AI‐Guided Design of pH‐ and Redox‐Responsive Lignin@GO@ZIF‐8 Nanocarriers for Targeted Co‐Delivery of 5‐Fluorouracil and Metformin in Prostate Cancer Therapy

ABSTRACT Prostate cancer therapy is limited by systemic toxicity and inefficient tumor‐selective delivery. Here we report a multi‐stimuli‐responsive nanocomposite, Lignin@GO@ZIF‐8, that co‐delivers 5‐Fluorouracil (5‐FU) and metformin and couples pH‐ and redox‐responsive release. We integrate machine learning (ML) to guide formulation: trained on 500 formulation property pairs with cross‐validation and a held‐out test set, XGBoost achieved the highest predictive performance ( R 2 = 0.86–0.89) for drug loading, encapsulation efficiency, and release rate, with influential features including the ZIF‐8 fraction, graphene oxide (GO) content, particle size, zeta potential, pH, and glutathione concentration. ML‐optimized Lignin@GO@ZIF‐8 exhibited improved loading and tunable release relative to pre‐optimized controls. In vitro, the platform sustained drug release and produced potent anticancer activity, reducing LNCaP viability to 18 ± 3% at 72 h, while showing low cytotoxicity toward non‐malignant cells. These results support a data‐driven framework for rational design of multifunctional, stimuli‐responsive nanomedicine platforms and may help inform future translational strategies for prostate cancer.