Data and code for "Grace Patlewicz, Ann M. Richard, Antony J. Williams, Richard S. Judson, Russell S. Thomas, Towards reproducible structure-based chemical categories for PFAS to inform and evaluate toxicity and toxicokinetic testing, Computational Toxicology, Volume 24, 2022, 100250, ISSN 2468-1113, https://doi.org/10.1016/j.comtox.2022.100250.". This dataset is associated with the following publication: Patlewicz, G., A. Richard, A. Williams, R. Judson, and R. Thomas. Towards reproducible structure-based chemical categories for PFAS to inform and evaluate toxicity and toxicokinetic testing.. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 24: 100250, (2022).

Bioactivity data for p,p'-DDD and analogues from ToxCast assays conducted in liver cells were sourced from the EPA’s CompTox Chemistry Dashboard. The links also provide access to the ToxCast assay information and annotation data user guide. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).

Bioactivity data for p,p'-DDD and analogues from ToxCast assays conducted in liver cells were sourced from the EPA’s CompTox Chemistry Dashboard. The links also provide access to the ToxCast assay information and annotation data user guide. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).

The dataset contains the outputs for the analogue searches conducted for the chemical of interest, p,p'-DDD. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).

ToxRefDB comprises information from over fifty years of in vivo toxicity data. The database includes information for over 1000 chemicals, and is being used as a primary source of data for evaluating efforts of the ToxCast program [4,5], as well as for numerous predictive and retrospective analyses. This dataset is associated with the following publication: Watford, S., L. Pham, J. Wignall, R. Shin, M.T. Martin, and K. Friedman. ToxRefDB version 2.0: Improved utility for predictive and retrospective toxicology analyses. REPRODUCTIVE TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 89: 145-158, (2019).

We used systematic evidence map methods to summarize the available epidemiological and animal bioassay evidence for an expanded set of ~345 PFAS that were prioritized in 2019 by the EPA’s Center for Computational Toxicology and Exposure (CCTE) for in vitro toxicity and toxicokinetic screening. This work builds upon our previously published evidence map for ~150 PFAS chemicals (Carlson et al. 2022, https://doi.org/10.1289/EHP10343). This dataset is associated with the following publication: Shirke, A., E. Radke-Farabaugh, C. Lin, R. Blain, N. Vetter, c. lemeris, p. hartman, H. Hubbard, M. Angrish, X. Arzuaga Andino, J. Congleton, J. Davis, L. Dishaw, R. Jones, R. Judson, J. Kaiser, A. Kraft, L. Lizarraga, P. Noyes, G. Patlewicz, M. Taylor, A. Williams, K. Chialton, and L. Carlson. Expanded Systematic Evidence Map for Hundreds of Per- and Polyfluoroalkyl Substances (PFAS) and Comprehensive PFAS Human Health Dashboard. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 132(2): CID: 026001, (2024).

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.

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.

Table S1: Tox21 IDs mapped to NCGC IDs, PubChem IDs, and DSSTox IDs, and indicating NCATS, NTP and EPA partner library associations (date stamped February 24, 2020). Table S2: DSSTox TOX21SL list of substance IDs and structure formula, molecular weight, SMILES, InChI, and QSAR-ready SMILES (downloaded January 24, 2020). Table S3: DSSTox TOX21SL DTXSID overlaps with EPA CompTox Dashboard lists (downloaded January 24, 2020). Table S4: Predicted physicochemical properties and toxicities generated from OPERA, T.E.S.T, CORINA, and Derek Nexus models. Table S5: ToxPrint (V2.0_r711) fingerprint file for the TOX21SL chemical list. Table S6: Chemotype enrichment workflow results generated from binarized activity hit calls for ToxCast and Tox21 assay end points (aeids) obtained from EPA’s public ToxCast database, invitroDBv2. Table S7: Tox21 binarized assay hit call matrix for stereo and salt pairs, extracted from EPA’s public ToxCast database, invitroDBv3. This dataset is associated with the following publication: Richard, A., R. Huang, S. Waidyanatha, P. Shinn, B.J. Collins, I. Thillainadarajah, C. Grulke, A. Williams, R. Lougee, R. Judson, K. Houck, M.A. Shobair, C. Yang, J.F. Rathman, A. Yasgar, S.C. Fitzpatrick, A. Simeonov, R. Thomas, K.M. Crofton, R.S. Paules, J.R. Bucher, C.P. Austin, R.J. Kavlock, and R.R. Tice. The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 34(2): 189-216, (2021).

Table S1: Tox21 IDs mapped to NCGC IDs, PubChem IDs, and DSSTox IDs, and indicating NCATS, NTP and EPA partner library associations (date stamped February 24, 2020). Table S2: DSSTox TOX21SL list of substance IDs and structure formula, molecular weight, SMILES, InChI, and QSAR-ready SMILES (downloaded January 24, 2020). Table S3: DSSTox TOX21SL DTXSID overlaps with EPA CompTox Dashboard lists (downloaded January 24, 2020). Table S4: Predicted physicochemical properties and toxicities generated from OPERA, T.E.S.T, CORINA, and Derek Nexus models. Table S5: ToxPrint (V2.0_r711) fingerprint file for the TOX21SL chemical list. Table S6: Chemotype enrichment workflow results generated from binarized activity hit calls for ToxCast and Tox21 assay end points (aeids) obtained from EPA’s public ToxCast database, invitroDBv2. Table S7: Tox21 binarized assay hit call matrix for stereo and salt pairs, extracted from EPA’s public ToxCast database, invitroDBv3. This dataset is associated with the following publication: Richard, A., R. Huang, S. Waidyanatha, P. Shinn, B.J. Collins, I. Thillainadarajah, C. Grulke, A. Williams, R. Lougee, R. Judson, K. Houck, M.A. Shobair, C. Yang, J.F. Rathman, A. Yasgar, S.C. Fitzpatrick, A. Simeonov, R. Thomas, K.M. Crofton, R.S. Paules, J.R. Bucher, C.P. Austin, R.J. Kavlock, and R.R. Tice. The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 34(2): 189-216, (2021).