2025 AIChE Annual Meeting

(72f) Nano-Hydrogel Assemblies Enable Prolonged and Inflammation-Responsive Gene Delivery for Cartilage Repair

Authors

Juwon Kang - Presenter, Hanbat National University
Jieun Ha, Ewha Womans University
Kye Il Joo, Ewha Womans University
Despite advances in gene and drug delivery systems, current osteoarthritis (OA) therapies remain limited by short-lived efficacy and systemic side effects. In this study, we developed and validated a multi-functional levan-based nanoparticle (NP)-hydrogel platform that enables targeted and sustained gene delivery of OA treatment. Levan, a biocompatible and biodegradable polysaccharide with amphiphilic properties, serves as an effective base material for constructing nanoparticle and hydrogel systems. The levan-based NPs were engineered to selectively target inflamed tissues via specific interactions with CD44, a membrane protein overexpressed on inflammatory cells. In vitro studies confirmed that the NPs effectively delivered growth differentiation factor-5 (GDF-5) expression plasmid into bone marrow-derived mesenchymal stem cells (BMSCs), inducing their chondrogenic differentiation. To prolong the retention and therapeutic efficacy of the NPs at the OA site, methacrylated levan (LevMA) was photo-crosslinked to form a hydrogel matrix encapsulating the NPs. The LevMA hydrogel exhibited pH-responsive drug release kinetics, selectively discharging its cargo under acidic inflammatory conditions. Compared to NP delivery alone, the NP-hydrogel system maintained gene expression for an extended period, indicating that the hydrogel shielded the NPs and enabled sustained therapeutic effects. Taken together, our study demonstrates that the hybrid platform combines active targeting and gene delivery capabilities of the NPs with the controlled release and retention functions of the hydrogel. This integrated system shows significant potential for cartilage regeneration and long-term OA treatment, and its modular nature may be applicable to other inflammatory disease models.