fig2

Figure 2. AIVC-guided source programming for optimized EV production. This diagram shows how multi-omics datasets from parental cells, including genomic, transcriptomic, proteomic, and metabolic information, could be integrated into AIVC models to predict potential EV changes in response to defined perturbations. AIVC models may use in silico perturbations, such as genetic modulation, environmental changes, or small-molecule treatment, to estimate changes in EV cargo composition, surface features, and secretion output. The predicted outputs can then be compared with experimental data to support model refinement and may help inform subsequent source-cell perturbation and EV production strategies. Created in BioRender. AIVC: Artificial intelligence virtual cell; EV: extracellular vesicle.