ToxCast high-throughput assay information including assay annotation user guide, assay target information, study design information and quality statistics on the assays.Science Inventory, CCTE products: https://cfpub.epa.gov/si/si_public_search_results.cfm?advSearch=true&showCriteria=2&keyword=CCTE&TIMSType=&TIMSSubTypeID=&epaNumber=&ombCat=Any&dateBeginPublishedPresented=07/01/2017&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&DEID=&personName=&personID=&role=Any&journalName=&journalID=&publisherName=&publisherID=&sortBy=pubDate&count=25

ToxCast is used as a cost-effective approach for efficiently prioritizing the toxicity testing of thousands of chemicals. It uses data from state-of-the-art high throughput screening (HTS) bioassay and builds computational models to forecast potential chemical toxicity in humans. ToxRefDB stores data related to ToxCast.

ToxCast high-throughput assay information including assay annotation user guide, assay target information, study design information and quality statistics on the assays. This version is Mac compatible.

Background: Chemical toxicity testing is being transformed by advances in biology and computer modeling, concerns over animal use and the thousands of environmental chemicals lacking toxicity data. EPA's ToxCast program aims to address these concerns by screening and prioritizing chemicals for potential human toxicity using in vitro assays and in silico approaches. Objectives: This project aims to evaluate the use of in vitro assays for understanding the types of molecular and pathway perturbations caused by environmental chemicals and to build initial prioritization models of in vivo toxicity. Methods: We tested 309 mostly pesticide active chemicals in 467 assays across 9 technologies, including high-throughput cell-free assays and cell-based assays in multiple human primary cells and cell lines, plus rat primary hepatocytes. Both individual and composite scores for effects on genes and pathways were analyzed. Results: Chemicals display a broad spectrum of activity at the molecular and pathway levels. Many expected interactions are seen, including endocrine and xenobiotic metabolism enzyme activity. Chemicals range in promiscuity across pathways, from no activity to affecting dozens of pathways. We find a statistically significant inverse association between the number of pathways perturbed by a chemical at low in vitro concentrations and the lowest in vivo dose at which a chemical causes toxicity. We also find associations between a small set in vitro assays and rodent liver lesion formation. Conclusions: This approach promises to provide meaningful data on the thousands of untested environmental chemicals, and to guide targeted testing of environmental contaminants.

Supplemental files to accompany the manuscript: Feshuk et al., "The ToxCast Pipeline: Updates to Curve-fitting Approaches and Database Structure", DOI https://doi.org/10.3389/ftox.2023.1275980, PMC10552852. This dataset is associated with the following publication: Feshuk, M., L. Kolaczkowski, K. Dunham, S. Davidson-Fritz, K. Carstens, J. Brown, R. Judson, and K. Friedman. The ToxCast Pipeline: Updates to Curve-fitting Approaches and Database Structure. Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 5: 1275980, (2023).

ToxCast high-throughput assay information including assay annotation user guide, assay target information, study design information and quality statistics on the assays.

A data set of 500 chemicals evaluated for their ability to induce cleft palate in animal prenatal developmental studies was compiled from Toxicity Reference Database and the biomedical literature, which included 63 cleft palate active and 437 inactive chemicals. To characterize the potential molecular targets for chemical‐induced cleft palate, we mined the ToxCast high‐throughput screening database for patterns and linkages in bioactivity profiles and chemical structural descriptors. The following datasets can be obtained via the links and files in the Data section: Phase II ToxCast assay data results (Judson et al., 2010); The Gene Score data set derived from ToxCast; ToxRefDB version 1 (Knudsen et al., 2009; Martin, Judson, et al., 2009); The ToxPrint chemotypes (Yang et al., 2015). This dataset is associated with the following publication: Baker, N., N. Sipes, J. Franzosa, D. Belair, B. Abbott, R. Judson, and T. Knudsen. Characterizing cleft palate toxicants using ToxCast data, chemical structure, and the biomedical literature. Birth Defects Research. John Wiley & Sons, Inc., Hoboken, NJ, USA, 1-21, (2019).

Air pollution poses a major threat to global public health. Although there have been a few investigations into the relationships between organic pollutants and adverse outcomes, the responsible components and molecular mechanisms may be ignored. In this study, a suspect screening method combining comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOF MS) with the Toxicity Forecaster (ToxCast) database was applied to analyze complex hydrophobic compounds in ambient air and prospectively figure out toxicologically significant compounds. Seventy-six ToxCast compounds were screened, including seven pollutants receiving less attention and five chemicals never published in the air previously. Given the concentrations, bioactivities, as well as absorption, distribution, metabolism, and excretion properties in vivo, 29 contaminants were assigned high priority since they had active biological effects in the vascular, lung, liver, kidney, prostate, and bone tissues. Phenotypic linkages of key pollutants to potential mechanistic pathways were explored by systems toxicology. A total of 267 chemical–effect pathways involving 29 toxicants and 31 molecular targets were mapped in bipartite network, in which 12 key pathogenic pathways were clarified, which not only provided evidence supporting the previous hypothesis but also provided new insights into the molecular targets. The results would facilitate the development of pollutant priority control, population intervention, and clinical therapeutic strategies so as to substantially reduce human health hazards induced by urban air.

