay utilising the PerkinElmer Operetta high-content imager and Harmony software to determine cell cycle distribution is described. PhenoLOGIC, a machine learning algorithm within Harmony software was employed to robustly separate single cells from cell clumps. DNA content, EdU incorporation and pHH3 (S10) expression levels were subsequently utilised to separate cells into the various phases of the cell cycle. The assay is amenable to multiplexing with an additional pharmacodynamic marker to assess cell cycle changes within a specific cellular sub-population. Using this approach, the cell cycle distribution of γH2AX positive nuclei was determined following treatment with DNA damaging agents. Likewise, the assay can be multiplexed with Ki67 to determine the fraction of quiescent cells and with BrdU dual labelling to determine S-phase duration. This methodology therefore provides a relatively cheap, quick and high-throughput phenotypic method for determining accurate cell cycle distribution for small molecule mechanism of action and drug toxicity studies.

High-content screening technology for studying drug-induced hepatotoxicity in cell models

High-content screening is the application of automated microscopy and image analysis to both cell biology and drug discovery. Over the last decade, this technique has emerged as a useful technology that allows the simultaneous measurement of different parameters at a single-cell level. Hepatotoxicity is a compelling reason for drug nonapprovals and withdrawals. It is recognized that the safety of a compound cannot be based on a single in vitro assay, and existing methods are not predictive of drug-induced toxicity. However, different HCS assays have been recently demonstrated as being powerful for identifying different mechanisms implicated in drug-induced toxicity with high sensitivity and specificity. These assays integrate the data obtained from different cell function indicators and can be easily incorporated into basic screening processes for the safety evaluation and selection of drug candidates; thus, they contribute greatly to lessen the likelihood of drug failure. Exploring the use of cellular imaging technology in drug-induced liver injury by reviewing the different tests proposed provides evidence that this technology has a strong impact on drug discovery.

Initiatives in South Africa to enhance the prescribing of generic proton pump inhibitors: findings and implications

Background: There have been multiple reforms in South Africa to conserve resources including policies to enhance generic use, such as compulsory generic substitution and copayments. However, there are concerns with the limited knowledge of their impact. Objective: The objective was to determine utilization and expenditure of different proton pump inhibitors (PPIs). Methodology: A retrospective drug utilization study was conducted on a prescription database of a medical aid administrator in 2010. Results: The limited prescribing of single-sourced PPIs accounted for 21.5% of total prescriptions. The limited use of originators omeprazole and lansoprazole accounted for 1.8 and 1.4% of total prescriptions for the molecule, respectively. Generic prices accounted for 36–68% of the originator in 2010. Patients received on average 2.91 PPI prescriptions during the year. Conclusion: Policies to enhance prescribing of generics appear working. Opportunities exist to further lower generic prices given low prices in some European countries.

Intersection of toxicogenomics and high throughput screening in the Tox21 program: an NIEHS perspective

Humans are exposed to thousands of chemicals with inadequate toxicological data. Advances in computational toxicology, robotic high throughput screening (HTS), and genome-wide expression have been integrated into the Tox21 program to better predict the toxicological effects of chemicals. Tox21 is a collaboration among US government agencies initiated in 2008 that aims to shift chemical hazard assessment from traditional animal toxicology to target-specific, mechanism-based, biological observations using in vitro assays and lower organism models. HTS uses biocomputational methods for probing thousands of chemicals in in vitro assays for gene-pathway response patterns predictive of adverse human health outcomes. In 1999, NIEHS began exploring the application of toxicogenomics to toxicology and recent advances in NextGen sequencing should greatly enhance the biological content obtained from HTS platforms. We foresee an intersection of new technologies in toxicogenomics and HTS as an innovative development in Tox21. Tox21 goals, priorities, progress, and challenges will be reviewed.

High Content Imaging and Analysis Enable Quantitative In Situ Assessment of CYP3A4 Using Cryopreserved Differentiated HepaRG Cells

High-throughput imaging-based hepatotoxicity studies capable of analyzing individual cells in situ hold enormous promise for drug safety testing but are frequently limited by a lack of sufficient metabolically competent human cells. This study examined cryopreserved HepaRG cells, a human liver cell line which differentiates into both hepatocytes and biliary epithelial cells, to determine if these cells may represent a suitable metabolically competent cellular model for novel High Content Analysis (HCA) applications. Characterization studies showed that these cells retain many features characteristic of primary human hepatocytes and display significant CYP3A4 and CYP1A2 induction, unlike the HepG2 cell line commonly utilized for HCA studies. Furthermore, this study demonstrates that CYP3A4 induction can be quantified via a simple image analysis-based method, using HepaRG cells as a model system. Additionally, data demonstrate that the hepatocyte and biliary epithelial subpopulations characteristic of HepaRG cultures can be separated during analysis simply on the basis of nuclear size measurements. Proof of concept studies with fluorescent cell function reagents indicated that further multiparametric image-based assessment is achievable with HepaRG. In summary, image-based screening of metabolically competent human hepatocyte models cells such as HepaRG offers novel approaches for hepatotoxicity assessment and improved drug screening tools.