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June 29, 2026Critical Reviews in Environmental Science and Technology

Artificial intelligence-powered new approach methodologies for assessing combined toxicity of chemical mixtures

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Authors

YLYu-Shun LuLCLe ChenYQYong-zhong Qian

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Overview

Review examines AI methodologies to improve assessment of complex chemical mixtures, suggesting crucial regulatory implications.

Key Points

  • The aim is to evaluate how AI and New Approach Methodologies enhance the assessment of toxicity for chemical mixtures.
  • Review of AI architectures including traditional machine learning, GNNs, and q-RASAR framework.
  • Assessment of capabilities in modeling non-additive effects and regulatory interpretability.
  • Discussion of a closed-loop validation strategy integrating various in vitro and computational techniques.
  • Established critical gaps in the evaluation of contaminant mixtures like microplastics and antibiotics.
  • Proposed regulatory frameworks for standardized validation of AI models in toxicity assessments.
  • Highlighted the need for moving from statistical methods to causal biological proof in risk assessment.

Cite This Study

Lu et al. (2026) studied this question.

synapsesocial.com/papers/6a420ab2f91bb43ea9191e18https://doi.org/10.1080/10643389.2026.2693546
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