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药物输送中的纳米材料:利用人工智能和大数据进行预测设计
Youngji Han1, Dong Hyun Kim2, Seung Pil Pack2,3
1Bio-Medical Research Institute, Kyungpook National University Hospital, Daegu 41940, Republic of Korea.
International journal of molecular sciences
|November 27, 2025
概括
人工智能 (AI) 和大数据分析正在加速先进的纳米材料药物输送系统的发展. 人工智能模型预测纳米载体的特性,并优化设计,以改善临床转化和患者的结果.
科学领域:
- 纳米技术 纳米技术
- 计算生物学 计算生物学
- 药物输送系统 药物输送系统
背景情况:
- 纳米材料可以精确控制药物输送特性,例如溶解性和稳定性.
- 纳米药物的临床翻译在合成,生物相互作用和监管批准方面面临挑战.
研究的目的:
- 审查人工智能驱动的战略,以优化纳米载体设计和预测其性能.
- 讨论人工智能辅助纳米医学开发的转化和监管视角.
主要方法:
- 整合多维数据集 (物理化学,药物动力学,奥米学,临床前) 用于预测建模.
- 机器学习,深度学习和生成算法的应用,用于纳米载体设计和优化.
- 利用纳米信息平台和大型数据存储库来提高可重现性.
主要成果:
- 人工智能可以预测关键参数,如粒子大小,药物负载和生物分布.
- 生成算法促进了对新型纳米材料化学和架构的探索.
- 纳米信息学改善了数据标准化,可复制性和跨研究比较.
结论:
- 人工智能辅助设计具有很大的潜力,可以克服纳米医药开发中的瓶.
- 这种方法可以带来更高效,可复制和个性化的药物输送系统.
- 跨越纳米技术,人工智能和精密医学加速了从长椅到床边的道路.
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