Standardizing Extracted Data Using Automated Application of Controlled Vocabularies.

BACKGROUND: Extraction of toxicological end points from primary sources is a central component of systematic reviews and human health risk assessments. To ensure optimal use of these data, consistent language should be used for end point descriptions. However, primary source language describing treatment-related end points can vary greatly, resulting in large labor efforts to manually standardize extractions before data are fit for use. OBJECTIVES: To minimize these labor efforts, we applied an augmented intelligence approach and developed automated tools to support standardization of extracted information via application of preexisting controlled vocabularies. METHODS: We created and applied a harmonized controlled vocabulary crosswalk, consisting of Unified Medical Language System (UMLS) codes, German Federal Institute for Risk Assessment (BfR) DevTox harmonized terms, and The Organization for Economic Co-operation and Development (OECD) end point vocabularies, to roughly 34,000 extractions from prenatal developmental toxicology studies conducted by the National Toxicology Program (NTP) and 6,400 extractions from European Chemicals Agency (ECHA) prenatal developmental toxicology studies, all recorded based on the original study report language. RESULTS: We automatically applied standardized controlled vocabulary terms to 75% of the NTP extracted end points and 57% of the ECHA extracted end points. Of all the standardized extracted end points, about half (51%) required manual review for potential extraneous matches or inaccuracies. Extracted end points that were not mapped to standardized terms tended to be too general or required human logic to find a good match. We estimate that this augmented intelligence approach saved >350 hours of manual effort and yielded valuable resources including a controlled vocabulary crosswalk, organized related terms lists, code for implementing an automated mapping workflow, and a computationally accessible dataset. DISCUSSION: Augmenting manual efforts with automation tools increased the efficiency of producing a findable, accessible, interoperable, and reusable (FAIR) dataset of regulatory guideline studies. This open-source approach can be readily applied to other legacy developmental toxicology datasets, and the code design is customizable for other study types. https://doi.org/10.1289/EHP13215.

Weight of evidence for cross-species conservation of androgen receptor-based biological activity.

The U.S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) is tasked with assessing chemicals for their potential to perturb endocrine pathways, including those controlled by androgen receptor (AR). To address challenges associated with traditional testing strategies, EDSP is considering in vitro high-throughput screening assays to screen and prioritize chemicals more efficiently. The ability of these assays to accurately reflect chemical interactions in nonmammalian species remains uncertain. Therefore, a goal of the EDSP is to evaluate how broadly results can be extrapolated across taxa. To assess the cross-species conservation of AR-modulated pathways, computational analyses and systematic literature review approaches were used to conduct a comprehensive analysis of existing in silico, in vitro, and in vivo data. First, molecular target conservation was assessed across 585 diverse species based on the structural similarity of ARs. These results indicate that ARs are conserved across vertebrates and are predicted to share similarly susceptibility to chemicals that interact with the human AR. Systematic analysis of over 5000 published manuscripts was used to compile in vitro and in vivo cross-species toxicity data. Assessment of in vitro data indicates conservation of responses occurs across vertebrate ARs, with potential differences in sensitivity. Similarly, in vivo data indicate strong conservation of the AR signaling pathways across vertebrate species, although sensitivity may vary. Overall, this study demonstrates a framework for utilizing bioinformatics and existing data to build weight of evidence for cross-species extrapolation and provides a technical basis for extrapolating hAR-based data to prioritize hazard in nonmammalian vertebrate species.

Therapeutic trials for long COVID-19: A call to action from the interventions taskforce of the RECOVER initiative.

Although most individuals recover from acute SARS-CoV-2 infection, a significant number continue to suffer from Post-Acute Sequelae of SARS-CoV-2 (PASC), including the unexplained symptoms that are frequently referred to as long COVID, which could last for weeks, months, or even years after the acute phase of illness. The National Institutes of Health is currently funding large multi-center research programs as part of its Researching COVID to Enhance Recover (RECOVER) initiative to understand why some individuals do not recover fully from COVID-19. Several ongoing pathobiology studies have provided clues to potential mechanisms contributing to this condition. These include persistence of SARS-CoV-2 antigen and/or genetic material, immune dysregulation, reactivation of other latent viral infections, microvascular dysfunction, and gut dysbiosis, among others. Although our understanding of the causes of long COVID remains incomplete, these early pathophysiologic studies suggest biological pathways that could be targeted in therapeutic trials that aim to ameliorate symptoms. Repurposed medicines and novel therapeutics deserve formal testing in clinical trial settings prior to adoption. While we endorse clinical trials, especially those that prioritize inclusion of the diverse populations most affected by COVID-19 and long COVID, we discourage off-label experimentation in uncontrolled and/or unsupervised settings. Here, we review ongoing, planned, and potential future therapeutic interventions for long COVID based on the current understanding of the pathobiological processes underlying this condition. We focus on clinical, pharmacological, and feasibility data, with the goal of informing future interventional research studies.

