Advancing the implementation of artificial intelligence in regulatory frameworks for chemical safety assessment by defining robust readiness criteria

Joyce De Paula Souza^1,2*Jonathan Blum^1,2Uko Maran³Sulev Sild³Louis Dawson⁴Aleksandra Čavoški⁴Laura Holden⁴Robert Lee⁴Veronika Plichta⁵Lukas Meusburger⁶Sandrine Fraize-Frontier⁷Alexander Walsh⁷Gilles Riviere⁷Giuseppa Raitano⁸Alessandra Roncaglioni⁸Emma Di Consiglio⁹Olga Tcheremenskaia⁹Cecilia Bossa⁹Lina Wendt-Rasch¹⁰Tomasz Puzyn^11,12*Ellen Fritsche^1,2*

• ¹University of Basel, Basel, Switzerland
• ²Swiss Centre for Applied Human Toxicology, Basel, Switzerland
• ³Institute of Chemistry, University of Tartu, Tartu, Estonia
• ⁴Birmingham Law School, University of Birmingham, Birmingham, United Kingdom
• ⁵Department Risk Assessment, Austrian Agency for Health and Food (AGES), Vienna, Austria
• ⁶Department Risk Assessment, Austrian Agency for Health and Food Safety (AGES), Vienna, Austria
• ⁷French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Maisons-Alfort, France
• ⁸Department of Environmental Health Sciences, Mario Negri Institute for Pharmacological Research, Milan, Italy
• ⁹Environment & Health Department, Italian National Institute of Health (ISS), Rome, Italy
• ¹⁰Swedish Chemicals Agency (KEMI), Stockholm, Sweden
• ¹¹Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
• ¹²QSAR Lab Ltd, Gdańsk, Poland

The integration of artificial intelligence (AI) into chemical risk assessment (CRA) is emerging as a powerful approach to enhance the interpretation of complex toxicological data and accelerate safety evaluations. However, the regulatory uptake of AI remains limited due to concerns about transparency, explainability, and trustworthiness. The European Partnership for the Assessment of Risks from Chemicals (PARC) project ReadyAI was established to address these challenges by developing a readiness scoring system to evaluate the maturity and regulatory applicability of AI-based models in CRA. The project unites a multidisciplinary consortium of academic, regulatory, and legal experts to define transparent and reproducible criteria encompassing data curation, model development, validation, explainability, and uncertainty quantification. Current efforts focus on identifying key priorities, including harmonized terminology, rigorous data quality standards, case studies, and targeted training of regulatory scientists. ReadyAI aims to deliver a practical, evidence-based scoring system that enables regulators to assess whether AI tools are sufficiently reliable for decision-making and guides developers toward compliance with regulatory expectations. By bridging the gap between AI innovation and regulatory applicability, ReadyAI contributes to the responsible integration of AI into chemical safety assessment frameworks, ultimately supporting human and environmental health protection.