TY - JOUR
KW - 3Rs
KW - Artificial intelligence
KW - High content imaging
KW - Imaging-based in vitro methods
KW - Regulatory toxicology
KW - Validation
AU - Monica Piergiovanni
AU - Milena Mennecozzi
AU - Erio Barale-Thomas
AU - Davide Danovi
AU - Sebastian Dunst
AU - David Egan
AU - Aurora Fassi
AU - Matthew Hartley
AU - Philipp Kainz
AU - Katharina Koch
AU - Sylvia E. Le Dévédec
AU - Iris Mangas
AU - Elena Miranda
AU - Jo Nyffeler
AU - Enrico Pesenti
AU - Fernanda Ricci
AU - Christopher Schmied
AU - Alexander Schreiner
AU - Nadine Stokar-Regenscheit
AU - Jason R. Swedlow
AU - Virginie Uhlmann
AU - Fredrik C. Wieland
AU - Amy Wilson
AU - Maurice Whelan
AB - 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.
BT - Archives of Toxicology
DA - 2025-02-13
DO - 10.1007/s00204-024-03922-z
LA - en
N2 - 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.
PY - 2025
T2 - Archives of Toxicology
TI - Bridging imaging-based in vitro methods from biomedical research to regulatory toxicology
UR - https://doi.org/10.1007/s00204-024-03922-z
Y2 - 2025-02-25
SN - 1432-0738
ER -