Thousands of chemicals are directly added to or come in contact with food, many of which have undergone little to no toxicological evaluation. The landscape of the food-relevant chemical universe was evaluated using cheminformatics, and subsequently the bioactivity of food-relevant chemicals across the publicly available ToxCast highthroughput screening program was assessed. In total, 8659 food-relevant chemicals were compiled including direct food additives, food contact substances, and pesticides. Of these food-relevant chemicals, 4719 had curated structure definition files amenable to defining chemical fingerprints, which were used to cluster chemicals using a selforganizing map approach. Pesticides, and direct food additives clustered apart from one another with food contact substances generally in between, supporting that these categories not only reflect different uses but also distinct chemistries. Subsequently, 1530 food-relevant chemicals were identified in ToxCast comprising 616 direct food additives, 371 food contact substances, and 543 pesticides. Bioactivity across ToxCast was filtered for cytotoxicity to identify selective chemical effects. Initiating analyses from strictly chemical-based methodology or bioactivity/cytotoxicity-driven evaluation presents unbiased approaches for prioritizing chemicals. Although bioactivity in vitro is not necessarily predictive of adverse effects in vivo, these data provide insight into chemical properties and cellular targets through which foodrelevant chemicals elicit bioactivity. This dataset is associated with the following publication: Karmaus , A., D. Filer , M. Martin , and K. Houck. (FOOD AND CHEMICAL TOXICOLOGY) Evaluation of food-relevant chemicals in the ToxCast high-throughput screening program. FOOD AND CHEMICAL TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 92: 188-196, (2016).

Abbreviations and data for manuscript Figures in the main text and supplemental. This dataset is associated with the following publication: Stoker, T., J. Want, A. Murr, J. Bailey, and A.R. Buckalew. High-Throughput Screening of ToxCast PFAS Chemical Library for Potential Inhibitors of the Human Sodium Iodide Symporter. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 36(3): 380-389, (2023).

Humans spend most of their time indoors and thus have long-term exposure to chemicals. Dust is a sink for most indoor chemicals, and its ingestion is an important pathway for chemical uptake. Therefore, the chemical atlas from dust is an ideal environmental sample to investigate the indoor exposome and associated risk. In this study, we aimed to establish an indoor exposome database through comprehensive data mining on the occurrence of identified compounds in dust, and we prioritize chemicals of health concern. Through an extensive literature review (2849 articles), 355 chemicals and their concentrations were documented and analyzed for human exposure. Together with 81 compounds without concentration and 75 volatile organic compounds, we have established an indoor exposome database with 511 chemicals. Sixteen toxicological end points were selected for toxicity prioritization. Toxic equivalency factor (TEF)-based toxicity, calculated from EPA’s ToxCast database, revealed a comprehensive atlas of the chemicals that had a primary contribution. Many of the prioritized compounds are currently neglected or are not actively studied. Overall, this investigation provides one of the most comprehensive analyses on chemical occurrence in indoor dust and prioritizes their chemical toxicity. Our findings can be used as a database for future exposome studies of the indoor environment and provide guidance for indoor risk assessments.

Previous work identified a ‘cytotoxic burst’ (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase).

This dataset is associated with the following publication: Fay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 500-515, (2018).

The US EPA Toxicity Forecasting (ToxCast) project has involved the generation of large amount of high throughput in vitro data (Over 4000 chemicals tested in between 100 and 700 assays). This data is generated in a consistent manner, and includes a wide variety of chemicals including industrial and consumer products, food additives, pesticides, and drugs. These chemicals were not chosen because they were expected to be active, resulting in a database containing a balance of positive and negative data points. As such this data is useful for computational model construction. This in vitro data has been used at the EPA and elsewhere in modelling approaches, including computational modelling for specific target binding as biological descriptors for toxicity prediction, and pharmacokinetic modelling of human dose responses. All analyses in the generation of the burst flag hit-call matrix and extraction of chemicals for the targets in this study (AR and GR) were performed using R v3.1.2. This dataset is associated with the following publication: Allen, T.E., M.D. Nelms, S.W. Edwards, J.M. Goodman, S. Gutsell, and P.J. Russell. In Silico Guidance for In Vitro Androgen and Glucocorticoid Receptor ToxCast Assays. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(12): 7461-7470, (2020).

The tcpl package provides a set of tools for processing and modeling high-throughput and high-content chemical screening data.

This dataset is associated with the following publication: Filer, D.L., P. Kothiya, R.W. Setzer, R.S. Judson, and M.T. Martin. (BIOINFORMATICS) tcpl: The ToxCast Pipeline for High-Throughput Screening Data. BIOINFORMATICS. Oxford University Press, Cary, NC, USA, 1-3, (2016).