Evaluation of the fish acute toxicity test for pesticide registration.

The U.S. Environmental Protection Agency (USEPA) uses the in vivo fish acute toxicity test to assess potential risk of substances to non-target aquatic vertebrates. The test is typically conducted on a cold and a warm freshwater species and a saltwater species for a conventional pesticide registration, potentially requiring upwards of 200 or more fish. A retrospective data evaluation was conducted to explore the potential for using fewer fish species to support conventional pesticide risk assessments. Lethal concentration 50% (LC50) values and experimental details were extracted and curated from 718 studies on fish acute toxicity submitted to USEPA. The LC50 data were analysed to determine, when possible, the relative sensitivity of the tested species to each pesticide. One of the tested freshwater species was most sensitive in 85% of those cases. The tested cold freshwater species was the most sensitive overall among cases with established relative sensitivity and was within 3X of the LC50 value of the most sensitive species tested in 98% of those cases. The results support potentially using fewer than three fish species to conduct ecological risk assessments for the registration of conventional pesticides.

Data curation to support toxicity assessments using the Integrated Chemical Environment.

Humans are exposed to large numbers of chemicals during their daily activities. To assess and understand potential health impacts of chemical exposure, investigators and regulators need access to reliable toxicity data. In particular, reliable toxicity data for a wide range of chemistries are needed to support development of new approach methodologies (NAMs) such as computational models, which offer increased throughput relative to traditional approaches and reduce or replace animal use. NAMs development and evaluation require chemically diverse data sets that are typically constructed by incorporating results from multiple studies into a single, integrated view; however, integrating data is not always a straightforward task. Primary study sources often vary in the way data are organized and reported. Metadata and information needed to support interoperability and provide context are often lacking, which necessitates literature research on the assay prior to attempting data integration. The Integrated Chemical Environment (ICE) was developed to support the development, evaluation, and application of NAMs. ICE provides curated toxicity data and computational tools to integrate and explore available information, thus facilitating knowledge discovery and interoperability. This paper describes the data curation workflow for integrating data into ICE. Data destined for ICE undergo rigorous harmonization, standardization, and formatting processes using both automated and manual expert-driven approaches. These processes improve the utility of the data for diverse analyses and facilitate application within ICE or a user's external workflow while preserving data integrity and context. ICE data curation provides the structure, reliability, and accessibility needed for data to support chemical assessments.

Current ecotoxicity testing needs among selected U.S. federal agencies.

U.S. regulatory and research agencies use ecotoxicity test data to assess the hazards associated with substances that may be released into the environment, including but not limited to industrial chemicals, pharmaceuticals, pesticides, food additives, and color additives. These data are used to conduct hazard assessments and evaluate potential risks to aquatic life (e.g., invertebrates, fish), birds, wildlife species, or the environment. To identify opportunities for regulatory uses of non-animal replacements for ecotoxicity tests, the needs and uses for data from tests utilizing animals must first be clarified. Accordingly, the objective of this review was to identify the ecotoxicity test data relied upon by U.S. federal agencies. The standards, test guidelines, guidance documents, and/or endpoints that are used to address each of the agencies' regulatory and research needs regarding ecotoxicity testing are described in the context of their application to decision-making. Testing and information use, needs, and/or requirements relevant to the regulatory or programmatic mandates of the agencies taking part in the Interagency Coordinating Committee on the Validation of Alternative Methods Ecotoxicology Workgroup are captured. This information will be useful for coordinating efforts to develop and implement alternative test methods to reduce, refine, or replace animal use in chemical safety evaluations.

Quantitative in vitro to in vivo extrapolation for developmental toxicity potency of valproic acid analogues.

