The data is on 4 tabs, separated by species (rat, human) and chemical (EH-TBB and BEH_TEBP). The data is by cell (2-4/skin), and includes %dose in receptor fluid over time, % unabsorbed, % absorbed and % penetrated. This dataset is associated with the following publication: Knudsen, G., M. Hughes, J.M. Sanders, S. Hall, and L. Birnbaum. Estimation of human percutaneous bioavailability for two novel brominated flame retardants, 2-ethylhexyl tetrabromobenzoate (EH-TBB) and bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP), using the parallelogram approach. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 311: 117-127, (2016).

Data includes disposition data of radiolabelled pyrethroids (bifenthrin, deltamethrin, cis-permethrin) following topical application. One dataset is the disposition of pyrethroid-derived radioactivity 24 hr post-application. The second dataset is the disposition of pyrethroid-derived radioactivity 120 hr post-application. This dataset is associated with the following publication: Hughes , M., and B. Edwards. In vivo dermal absorption of pyrethroid pesticides in the rat.. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. Taylor & Francis, Inc., Philadelphia, PA, USA, 79(2): 83-91, (2016).

This data set contains the code for the BDCM human multi-route model written in the programming language acsl. The final published manuscript is provided since it contains all the model parameters and data (from published literature). This dataset is associated with the following publication: Kenyon , E., T.L. Leavens, C. Eklund , and R. Pegram. Development and Application of a Human PBPK Model for Bromodichloromethane (BDCM) to Investigate Impacts of Multi-Route Exposure. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 36(9): 1095-1111, (2015).

Supplementary data for "H.A. Fisher, M.V. Evans, A.L. Bunge, E.A. Cohen Hubal, D.A. Vallero, A compartment model to predict in vitro finite dose absorption of chemicals by human skin, Chemosphere, Volume 349, 2024, 140689, ISSN 0045-6535, https://doi.org/10.1016/j.chemosphere.2023.140689.". This dataset is associated with the following publication: Fisher, H., M. Evans, A. Bunge, E. Cohen-Hubal, and D. Vallero. A compartment model to predict in vitro finite dose absorption of chemicals by human skin. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 349: 140689, (2024).

Complete dataset for "Efficacy of Triethylene Glycol (Grignard Pure) against Bacteriophage MS2 in the Air and on Surfaces". This dataset is associated with the following publication: Ratliff, K., L. Oudejans, J. Archer, M. Calfee, J. Gilberry, D. Hook, W. Schoppman, R. Yaga, L. Brooks, and S. Ryan. Impact of test methodology on the efficacy of triethylene glycol (Grignard Pure) against bacteriophage MS2. AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 57(12): 1178–1185, (2023).

All data tables are available in the publication and uploaded onto ScienceHub. This dataset is associated with the following publication: Bangma, J., T.C. Guillette, M. Strynar, A. Lindstrom, J. McCord, D. Jenkins-Hill, C. Lau, N. Chernoff, and J. Lang. A rapid assessment bioaccumulation screening (RABS) study design for emerging per-and polyfluoroalkyl substances in mice exposed to industrially impacted surface water. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 308(1): 136159, (2022).

Salamander liver and swab data, processed chromatograph data, and code used for figure generation are available from a GitHub repository at: https://github.com/amphibian-exeff/vanmeter_salamander_exposures/. Data, associated metadata, and calculation tools are also available from the corresponding author (rvanmeter2@washcoll.edu). This dataset is associated with the following publication: Van Meter, R., D. Glinski, J. Wanat, S. Purucker, and M. Henderson. Validation of Salamander Dermal Mucus Swabs as a Novel, Nonlethal Approach for Amphibian Metabolomics and Glutathione Analysis Following Pesticide Exposure. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 43(5): 1126-1137, (2024).

*********** Note to Josh Harrill- I don't have a copy of the final manuscript so could you please add the description of this dataset (just delete this comment and enter or cut and paste and then it should be ready to route by clicking on 'Submit for Review' button above) **********. This dataset is associated with the following publication: Nyffeler, J., D. Haggard, C. Willis, W. Setzer, R. Judson, K. Paul-Friedman, L. Everett, and J. Harrill. Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data. SLAS Discovery. SAGE Publications, THOUSAND OAKS, CA, USA, 26(2): 292-308, (2021).

Appendix Skin sensitization data and non‐animal test data for 271 chemicals. This dataset is associated with the following publication: Roberts, D., and G. Patlewicz. Non‐animal assessment of skin sensitization hazard: Is an integrated testing strategy needed, and if so what should be integrated?. JOURNAL OF APPLIED TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 38(1): 41-50, (2017).

Allergic contact dermatitis (ACD) is estimated to constitute about 10-15% of all occupational diseases. Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives. Significant progress has been made in developing and evaluating non-animal test methods. There have been efforts to develop and evaluate the utility of in silico models for skin sensitisation including local and global (Q)SARs as well as expert systems. In this study, we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge based), TIMES-SS (hybrid) and evaluated their performance using 2 large datasets of substances that had been assessed for their skin sensitisation potential in animal models. We considered a model to be successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the outcomes of one another, which ranged from 79% to 86% depending on the dataset. We found that none of the expert systems evaluated was able to achieve such a high balanced accuracy in their global predictions, with balanced accuracies ranging from 56% to 65%. However, for substances within the domain of TIMES-SS, balanced accuracies were found to be 79% and 82%, for the two datasets, in line with the animal data. The expert systems evaluated could be extended in light of the additional data collected as part of this study. The incorrect predictions offer new insights for how the existing alerts within these expert systems could be refined. These datasets also offer exciting opportunities for the development of new models. This dataset is associated with the following publication: Fitzpatrick, J., D. Roberts, and G. Patlewicz. (SAR and QSAR in ENVIRONMENTAL RESEARCH) An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential. SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 29(6): 439-468, (2018).