TY - JOUR
KW - AI
KW - Explainable AI
KW - FAIR data
KW - Hazard and risk assessment
KW - Toxicology
KW - Trust
AU - Timothy W. Gant
AU - Alistair Boxall
AU - Daniel Burgwinkel
AU - Maryam Zare Jeddi
AU - Ivo Djidrovski
AU - Steffi Friedrichs
AU - Barry Hardy
AU - Thomas Hartung
AU - Daniela Holland
AU - Andreas Karwath
AU - Anne Kienhuis
AU - Nicole Kleinstreuer
AU - Zhoumeng Lin
AU - Emma L. Marczylo
AU - Antonino Marvuglia
AU - Hua Qian
AU - Bennard van Ravenzwaay
AU - Paul Rees
AU - Haralambos Sarimveis
AU - Tewes Tralau
AU - Lucy Wilmot
AU - Adam Zalewski
AU - David Rouquié
AB - Artificial Intelligence (AI) is increasingly influencing chemical risk assessment, enabling faster, more comprehensive, and potentially more ethical assessments. The application of AI in chemical risk assessment refers to both generative and predictive algorithms encompassing machine learning, to analyse complex chemical, biological, and environmental data and provide insights into adverse effect potential for humans and ecosystems. AI systems support the prediction of chemical hazards, exposure levels, and adverse effects by learning from experimental results, mechanistic models, and regulatory datasets, thereby enhancing the efficiency of safety evaluations.
BT - Archives of Toxicology
DA - 2026-02-17
DO - 10.1007/s00204-025-04286-8
LA - en
N2 - Artificial Intelligence (AI) is increasingly influencing chemical risk assessment, enabling faster, more comprehensive, and potentially more ethical assessments. The application of AI in chemical risk assessment refers to both generative and predictive algorithms encompassing machine learning, to analyse complex chemical, biological, and environmental data and provide insights into adverse effect potential for humans and ecosystems. AI systems support the prediction of chemical hazards, exposure levels, and adverse effects by learning from experimental results, mechanistic models, and regulatory datasets, thereby enhancing the efficiency of safety evaluations.
PY - 2026
ST - Building trust in the integration of artificial intelligence into chemical risk assessment
T2 - Archives of Toxicology
TI - Building trust in the integration of artificial intelligence into chemical risk assessment: findings from the 2024 ECETOC workshop
UR - https://doi.org/10.1007/s00204-025-04286-8
Y2 - 2026-02-23
SN - 1432-0738
ER -