BACKGROUND: The developmental toxicity potential (dTP) concentration from the devTOX quickPredict (devTOXqP ) assay, a metabolomics-based human induced pluripotent stem cell assay, predicts a chemical's developmental toxicity potency. Here, in vitro to in vivo extrapolation (IVIVE) approaches were applied to address whether the devTOXqP assay could quantitatively predict in vivo developmental toxicity lowest effect levels (LELs) for the prototypical teratogen valproic acid (VPA) and a group of structural analogues. METHODS: VPA and a series of structural analogues were tested with the devTOXqP assay to determine dTP concentration and we estimated the equivalent administered doses (EADs) that would lead to plasma concentrations equivalent to the in vitro dTP concentrations. The EADs were compared to the LELs in rat developmental toxicity studies, human clinical doses, and EADs reported using other in vitro assays. To evaluate the impact of different pharmacokinetic (PK) models on IVIVE outcomes, we compared EADs predicted using various open-source and commercially available PK and physiologically based PK (PBPK) models. To evaluate the effect of in vitro kinetics, an equilibrium distribution model was applied to translate dTP concentrations to free medium concentrations before subsequent IVIVE analyses. RESULTS: The EAD estimates for the VPA analogues based on different PK/PBPK models were quantitatively similar to in vivo data from both rats and humans, where available, and the derived rank order of the chemicals was consistent with observed in vivo developmental toxicity. Different models were identified that provided accurate predictions for rat prenatal LELs and conservative estimates of human safe exposure. The impact of in vitro kinetics on EAD estimates is chemical-dependent. EADs from this study were within range of predicted doses from other in vitro and model organism data. CONCLUSIONS: This study highlights the importance of pharmacokinetic considerations when using in vitro assays and demonstrates the utility of the devTOXqP human stem cell-based platform to quantitatively assess a chemical's developmental toxicity potency.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

U.S. Federal Agency interests and key considerations for new approach methodologies for nanomaterials.

Engineered nanomaterials (ENMs) come in a wide array of shapes, sizes, surface coatings, and compositions, and often possess novel or enhanced properties compared to larger sized particles of the same elemental composition. To ensure the safe commercialization of products containing ENMs, it is important to thoroughly understand their potential risks. Given that ENMs can be created in an almost infinite number of variations, it is not feasible to conduct in vivo testing on each type of ENM. Instead, new approach methodologies (NAMs) such as in vitro or in chemico test methods may be needed, given their capacity for higher throughput testing, lower cost, and ability to provide information on toxicological mechanisms. However, the different behaviors of ENMs compared to dissolved chemicals may challenge safety testing of ENMs using NAMs. In this study, member agencies within the Interagency Coordinating Committee on the Validation of Alternative Methods were queried about what types of ENMs are of agency interest and whether there is agency-specific guidance for ENM toxicity testing. To support the ability of NAMs to provide robust results in ENM testing, two key issues in the usage of NAMs, namely dosimetry and interference/bias controls, are thoroughly discussed.

Performance of the GHS Mixtures Equation for Predicting Acute Oral Toxicity.

Acute oral toxicity classifications are based on the estimated chemical dose causing lethality in 50 % of laboratory animals tested (LD50). Given the large number of pesticide registration applications that require acute toxicity data, an alternative to the in vivo test could greatly reduce animal testing. The United Nations Globally Harmonized System of Classification and Labelling of Chemicals (GHS) Mixtures Equation estimates the acute toxicity of mixtures using the toxicities of mixture components. The goal of this study was to evaluate the concordance of LD50s predicted using the GHS Mixtures Equation and LD50s from the in vivo test results. Using the EPA classification system, concordance was 55 % for the full dataset (N = 671), 52 % for agrochemical formulations (N = 620), and 84 % for antimicrobial cleaning products (N = 51). Most discordant results were from substances LD50 > 2000 mg/kg (limit test) or 2000 < LD50 < 5000 mg/kg that were predicted as LD50 > 5000 mg/kg. A supplementary analysis combining all formulations with an LD50 > 500 mg/kg produced a concordance of 82 %. The lack of more toxic formulations in this dataset prevented a thorough evaluation of the GHS equation for such substances. Accordingly, our results suggest the GHS equation is helpful to predict the toxicity of mixtures, particularly those with lower toxicity.

Analysis of variability in the rabbit skin irritation assay.

