Present and future of Al, open science, and transparency in regulatory science

At the 13th Global Summit on Regulatory Science (GSRS23), a pre-summit workshop organized by EBTC and EFSA explored the integration of artificial intelligence (AI), big data, and new approach methodologies (NAMs) into regulatory science. Experts Presentations highlighted how AI can enhance toxicological assessments by improving data processing, enabling predictive modeling, and supporting systematic evidence synthesis. Emphasis was placed on the need for high-quality, interoperable data and FAIR principles to ensure reliable AI outputs. Case studies, such as the ONTOX project, demonstrated practical progress toward animal-free, AI-supported toxicity prediction. Key challenges discussed included data quality and data gaps, legal and ethical considerations, and the need for trust building, standards, and the regulatory readiness for AI. The workshop concluded that while AI holds transformative promise, responsible implementation requires coordinated efforts across science, policy, and regulation.