Artificial intelligence (AI) is changing the way chemicals can be tested for safety. Instead of animal testing, new computer-based tools can predict how substances affect human health more quickly, accurately, and ethically. This article explores how various technologies (e.g., intelligent data systems; models that explain their reasoning; AI “agents” that perform simulations) can improve and fundamentally change toxicology. AI is no longer limited to automating traditional workflows, but also supports the interpretation of complex biological data and regulatory decisions.
The publication also introduces a new concept called “e-validation,” in which AI is used to validate toxicological methods and models not just once, but continuously, in real time. This ensures that the models remain up to date and reliable. However, the use of AI in toxicology also raises important questions: Can we trust results that we do not fully understand and comprehend? How do we prevent unfairness or bias in the data? To address this, this paper proposes a “co-pilot” model in which AI supports human experts but does not replace them. With better data sharing, strict ethical principles, and smarter oversight, AI can help make chemical safety testing more human-centered, fair, and effective.
The future of toxicology lies not in imitating old practices, but in reshaping it as an adaptable, transparent, and ethically grounded science that delivers more accurate, comprehensive, and human-centered safety assessments.
Original publication: Luechtefeld, T., Hartung, T. Navigating the AI Frontier in Toxicology: Trends, Trust, and Transformation. Curr Envir Health Rpt 12, 51 (2025). https://doi.org/10.1007/s40572-025-00514-6
