Artificial intelligence as the new frontier in chemical risk assessment - Hartung, Thomas (Frontiers in Artificial Intelligence, 2023)
The rapid progress of AI impacts various areas of life, including toxicology, and promises a major role for AI in future risk assessments. Toxicology has shiQed from a purely empirical science focused on observing chemical exposure outcomes to a data-rich field ripe for AI integraon. AI methods are well-suited to handling and integrang large, diverse data volumes -a key challenge in modern toxicology. Addionally, AI enables Predicve Toxicology, as demonstrated by the automated read-across tool RASAR that achieved 87% balanced accuracy across nine OECD tests and 190,000 chemicals, outperforming animal test reproducibility. AI's ability to handle big data and provide probabilisc outputs facilitates probabilisc risk assessment. Rather than just replicang human skills at larger scales, AI should be viewed as a transformave technology. Despite potenal challenges like model black-boxing and dataset biases, explainable AI (xAI) is emerging to address these issues.