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Organoid-Based Testing of Bio-Nano Platforms to Predict Efficacy, Screen Toxicity, and Support Personalized Therapy Selection
To evaluate patient-derived organoids as a translational testing platform for bio-nano drug delivery systems, this study examined whether organoid assays could predict therapeutic efficacy, identify organ-specific toxicity, and support patient-specific nanomedicine selection. The central objective was to determine whether tumor and matched normal organoids could resolve formulation-dependent differences that are often obscured in conventional two-dimensional cultures. Five bio-nano platforms, comprising lipid nanoparticles, polymeric micelles, gold nanorods, mesoporous silica nanoparticles, and liposomes, were systematically exposed to six patient-derived organoid lines representing colorectal, pancreatic, and lung cancer with matched normal intestinal, pancreatic, and airway organoids. High-content imaging, ATP-based viability testing, cleaved-caspase apoptosis quantification, confocal penetration mapping, epithelial barrier measurements, and cytokine profiling were performed. Organoid drug sensitivity scores were integrated with nanoparticle physicochemical attributes and genomic annotations. The organoid panel discriminated nanocarrier efficacy across tumor types, with targeted lipid nanoparticles and polymeric micelles producing the strongest selective tumor killing. Gold nanorods showed deep penetration but limited drug-release-associated efficacy, whereas mesoporous silica nanoparticles produced mixed efficacy with elevated inflammatory signaling in normal organoids. Personalized benefit-risk ranking identified different optimal nanocarriers for each patient-derived model, demonstrating clinically relevant interpatient heterogeneity. Organoid-based testing provides a scalable and patient-relevant strategy for evaluating bio-nano drug delivery systems before clinical translation. By combining efficacy, toxicity, penetration, and patient-specific sensitivity metrics, this platform may reduce late-stage nanomedicine failure and support individualized therapy selection.
EAMD 3
Original Research | Open access | 10 July 2026 | Article: 201