The in vivo rabbit test is the benchmark against which new approach methodologies for skin irritation are usually compared. No alternative method offers a complete replacement of animal use for this endpoint for all regulatory applications. Variability in the animal reference data may be a limiting factor in identifying a replacement. We established a curated data set of 2624 test records, representing 990 substances, each tested at least twice, to characterize the reproducibility of the in vivo assay. Methodological deviations from guidelines were noted, and multiple data sets with differing tolerances for deviations were created. Conditional probabilities were used to evaluate the reproducibility of the in vivo method in identification of U.S. Environmental Protection Agency or Globally Harmonized System hazard categories. Chemicals classified as moderate irritants at least once were classified as mild or non-irritants at least 40% of the time when tested repeatedly. Variability was greatest between mild and moderate irritants, which both had less than a 50% likelihood of being replicated. Increased reproducibility was observed when a binary categorization between corrosives/moderate irritants and mild/non-irritants was used. This analysis indicates that variability present in the rabbit skin irritation test should be considered when evaluating nonanimal alternative methods as potential replacements.

An integrated chemical environment with tools for chemical safety testing.

Moving toward species-relevant chemical safety assessments and away from animal testing requires access to reliable data to develop and build confidence in new approaches. The Integrated Chemical Environment (ICE) provides tools and curated data centered around chemical safety assessment. This article describes updates to ICE, including improved accessibility and interpretability of in vitro data via mechanistic target mapping and enhanced interactive tools for in vitro to in vivo extrapolation (IVIVE). Mapping of in vitro assay targets to toxicity endpoints of regulatory importance uses literature-based mode-of-action information and controlled terminology from existing knowledge organization systems to support data interoperability with external resources. The most recent ICE update includes Tox21 high-throughput screening data curated using analytical chemistry data and assay-specific parameters to eliminate potential artifacts or unreliable activity. Also included are physicochemical/ADME parameters for over 800,000 chemicals predicted by quantitative structure-activity relationship models. These parameters are used by the new ICE IVIVE tool in combination with the U.S. Environmental Protection Agency's httk R package to estimate in vivo exposures corresponding to in vitro bioactivity concentrations from stored or user-defined assay data. These new ICE features allow users to explore the applications of an expanded data space and facilitate building confidence in non-animal approaches.

Characterizing sources of variability in zebrafish embryo screening protocols.

There is a need for fast, efficient, and cost-effective hazard identification and characterization of chemical hazards. This need is generating increased interest in the use of zebrafish embryos as both a screening tool and an alternative to mammalian test methods. A Collaborative Workshop on Aquatic Models and 21st Century Toxicology identified the lack of appropriate and consistent testing protocols as a challenge to the broader application of the zebrafish embryo model. The National Toxicology Program established the Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) initiative to address the lack of consistent testing guidelines and identify sources of variability for zebrafish-based assays. This report summarizes initial SEAZIT information-gathering efforts. Investigators in academic, government, and industry laboratories that routinely use zebrafish embryos for chemical toxicity testing were asked about their husbandry practices and standard protocols. Information was collected about protocol components including zebrafish strains, feed, system water, disease surveillance, embryo exposure conditions, and endpoints. Literature was reviewed to assess issues raised by the investigators. Interviews revealed substantial variability across design parameters, data collected, and analysis procedures. The presence of the chorion and renewal of exposure media (static versus static-renewal) were identified as design parameters that could potentially influence study outcomes and should be investigated further with studies to determine chemical uptake from treatment solution into embryos. The information gathered in this effort provides a basis for future SEAZIT activities to promote more consistent practices among researchers using zebrafish embryos for toxicity evaluation.

Evaluation and Optimization of Pharmacokinetic Models for in Vitro to in Vivo Extrapolation of Estrogenic Activity for Environmental Chemicals.

