Engineering Bilosomal Nanocarriers for Targeted Delivery of Resveratrol: Rational Design, Radiotracking Insights and Cytotoxic Assessment

Abstract

Abstract Colorectal cancer (CRC) is a major cause of cancer-related death. Resveratrol (RES), despite its promising anti-inflammatory, antioxidant, and anticancer properties, suffers from poor solubility, low bioavailability, and limited tumor accumulation. Accordingly, eight RES-loaded bilosomes were prepared and characterized. Optimization was performed using a desirability study based on the observed colloidal properties. The selected formulation was radiolabeled with iodine-131 and assessed for radiolabeling efficiency and stability. In-vitro cytotoxicity was evaluated against HT- 29 and LS174T CRC cell lines. Biodistribution studies in tumor-bearing mice were also assessed. Bilosomes displayed PS (93.08 to 340.00 nm), negative charges (-27.50 to -51.80 mV), EE% (73.45—96.35%), and a sustained release over a 24-h period. Optimization revealed formulation with PS (163.8 nm), PDI (0.41), EE% (93.80%) and ZP (− 51.8 mV). Radiolabeling efficiency was 93.23 ± 2.15% and was stable for 2 h. In tumor-bearing mice, the tumor uptake of 131 I-RES bilosomes was 4.34-fold compared to 131 I-RES solution, indicating enhanced tumor accumulation and selectivity, likely driven by enhanced permeability and retention-mediated passive targeting. Bilosomes significantly enhanced cytotoxicity, reducing IC₅₀ values ~ fourfold in LS174T and ~ sixfold in HT-29 cells versus free RES. The pharmacokinetic behavior revealed a significantly higher C max for bilosomes relative to the solution. This study marks the first integration of 131 I-radiotracking with RES-loaded bilosomes, enabling precise measurement of biodistribution and tumor targeting. The approach established a theranostic framework that combined enhanced drug delivery with real-time tracking. Mechanistically, it improved RES accumulation in CRC, highlighting its potential but also underscoring the need for further preclinical research. Graphical Abstract