Assessing skin irritation potential is critical for the safety evaluation of topical drugs and other consumer products such as cosmetics. The use of advanced cellular models, as an alternative to replace animal testing in the safety evaluation for both consumer products and ingredients, is already mandated by law in the European Union (EU) and other countries. However, there has not yet been a large-scale comparison of the effects of topical-use compounds in different cellular skin models. This study assesses the irritation potential of topical-use compounds in different cellular models of the skin that are compatible with high throughput screening (HTS) platforms. A set of 451 topical-use compounds were first tested for cytotoxic effects using two-dimensional (2D) monolayer models of primary neonatal keratinocytes and immortalized human keratinocytes. Forty-six toxic compounds identified from the initial screen with the monolayer culture systems were further tested for skin irritation potential on reconstructed human epidermis (RhE) and full thickness skin (FTS) three-dimensional (3D) tissue model constructs. Skin irritation potential of the compounds was assessed by measuring tissue viability, trans-epithelial electrical resistance (TEER), and secretion of cytokines interleukin 1 alpha (IL-1α) and interleukin 18 (IL-18). Among known irritants, high concentrations of methyl violet and methylrosaniline decreased viability, lowered TEER, and increased IL-1α secretion in both RhE and FTS models, consistent with irritant properties. However, at low concentrations, these two compounds increased IL-18 secretion without affecting levels of secreted IL-1α, and did not reduce tissue viability and TEER, in either RhE or FTS models. This result suggests that at low concentrations, methyl violet and methylrosaniline have an allergic potential without causing irritation. Using both HTS-compatible 2D cellular and 3D tissue skin models, together with irritation relevant activity endpoints, we obtained data to help assess the irritation effects of topical-use compounds and identify potential dermal hazards.

Traditional toxicity testing reliant on animal models is costly and low throughput, posing a significant challenge with the increasing numbers of chemicals that humans are exposed to in the environment. The purpose of this investigation was to build optimal prediction models for various human in vivo/organ-level toxicity end points (extracted from ChemIDPlus) using chemical structure and Tox21 in vitro quantitative high-throughput screening (qHTS) bioactivity assay data. Several supervised machine learning algorithms were applied to model 14 human toxicity end points pertaining to vascular, kidney, ureter and bladder, and liver organ systems. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The top four models, with AUC-ROC values >0.8, were derived for endocrine (0.90 ± 0.00), musculoskeletal (0.88 ± 0.02), peripheral nerve and sensation (0.85 ± 0.01), and brain and coverings (0.83 ± 0.02) toxicities, whereas the best model AUC-ROC values were >0.7 for the remaining 10 toxicities. Model performance was found to be dependent on the specific data set, model type, and feature selection method used. In addition, chemical structure and assay data showed different levels of contribution to the prediction of different toxicity end points. Although in vitro assay data, when combined with chemical structure, slightly improved the predictive accuracy for most end points (11 out of 14), a noteworthy finding was the near equal success of the structure-only models, which do not require Tox21 qHTS screening data, and the relatively poor performance of assay-only models. Thus, the top-performing structure-only models from this study could be applied for hazard screening of large sets of chemicals for potential human toxicity, whereas the largest assay contributions to models (i.e., cellular targets) could be used, along with the top-contributing structural features, to provide insight into toxicity mechanisms.

The more than 80,000 chemicals in commerce present a challenge for hazard assessments that toxicity testing in the 21st century strives to address through high-throughput screening (HTS) assays. Assessing chemical effects on human development adds an additional layer of complexity to the screening, with a need to capture complex and dynamic events essential for proper embryo-fetal development. HTS data from ToxCast/Tox21 informs systems toxicology models, which incorporate molecular targets and biological pathways into mechanistic models describing the effects of chemicals on human cells, 3D organotypic culture models, and small model organisms. Adverse Outcome Pathways (AOPs) provide a useful framework for integrating the evidence derived from these in silico and in vitro systems to inform chemical hazard characterization. To illustrate this formulation, we have built an AOP for developmental toxicity through a mode of action linked to embryonic vascular disruption (Aop43). Here, we review the model for quantitative prediction of developmental vascular toxicity from ToxCast HTS data and compare the HTS results to functional vascular development assays in complex cell systems, virtual tissues, and small model organisms. ToxCast HTS predictions from several published and unpublished assays covering different aspects of the angiogenic cycle were generated for a test set of 38 chemicals representing a range of putative vascular disrupting compounds (pVDCs). Results boost confidence in the capacity to predict adverse developmental outcomes from HTS in vitro data and model computational dynamics for in silico reconstruction of developmental systems biology. Finally, we demonstrate the integration of the AOP and developmental systems toxicology to investigate the unique modes of action of two angiogenesis inhibitors.

