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The development of treatment methods for complex brain diseases faces significant challenges due to the complex biological structures and the strict blood-brain barrier. Although nanomedicine is promising, traditional research and development models are inefficient. This review introduces a theoretical paradigm of intelligent therapeutics, integrating high-precision brain organoid models, high-throughput screening (HTS/HCS), and artificial intelligence (AI).In this closed-loop workflow, the organoid platform plays a diagnostic role, generating predictive data on nanomedicine performance. Subsequently, AI processes this data to provide treatment guidance, promoting rational drug design, synthesis, and interaction prediction. This AI-driven integration is expected to significantly accelerate the development of precisely targeted and personalized nanomedicine, bringing new hope for the treatment of brain diseases.
