Sep 2026· Archives of Toxicology· 0 citations· 60 references
Medicine
TL;DR
This review critically evaluates the evidence base for AI-based toxicity prediction, assesses current challenges and considers the trajectory toward next-generation risk assessment, which requires adherence to the TREAT validation principles and sustained regulatory engagement.
This review discusses recent progress in ML, DL, and AI-based strategies for toxicity prediction, assesses their utility across major toxicity endpoints, and highlights the challenges and future research opportunities in predictive toxicology.
Anjali Mahavar, Atul Patel, Ashish Patel· Current Chemical Biology· 0 citations
Predictive artificial intelligence applications in pollutant hazard assessment, environmental monitoring, exposure modeling, multi-omics integration, and regulatory decision support are examined.
Ehsan Ghassemi Barghi, F. Motafeghi, Jafar Gholami Gharab et al.· Discover Artificial Intellig...· 0 citations
Toxicogenomics integrates high-throughput genomic technologies with toxicology to evaluate molecular responses to chemical and pharmaceutical exposures. The increasing volume and complexity of multi-omics data necessitate advanced computational approaches capable of extracting meaningful and predictive insights. In thi...
Mohammed Monirul Islam, Sibghatullah Muhammad Ali Sangi, Girish Meravanige et al.· Frontiers in Genetics· 0 citations
A paradigm shift toward autonomous scientific agents capable of causal reasoning and end-to-end experimental guidance is highlighted, and persistent challenges are discussed, including data bias, limited interpretability, and in silico-to-wet lab translation.
The increasing burden of persistent organic pollutants, per‐ and polyfluoroalkyl substances, heavy metals, and emerging contaminants represents a global threat to human, animal, and ecosystem health. Current management strategies remain fragmented and reactive, limiting the effectiveness of the One Health paradigm. Thi...
Toxicokinetics (TK) characterizes the absorption, distribution, metabolism, and excretion (ADME) of chemicals in the body and connects exposure with internal dose and potential toxicity. Because in vivo and in vitro TK assays are costly and low-throughput, and demand for emerging chemicals is growing, artificial intell...
Xue Wu, Zhi-Cheng Zhang, Kun Mi et al.· Journal of Environmental Exp...· 0 citations
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