@article{5211,
  keywords = {3Rs, Artificial intelligence, High content imaging, Imaging-based in vitro methods, Regulatory toxicology, Validation},
  author = {Monica Piergiovanni and Milena Mennecozzi and Erio Barale-Thomas and Davide Danovi and Sebastian Dunst and David Egan and Aurora Fassi and Matthew Hartley and Philipp Kainz and Katharina Koch and Sylvia E. Le Dévédec and Iris Mangas and Elena Miranda and Jo Nyffeler and Enrico Pesenti and Fernanda Ricci and Christopher Schmied and Alexander Schreiner and Nadine Stokar-Regenscheit and Jason R. Swedlow and Virginie Uhlmann and Fredrik C. Wieland and Amy Wilson and Maurice Whelan},
  title = {Bridging imaging-based in vitro methods from biomedical research to regulatory toxicology},
  abstract = {Imaging technologies are being increasingly used in biomedical research and experimental toxicology to gather morphological and functional information from cellular models. There is a concrete opportunity of incorporating imaging-based in vitro methods in international guidelines to respond to regulatory requirements with human relevant data. To translate these methods from R&D to international regulatory acceptance, the community needs to implement test methods under quality management systems, assess inter-laboratory transferability, and demonstrate data reliability and robustness. This article summarises current challenges associated with image acquisition, image analysis, including artificial intelligence, and data management of imaging-based methods, with examples from the developmental neurotoxicity in vitro battery and phenotypic profiling assays. The article includes considerations on specific needs and potential solutions to design and implement future validation and transferability studies.},
  year = {2025},
  journal = {Archives of Toxicology},
  month = {2025-02-13},
  issn = {1432-0738},
  url = {https://doi.org/10.1007/s00204-024-03922-z},
  doi = {10.1007/s00204-024-03922-z},
  language = {en},
}