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Updated: May 5, 2026

Eye Irritation Test EIT for Hazard Identification of Eye Irritating Chemicals using Reconstructed Human Cornea-like Epithelial RhCE Tissue Model
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机器学习驱动的眼部刺激毒性的预测:In silico和in vitro研究的整合

Shanshan Chen1, Jiaxin Wang1, Lu Hao2

  • 1School of Basic Medical Sciences, Southwest Medical University, Luzhou 646000, China.

Toxicology and applied pharmacology
|July 4, 2025
PubMed
概括

这项研究引入了一个新的计算和实验框架,用于评估眼部刺激 (EI) 毒性. 该方法用可靠的AI驱动预测和体外验证取代动物试验,增强化学品安全评估.

关键词:
实验验证实验验证的验证眼部刺激毒性 毒性 眼部刺激机器学习 机器学习预测模型的预测模型.

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相关概念视频

Toxicity Testing in Animals01:23

Toxicity Testing in Animals

Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
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