BACKGROUND: To effectively incorporate in vitro data into regulatory use, confidence must be established in the quantitative extrapolation of in vitro activity to relevant end points in animals or humans. OBJECTIVE: Our goal was to evaluate and optimize in vitro to in vivo extrapolation (IVIVE) approaches using in vitro estrogen receptor (ER) activity to predict estrogenic effects measured in rodent uterotrophic studies. METHODS: We evaluated three pharmacokinetic (PK) models with varying complexities to extrapolate in vitro to in vivo dosimetry for a group of 29 ER agonists, using data from validated in vitro [U.S. Environmental Protection Agency (U.S. EPA) ToxCast™ ER model] and in vivo (uterotrophic) methods. In vitro activity values were adjusted using mass-balance equations to estimate intracellular exposure via an enrichment factor (EF), and steady-state model calculations were adjusted using fraction of unbound chemical in the plasma ([Formula: see text]) to approximate bioavailability. Accuracy of each model-adjustment combination was assessed by comparing model predictions with lowest effect levels (LELs) from guideline uterotrophic studies. RESULTS: We found little difference in model predictive performance based on complexity or route-specific modifications. Simple adjustments, applied to account for in vitro intracellular exposure (EF) or chemical bioavailability ([Formula: see text]), resulted in significant improvements in the predictive performance of all models. CONCLUSION: Computational IVIVE approaches accurately estimate chemical exposure levels that elicit positive responses in the rodent uterotrophic bioassay. The simplest model had the best overall performance for predicting both oral (PPK_EF) and injection (PPK_[Formula: see text]) LELs from guideline uterotrophic studies, is freely available, and can be parameterized entirely using freely available in silico tools. https://doi.org/10.1289/EHP1655.

Development and Validation of a Computational Model for Androgen Receptor Activity.

Testing thousands of chemicals to identify potential androgen receptor (AR) agonists or antagonists would cost millions of dollars and take decades to complete using current validated methods. High-throughput in vitro screening (HTS) and computational toxicology approaches can more rapidly and inexpensively identify potential androgen-active chemicals. We integrated 11 HTS ToxCast/Tox21 in vitro assays into a computational network model to distinguish true AR pathway activity from technology-specific assay interference. The in vitro HTS assays probed perturbations of the AR pathway at multiple points (receptor binding, coregulator recruitment, gene transcription, and protein production) and multiple cell types. Confirmatory in vitro antagonist assay data and cytotoxicity information were used as additional flags for potential nonspecific activity. Validating such alternative testing strategies requires high-quality reference data. We compiled 158 putative androgen-active and -inactive chemicals from a combination of international test method validation efforts and semiautomated systematic literature reviews. Detailed in vitro assay information and results were compiled into a single database using a standardized ontology. Reference chemical concentrations that activated or inhibited AR pathway activity were identified to establish a range of potencies with reproducible reference chemical results. Comparison with existing Tier 1 AR binding data from the U.S. EPA Endocrine Disruptor Screening Program revealed that the model identified binders at relevant test concentrations (<100 µM) and was more sensitive to antagonist activity. The AR pathway model based on the ToxCast/Tox21 assays had balanced accuracies of 95.2% for agonist (n = 29) and 97.5% for antagonist (n = 28) reference chemicals. Out of 1855 chemicals screened in the AR pathway model, 220 chemicals demonstrated AR agonist or antagonist activity and an additional 174 chemicals were predicted to have potential weak AR pathway activity.

Advancing toxicology research using in vivo high throughput toxicology with small fish models.

Small freshwater fish models, especially zebrafish, offer advantages over traditional rodent models, including low maintenance and husbandry costs, high fecundity, genetic diversity, physiology similar to that of traditional biomedical models, and reduced animal welfare concerns. The Collaborative Workshop on Aquatic Models and 21st Century Toxicology was held at North Carolina State University on May 5-6, 2014, in Raleigh, North Carolina, USA. Participants discussed the ways in which small fish are being used as models to screen toxicants and understand mechanisms of toxicity. Workshop participants agreed that the lack of standardized protocols is an impediment to broader acceptance of these models, whereas development of standardized protocols, validation, and subsequent regulatory acceptance would facilitate greater usage. Given the advantages and increasing application of small fish models, there was widespread interest in follow-up workshops to review and discuss developments in their use. In this article, we summarize the recommendations formulated by workshop participants to enhance the utility of small fish species in toxicology studies, as well as many of the advances in the field of toxicology that resulted from using small fish species, including advances in developmental toxicology, cardiovascular toxicology, neurotoxicology, and immunotoxicology. We alsoreview many emerging issues that will benefit from using small fish species, especially zebrafish, and new technologies that will enable using these organisms to yield results unprecedented in their information content to better understand how toxicants affect development and health.

A Curated Database of Rodent Uterotrophic Bioactivity.

