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Figure 6. Challenges and roadmap for AI-driven EV engineering. The roadmap summarizes major barriers and future directions for AI-enabled EV therapeutics. Current limitations include EV data heterogeneity, limited interpretability, insufficient multiscale integration, and translational or regulatory uncertainty. Future progress may depend on standardized, findable, accessible, interoperable, and reusable (FAIR) data, explainable and validated AI, digital-twin and mechanistic modeling, and prospective clinical validation. These advances may support the gradual transition of AI-driven EV engineering from early conceptual frameworks toward more predictive, personalized, and translationally feasible EV nanomedicine. Created in BioRender. AI: Artificial intelligence; EV: extracellular vesicle; FAIR: findable, accessible, interoperable, and reusable.