@article{2466,
  keywords = {Allergic contact dermatitis; human predictive patch test data, Benchmarking, Databases, Factual, Humans, Patch Tests, Reference data, Reproducibility of Results, Skin, Skin sensitization},
  author = {Judy Strickland and Jaleh Abedini and David G. Allen and John Gordon and Victoria Hull and Nicole C. Kleinstreuer and Hon-Sum Ko and Joanna Matheson and Hermann-Josef Thierse and James Truax and Jens T. Vanselow and Matthias Herzler},
  title = {A database of human predictive patch test data for skin sensitization},
  abstract = {Critical to the evaluation of non-animal tests are reference data with which to assess their relevance. Animal data are typically used because they are generally standardized and available. However, when regulatory agencies aim to protect human health, human reference data provide the benefit of not having to account for possible interspecies variability. To support the evaluation of non-animal approaches for skin sensitization assessment, we collected data from 2277 human predictive patch tests (HPPTs), i.e., human repeat insult patch tests and human maximization tests, for skin sensitization from 1555 publications. We recorded protocol elements and positive or negative outcomes, developed a scoring system to evaluate each test for reliability, and calculated traditional and non-traditional dose metrics. We also traced each test result back to its original report to remove duplicates. The resulting database, which contains information for 1366 unique substances, was characterized for physicochemical properties, chemical structure categories, and protein binding mechanisms. This database is publicly available on the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods website and in the Integrated Chemical Environment to serve as a resource for additional evaluation of alternative methods and development of new approach methodologies for skin sensitization assessments.},
  year = {2023},
  journal = {Archives of Toxicology},
  volume = {97},
  pages = {2825-2837},
  month = {2023-11},
  issn = {1432-0738},
  doi = {10.1007/s00204-023-03530-3},
  language = {eng},
}