Dysregulation of the Wnt/β-catenin signaling pathway has been widely recognized as a pathogenic mechanism for colorectal cancer (CRC). Although numerous Wnt inhibitors have been developed, they commonly suffer from toxicity and unintended effects. Moreover, concerns have been raised in targeting this pathway because of its critical roles in maintaining stem cells and regenerating tissues and organs. On the basis of the anthelmintic drug pyrvinium and previous lead FX1128, we have developed a compound YW2065 (1c) which demonstrated excellent anti-CRC effects in vitro and in vivo. YW2065 achieves its inhibitory activity for Wnt signaling by stabilizing Axin-1, a scaffolding protein that regulates proteasome degradation of β-catenin. Simultaneously, YW2065 also led to the activation of the tumor suppressor AMPK, providing an additional anticancer mechanism. In addition, YW2065 showed favorable pharmacokinetic properties without obvious toxicity. The anti-CRC effect of YW2065 was highlighted by its promising efficacy in a mice xenograft model.

High-content screening (HCS) technology combining automated microscopy and quantitative image analysis can address biological questions in academia and the pharmaceutical industry. Various HCS experimental applications have been utilized in the research field of in vitro toxicology. In this review, we describe several HCS application approaches used for studying the mechanism of compound toxicity, highlight some challenges faced in the toxicological community, and discuss the future directions of HCS in regards to new models, new reagents, data management, and informatics. Many specialized areas of toxicology including developmental toxicity, genotoxicity, developmental neurotoxicity/neurotoxicity, hepatotoxicity, cardiotoxicity, and nephrotoxicity will be examined. In addition, several newly developed cellular assay models including induced pluripotent stem cells (iPSCs), three-dimensional (3D) cell models, and tissues-on-a-chip will be discussed. New genome-editing technologies (e.g., CRISPR/Cas9), data analyzing tools for imaging, and coupling with high-content assays will be reviewed. Finally, the applications of machine learning to image processing will be explored. These new HCS approaches offer a huge step forward in dissecting biological processes, developing drugs, and making toxicology studies easier.

The transforming growth factor beta (TGFβ) superfamily of secreted signaling molecules and their cognate receptors regulate cell fate and behaviors relevant to many developmental and disease processes. Disruption of TGFβ signaling during embryonic development can, for example, affect morphogenesis and differentiation through complex pathways that may be SMAD (Small Mothers Against Decapentaplegic) dependent or SMAD independent. In the present study, the SMAD Binding Element (SBE)-beta lactamase (bla) HEK 293T cell line, which responds to the activation of the SMAD2/3/4 complex, was used in a quantitative high-throughput screening (qHTS) assay to identify potential TGFβ disruptors in the Tox21 10K compound library. From the primary screening we identified several kinase inhibitors, organometallic compounds, and dithiocarbamates (DTCs) that inhibited TGFβ1-induced SMAD signaling of reporter gene activation independent of cytotoxicity. Counterscreen of SBE antagonists on human embryonic neural stem cells demonstrated cytotoxicity, providing additional evidence to support evaluation of these compounds for developmental toxicity. We profiled the inhibitory patterns of putative SBE antagonists toward other developmental signaling pathways, including wingless-related integration site (WNT), retinoic acid α receptor (RAR), and sonic hedgehog (SHH). The profiling results from SBE-bla assay identify chemicals that disrupt TGFβ/SMAD signaling as part of an integrated qHTS approach for prioritizing putative developmental toxicants.

