Multifunctional chitosan–graphene composites for drug, gene, and protein delivery: Promises, challenges, and outlook

Graphical Abstract- Created in BioRender. User, A. (2025) https://BioRender.com/de15cnn • Reviewing CS-GO nanocomposites as promising drug delivery platforms. • Discussing synthesis and surface modification strategies of CS-GO composites. • Highlighting drug loading and release mechanisms, particularly in response to pH. • Outlining versatility of CS-GO composites in controlled and targeted drug delivery. Chitosan–graphene oxide (CS–GO) nanocomposites have been investigated as hybrid platforms for drug delivery because they combine the biodegradability of chitosan with the high surface functionality of graphene oxide. However, their clinical translation is still at an early stage, and a systematic overview of their design strategies and biological performance is needed. Publications were classified according to carrier responsiveness to pH, redox environments, and near-infrared (NIR) light, as well as approaches for co-delivery of multiple agents. Reported findings indicate that CS–GO systems can improve drug loading efficiency and enable controlled release, although results vary depending on fabrication method, surface modification, and drug type. Applications have been explored in cancer treatment, antimicrobial therapy, and delivery to tissues such as bone, brain, and the gastrointestinal tract. In vitro and in vivo studies generally demonstrate therapeutic potential, but limitations such as incomplete toxicity evaluation, lack of standardized synthesis protocols, and variability in biological outcomes remain major obstacles. Unlike other chitosan-based nanocarriers, the application of artificial intelligence in CS–GO design is still limited and has not been systematically assessed. Overall, this review synthesizes current knowledge, identifies gaps between experimental findings and translational requirements, and highlights directions for future work, including long-term safety assessment, reproducible large-scale fabrication, and integration with computational optimization tools.