类有机物
纳米医学
计算机科学
药物发现
神经科学
医学
个性化医疗
药物开发
精密医学
人工智能
大数据
纳米技术
作者
Rui Ye,Yupei Zhang,Wan Xu,Li Lai,Zhongwei Zhang,Yan Chen,Shugang Qin
出处
期刊:Theranostics
[Ivyspring International Publisher]
日期:2025-11-07
卷期号:16 (2): 876-897
被引量:3
摘要
Developing therapies for complex brain diseases faces significant challenges due to biological complexity and the stringent blood-brain barrier. While nanomedicine holds promise, traditional R&D paradigms suffer from inefficiency. This review introduces an intelligent theranostic paradigm that integrates high-fidelity brain organoid models, high-throughput screening (HTS/HCS), and Artificial Intelligence (AI). In this closed-loop workflow, organoid platforms serve a diagnostic role, generating predictive data on nanomedicine performance. AI then provides therapeutic guidance by processing this data to drive rational drug design, synthesis, and interaction prediction. This AI-driven convergence is poised to significantly accelerate the development of precisely targeted and individualized nanomedicines, offering new hope for breakthroughs in treating brain diseases.
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