Access to reliable information on hazardous chemicals remains a critical bottleneck for the circular economy. Globally, around 350,000 chemical substances are registered, yet the majority lack comprehensive data on their hazardous properties.
Existing information is fragmented across databases, safety data sheets, and scientific literature, limiting its practical use for policymakers, industry, and civil society. Addressing this knowledge gap, Formas, Sweden’s government research council for sustainable development, has awarded SEK 3 million to the TRACE AI project—Transparent and Accessible Information for a Chemically Safe Circular Economy—coordinated by the University of Gothenburg through FRAM, the Centre for Future Chemical Risk Assessment and Management.
Set to start in November 2025, the 18-month initiative aims to harness artificial intelligence and data-driven methodologies to improve how chemical information is collected, organized, and interpreted. This comes at a time when regulatory pressures are intensifying: the EU’s Ecodesign for Sustainable Products Regulation (ESPR) mandates increased documentation and traceability of hazardous substances, forcing industries to adopt faster and more reliable approaches to chemical risk assessment.
TRACE AI will explore AI techniques including machine learning, natural language processing, and generative models to identify hazardous substances, assess risks, and inform the design of safer alternatives. By translating dispersed and complex datasets into actionable insights, the project seeks to bridge the gap between scientific knowledge and practical decision-making in industry and policy.
Collaboration under TRACE AI spans the University of Gothenburg, Chalmers University of Technology, Stockholm University, RISE Research Institutes of Sweden, and ChemSec, the International Chemical Secretariat. This multidisciplinary partnership integrates expertise in environmental toxicology, life cycle analysis, environmental economics, chemicals policy, and artificial intelligence, while maintaining a strong focus on stakeholder needs.
Daniel Slunge, project leader and researcher at the University of Gothenburg, emphasized the potential of AI to transform chemical management. “Through TRACE AI, we aim to lay the foundation for a more transparent, reliable, and usable information system that supports safe and sustainable materials management,” Slunge said.
The project will also generate practical insights through case studies in sectors such as plastics, textiles, and food-contact materials, demonstrating AI-based tools in real-world decision-making. Additionally, TRACE AI will assess barriers to adoption and explore applications in low- and middle-income countries, as well as within international environmental agreements.
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