BACKGROUND: Thyroid hormone receptors (TRs) are critical endocrine receptors that regulate a multitude of processes in adult and developing organisms, and thyroid hormone disruption is of high concern for neurodevelopmental and reproductive toxicities in particular. To date, only a small number of chemical classes have been identified as possible TR modulators, and the receptors appear highly selective with respect to the ligand structural diversity. Thus, the question of whether TRs are an important screening target for protection of human and wildlife health remains. OBJECTIVE: Our goal was to evaluate the hypothesis that there is limited structural diversity among environmentally relevant chemicals capable of modulating TR activity via the collaborative interagency Tox21 project. METHODS: We screened the Tox21 chemical library (8,305 unique structures) in a quantitative high-throughput, cell-based reporter gene assay for TR agonist or antagonist activity. Active compounds were further characterized using additional orthogonal assays, including mammalian one-hybrid assays, coactivator recruitment assays, and a high-throughput, fluorescent imaging, nuclear receptor translocation assay. RESULTS: Known agonist reference chemicals were readily identified in the TR transactivation assay, but only a single novel, direct agonist was found, the pharmaceutical betamipron. Indirect activation of TR through activation of its heterodimer partner, the retinoid-X-receptor (RXR), was also readily detected by confirmation in an RXR agonist assay. Identifying antagonists with high confidence was a challenge with the presence of significant confounding cytotoxicity and other, non-TR-specific mechanisms common to the transactivation assays. Only three pharmaceuticals-mefenamic acid, diclazuril, and risarestat-were confirmed as antagonists. DISCUSSION: The results support limited structural diversity for direct ligand effects on TR and imply that other potential target sites in the thyroid hormone axis should be a greater priority for bioactivity screening for thyroid axis disruptors. https://doi.org/10.1289/EHP5314.

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (-)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening.

The inhibition of acetylcholinesterase (AChE) has pharmaceutical applications as well as potential neurotoxic effects. The in vivo metabolites of some chemicals including organophosphorus pesticides can become more potent AChE inhibitors compared to their parental compounds. To account for the effects of biotransformation, we have developed and characterized a high-throughput screening method for identifying AChE inhibitors that become active or more potent following xenobiotic metabolism. In this study, an enzyme-based assay was developed in 1536-well plates using recombinant human AChE combined with human or rat liver microsomes. The AChE activity was measured by two methods with different readouts: colorimetric and fluorescent. The assay exhibited exceptional performance characteristics including large assay signal window, low well-to-well variability and high reproducibility. The performance of the assays with microsomes was characterized by testing a group of known AChE inhibitors including parent compounds and their metabolites. Large potency differences between the parent compounds and the metabolites were observed in the assay with microsome addition. Both assay readouts were required for maximal sensitivity. These results demonstrate that this platform is a promising method to profile large numbers of chemicals that require metabolic activation for inhibiting AChE activity.

The constitutive androstane receptor (CAR; NR1I3) is a nuclear receptor involved in all phases of drug metabolism and disposition. However, recently it's been implicated in energy metabolism, tumor progression, and cancer therapy as well. It is, therefore, important to identify compounds that induce hCAR activation to predict drug-drug interactions and potential therapeutic usage. In this study, we screen the Tox21 10,000 compound collection to characterize hCAR activators. A novel structural cluster of compounds was identified, which included nitazoxanide and tenonitrozole, while known structural clusters, such as flavones and prazoles, were also detected. Four compounds, neticonazole, diphenamid, phenothrin, and rimcazole, have been identified as novel hCAR activators, one of which, rimcazole, shows potential selectivity towards hCAR over its sister receptor, the pregnane X receptor (PXR). All four compounds translocated hCAR from the cytoplasm into the nucleus demonstrating the first step to CAR activation. Profiling these compounds as hCAR activators would enable an estimation of drug-drug interactions, as well as identify prospective therapeutically beneficial drugs.