Understanding potential health risks is a significant challenge due to the large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phases I and II of the U.S. EPA’s ToxCast project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical–assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9 and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous but distinctly different patterns of activity, whereas many of the pharmaceutical compounds showed promiscuous activity across GPCRs. Literature analysis confirmed

50% of the activities for the most potent chemical–assay pairs (54) but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical–target combinations clustered with known chemical–target interactions. Results from this large inventory of chemical–biological interactions can inform read-across methods as well as link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities.

This file contains the data used to generate hit calls from neural activity recordings on microelectrode array (MEA) plates treated with ToxCast compounds at a single concentration.

This dataset is associated with the following publication: Strickland, J., M. Martin, A. Richard, K. Houck, and T. Shafer. Screening the ToxCast phase II libraries for alterations in network function using cortical neurons grown on multi-well microelectrode array (mwMEA) plates. Archives of Toxicology. Springer, New York, NY, USA, 92(1): 487-500, (2018).

There is a growing need in the field of exposure science for monitoring methods that rapidly screen environmental media for suspect contaminants. Measurement and analysis platforms, based on high resolution mass spectrometry (HRMS), now exist to meet this need. Here we describe results of a study that links HRMS data with exposure predictions from the U.S. EPA's ExpoCast™ program and in vitro bioassay data from the U.S. interagency Tox21 consortium. Vacuum dust samples were collected from 56 households across the U.S. as part of the American Healthy Homes Survey (AHHS). Sample extracts were analyzed using liquid chromatography time-of-flight mass spectrometry (LC–TOF/MS) with electrospray ionization. On average, approximately 2000 molecular features were identified per sample (based on accurate mass) in negative ion mode, and 3000 in positive ion mode. Exact mass, isotope distribution, and isotope spacing were used to match molecular features with a unique listing of chemical formulas extracted from EPA's Distributed Structure-Searchable Toxicity (DSSTox) database. A total of 978 DSSTox formulas were consistent with the dust LC–TOF/molecular feature data (match score ≥ 90); these formulas mapped to 3228 possible chemicals in the database. Correct assignment of a unique chemical to a given formula required additional validation steps. Each suspect chemical was prioritized for follow-up confirmation using abundance and detection frequency results, along with exposure and bioactivity estimates from ExpoCast and Tox21, respectively. Chemicals with elevated exposure and/or toxicity potential were further examined using a mixture of 100 chemical standards. A total of 33 chemicals were confirmed present in the dust samples by formula and retention time match; nearly half of these do not appear to have been associated with house dust in the published literature. Chemical matches found in at least 10 of the 56 dust samples include Piperine, N,N-Diethyl-m-toluamide (DEET), Triclocarban, Diethyl phthalate (DEP), Propylparaben, Methylparaben, Tris(1,3-dichloro-2-propyl)phosphate (TDCPP), and Nicotine. This study demonstrates a novel suspect screening methodology to prioritize chemicals of interest for subsequent targeted analysis. The methods described here rely on strategic integration of available public resources and should be considered in future non-targeted and suspect screening assessments of environmental and biological media.

This dataset is associated with the following publication: Rager, J.E., M. Strynar , S. Liang, R.L. McMahen, A. Richard , C.M. Grukle, J. Wambaugh , K. Isaacs , R. Judson , A. Williams , and J. Sobus. Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 88: 269-280, (2016).

Excel file containing ToxCast bioactivity data for carbaryl, celecoxib, chromium triacetate, HgCl2, nonylphenol, pentachlorophenol, PFOA, PFOS, pioglitazone, sodium dichromate, TCDD. The .zip file contains SeqAPASS results for multiple protein targets. This dataset is associated with the following publication: Schaupp, C., C. Lalone, B. Blackwell, G. Ankley, and D. Villeneuve. Leveraging ToxCast data and protein sequence conservation to complement aquatic life criteria derivation. Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, USA, 19(1): 224-238, (2023).

These are the raw data files for TOXSCI manuscript 19-0578 entitled, “Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries”: Description from readme.txt file: 1) sc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 1 single-concentration RSA screening of 1,042 Toxcast Phase I and II chemicals 2) mc_seahorse.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 2 multi-concentration RSA screening of 249 actives from tier 1 3) EFA.lvl0.merged.data.csv- contains all mapped raw OCR data from tier 3 EFA screening of 149 putative electron transport chain inhibitors 4) mc5_mc6_ncct_mito_nov2019.csv- level 5 and 6 outputs from ToxCast pipeline (tcpl) analysis 5) RawMC3_ToxCast_by_aeid.csv- level 3 tcpl outputs for all mitochondrial ToxCast assays 6) RawMC5_ToxCast_by_aeid.csv- level 5 tcpl outputs for all mitochondrial ToxCast assays 7) ref.set.chems.csv- sixty reference chemicals used to compared assay performance 8) study_code.R- R script used to analyze data and generate figures and tables. This dataset is associated with the following publication: Hallinger, D., H. Lindsay, K. Friedman, D. Suarez, and S. Simmons. Respirometric Screening and Characterization of Mitochondrial Toxicants Within the ToxCast Phase I and II Chemical Libraries. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 176(1): 175-192, (2020).

Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb.Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting.Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.