Automated Author Profile

Sayre, Risa R.

Current S-Index

2.0

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.0

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Insights derived from testing a library of per- and polyfluoroalkyl substances (PFAS) in a battery of new approach methods (NAMs)

Per- and polyfluoroalkyl substances (PFAS) comprise a large class of human-made chemicals that are in widespread use and present concerns for persistence, bioaccumulation and toxicity. Whilst a handful of PFAS have been characterized for their hazard profiles, the vast majority of PFAS have not been extensively studied. A comprehensive evaluation to characterize the hazard profiles of the thousands of available PFAS would require extensive resources in terms of cost, number of animals and time. An alternative and more efficient approach is to develop a structural chemical categorization approach to prioritize which PFAS or categories of PFAS should be subject to additional study. To that end, the U.S. Environmental Protection Agency (EPA), in collaboration with the National Institute of Environmental Health Sciences (NIEHS) Division of Translational Toxicology (DTT), initiated a research project in 2018 to screen approximately 150 PFAS through a battery of alternative model organisms, in vitro cell and biochemical assays, and in vitro toxico kinetic (TK) assays in order to inform chemical category and read-across approaches. The aim of this review summarizes the experimental testing undertaken, how data were processed, what insights were derived from a category perspective and how these might potentially inform subsequent tiered testing.

Authors

  • Patlewicz, Grace ;
  • Judson, Richard ;
  • Friedman, Katie Paul ;
  • Wetmore, Barbara A. ;
  • DeVito, Michael J. ;
  • Harrill, Joshua A. ;
  • Carstens, Kelly E. ;
  • Houck, Keith A. ;
  • Wambaugh, John F. ;
  • Padilla, Stephanie ;
  • Britton, Katy N. ;
  • Shafer, Timothy J. ;
  • Degitz, Sigmund ;
  • Nyffeler, Jo ;
  • Kreutz, Anna ;
  • Richard, Ann M. ;
  • Williams, Antony J. ;
  • Coutros, Katherine ;
  • Hornung, Michael W. ;
  • Cowden, John ;
  • Everett, Logan J. ;
  • Willis, Clinton M. ;
  • Smeltz, Marci G. ;
  • Clifton, M. Scott ;
  • Feshuk, Madison ;
  • Wall, Jonathan T. ;
  • Sayre, Risa R. ;
  • Brown, Jason ;
  • Thomas, Russell S.
1 Citation0 Mentions85% FAIR1.0 Dataset Index
10.6084/m9.figshare.294878582025

Insights derived from testing a library of per- and polyfluoroalkyl substances (PFAS) in a battery of new approach methods (NAMs)

Per- and polyfluoroalkyl substances (PFAS) comprise a large class of human-made chemicals that are in widespread use and present concerns for persistence, bioaccumulation and toxicity. Whilst a handful of PFAS have been characterized for their hazard profiles, the vast majority of PFAS have not been extensively studied. A comprehensive evaluation to characterize the hazard profiles of the thousands of available PFAS would require extensive resources in terms of cost, number of animals and time. An alternative and more efficient approach is to develop a structural chemical categorization approach to prioritize which PFAS or categories of PFAS should be subject to additional study. To that end, the U.S. Environmental Protection Agency (EPA), in collaboration with the National Institute of Environmental Health Sciences (NIEHS) Division of Translational Toxicology (DTT), initiated a research project in 2018 to screen approximately 150 PFAS through a battery of alternative model organisms, in vitro cell and biochemical assays, and in vitro toxico kinetic (TK) assays in order to inform chemical category and read-across approaches. The aim of this review summarizes the experimental testing undertaken, how data were processed, what insights were derived from a category perspective and how these might potentially inform subsequent tiered testing.

Authors

  • Patlewicz, Grace ;
  • Judson, Richard ;
  • Friedman, Katie Paul ;
  • Wetmore, Barbara A. ;
  • DeVito, Michael J. ;
  • Harrill, Joshua A. ;
  • Carstens, Kelly E. ;
  • Houck, Keith A. ;
  • Wambaugh, John F. ;
  • Padilla, Stephanie ;
  • Britton, Katy N. ;
  • Shafer, Timothy J. ;
  • Degitz, Sigmund ;
  • Nyffeler, Jo ;
  • Kreutz, Anna ;
  • Richard, Ann M. ;
  • Williams, Antony J. ;
  • Coutros, Katherine ;
  • Hornung, Michael W. ;
  • Cowden, John ;
  • Everett, Logan J. ;
  • Willis, Clinton M. ;
  • Smeltz, Marci G. ;
  • Clifton, M. Scott ;
  • Feshuk, Madison ;
  • Wall, Jonathan T. ;
  • Sayre, Risa R. ;
  • Brown, Jason ;
  • Thomas, Russell S.
1 Citation0 Mentions85% FAIR1.0 Dataset Index
10.6084/m9.figshare.29487858.v12025