BACKGROUND: Novel in vitro methods are being developed to identify chemicals that may interfere with estrogen receptor (ER) signaling, but the results are difficult to put into biological context because of reliance on reference chemicals established using results from other in vitro assays and because of the lack of high-quality in vivo reference data. The Organisation for Economic Co-operation and Development (OECD)-validated rodent uterotrophic bioassay is considered the "gold standard" for identifying potential ER agonists. OBJECTIVES: We performed a comprehensive literature review to identify and evaluate data from uterotrophic studies and to analyze study variability. METHODS: We reviewed 670 articles with results from 2,615 uterotrophic bioassays using 235 unique chemicals. Study descriptors, such as species/strain, route of administration, dosing regimen, lowest effect level, and test outcome, were captured in a database of uterotrophic results. Studies were assessed for adherence to six criteria that were based on uterotrophic regulatory test guidelines. Studies meeting all six criteria (458 bioassays on 118 unique chemicals) were considered guideline-like (GL) and were subsequently analyzed. RESULTS: The immature rat model was used for 76% of the GL studies. Active outcomes were more prevalent across rat models (74% active) than across mouse models (36% active). Of the 70 chemicals with at least two GL studies, 18 (26%) had discordant outcomes and were classified as both active and inactive. Many discordant results were attributable to differences in study design (e.g., injection vs. oral dosing). CONCLUSIONS: This uterotrophic database provides a valuable resource for understanding in vivo outcome variability and for evaluating the performance of in vitro assays that measure estrogenic activity. CITATION: Kleinstreuer NC, Ceger PC, Allen DG, Strickland J, Chang X, Hamm JT, Casey WM. 2016. A curated database of rodent uterotrophic bioactivity. Environ Health Perspect 124:556-562; http://dx.doi.org/10.1289/ehp.1510183.

Performance of the BG1Luc ER TA method in a qHTS format.

In 2012, the BG1Luc4E2 estrogen receptor (ER) transactivation (TA) method (BG1Luc ER TA) was accepted by U.S. regulatory agencies and the Organisation for Economic Co-operation and Development to detect substances with ER agonist activity. The method is now part of the Tier 1 testing battery in the Environmental Protection Agency's Endocrine Disruptor Screening Program. The BG1Luc ER TA method uses the BG1 ovarian cell line that endogenously expresses full-length ER (α and ß) and is stably transfected with a plasmid containing four estrogen responsive elements upstream of a luciferase reporter gene. To allow increased throughput and testing efficiency, the BG1Luc ER TA ("BG1 manual") method was adapted for quantitative high-throughput screening (BG1 qHTS) in the U.S. Tox21 testing program. The BG1 qHTS test method was used to test approximately 10,000 chemicals three times each, and concentration-response data (n=15) were analyzed to evaluate test method performance. The balanced accuracy of the BG1 qHTS test method (97% [32/33]) was determined by comparing results to ER TA performance standards for the BG1 manual method. Concordance between the BG1 manual and qHTS methods was 92% (57/62) when calculated for a larger set of non-reference chemicals tested in both methods. These data demonstrate that the performance of the BG1 qHTS is similar to the currently accepted BG1 manual method, thereby establishing the utility of the BG1 qHTS method for identifying ER active environmental chemicals.

Profiling of the Tox21 10K compound library for agonists and antagonists of the estrogen receptor alpha signaling pathway.

The U.S. Tox21 program has screened a library of approximately 10,000 (10K) environmental chemicals and drugs in three independent runs for estrogen receptor alpha (ERα) agonist and antagonist activity using two types of ER reporter gene cell lines, one with an endogenous full length ERα (ER-luc; BG1 cell line) and the other with a transfected partial receptor consisting of the ligand binding domain (ER-bla; ERα ß-lactamase cell line), in a quantitative high-throughput screening (qHTS) format. The ability of the two assays to correctly identify ERα agonists and antagonists was evaluated using a set of 39 reference compounds with known ERα activity. Although both assays demonstrated adequate (i.e. >80%) predictivity, the ER-luc assay was more sensitive and the ER-bla assay more specific. The qHTS assay results were compared with results from previously published ERα binding assay data and showed >80% consistency. Actives identified from both the ER-bla and ER-luc assays were analyzed for structure-activity relationships (SARs) revealing known and potentially novel ERα active structure classes. The results demonstrate the feasibility of qHTS to identify environmental chemicals with the potential to interact with the ERα signaling pathway and the two different assay formats improve the confidence in correctly identifying these chemicals.