Targeted Therapy for Glioblastoma Multiforme using Biofunctionalized Iron Oxide Nanoparticles and Deep Learning-Enhanced Method

Glioblastoma multiforme (GBM) remains one of the most aggressive and treatment-resistant brain tumors, largely due to its infiltrative nature and the presence of the blood brain barrier, which limits effective drug delivery. In this study, we explored the potential of biofunctionalized iron oxide nanoparticles (FeONPs) synthesized using Tinospora cordifolia ( T. cordifolia) leaf extract as a targeted therapeutic platform for glioblastoma treatment, supported by deep learning enhanced analytical methods. The green synthesis approach enabled the formation of stable and biocompatible FeONPs, as confirmed by UV–visible spectroscopy, FTIR, XRD, and TEM analyses. FTIR results indicated the involvement of plant-derived functional groups such as hydroxyl, amine, carbonyl, and C–O groups in nanoparticle stabilization, while XRD confirmed their crystalline magnetite/maghemite phase. TEM analysis revealed predominantly rod-shaped nanoparticles with nanoscale dimensions. The synthesized FeONPs exhibited notable antioxidant activity and demonstrated dose-dependent cytotoxic effects on glioblastoma and neuronal cell lines, highlighting their therapeutic relevance. Owing to their magnetic properties, surface biofunctionalization, and favorable morphology, these FeONPs offer a promising platform for targeted delivery and potential imaging applications in GBM. Furthermore, the integration of deep learning-based methods provides a powerful tool for analyzing nanoparticle behavior, optimizing targeting efficiency, and enabling precision-driven therapeutic strategies. Overall, this study presents a multidisciplinary approach combining green nanotechnology and artificial intelligence, laying the groundwork for the development of effective and targeted therapies for glioblastoma multiforme.