ARTIFICIAL INTELLIGENCE–ENABLED SUSTAINABLE NANOMEDICINE: GREEN CARBON DOTS FOR SMART DRUG DELIVERY

The rapid advancement of nanomedicine has improved drug delivery; however, conventional nanoparticle development remains limited by trial-and-error optimization, scalability constraints, and environmental concerns. Green nanotechnology offers a sustainable alternative through the use of biodegradable materials, renewable precursors, and environmentally benign synthesis approaches. Among emerging sustainable nanomaterials, green carbon dots have attracted increasing interest because of their biocompatibility, tunable surface chemistry, intrinsic fluorescence, and relatively low toxicity. Nevertheless, precise control of their physicochemical and biological properties remains challenging. Artificial intelligence (AI), particularly machine learning and data-driven modeling, provides opportunities for predictive formulation design, optimization of nanocarrier properties, and reduction of experimental burden. The integration of AI with sustainable nanomedicine therefore offers a promising strategy for developing intelligent drug delivery systems with improved therapeutic precision, targeting, controlled drug release, and bioimaging capabilities. This review critically examines the convergence of AI and sustainable nanomedicine, with particular emphasis on green carbon dots for smart drug delivery. It discusses green synthesis strategies, AI-driven nanocarrier design and optimization, intelligent targeting, controlled drug delivery, bioimaging applications, and translational challenges. Future perspectives concerning scalability, reproducibility, regulatory considerations, and environmentally responsible manufacturing are also addressed, highlighting the potential of AI-enabled green carbon dots as a sustainable platform for next-generation drug delivery.