Rui Ye, Yupei Zhang, Wan Xu, Li Lai, Zhongwei Zhang, Yan Chen, Shugang Qin
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.