Cannabinoid Loaded Microspheres for Integrated Cancer Pain and Tumor Control

Purpose: We aim to develop cannabinoid loaded microsphere (CALM) for sustained tumor pain release and anti-cancer effects.

Materials and Methods: CALM was developed using a machine learning-driven predictive framework to optimize encapsulation efficiency and release kinetics for efficient local delivery of cannabinoids. Monodisperse microspheres were generated via an oil-in-water single emulsion using a flow-focusing microfluidic device. Particle size modulation was assessed by optical microscopy with Gaussian fitting, revealing size reductions with lower polymer concentrations and higher external/internal flow rate ratios. Encapsulation efficiency and release kinetics were quantified by high-performance liquid chromatography. Anti-cancer effects of CALM-released cannabinoids were examined using CCK-8 proliferation assays and Annexin V/PI staining. Anti-inflammatory activity in M1-polarized macrophages was evaluated by cAMP and cytokine quantification, while reprogramming potential toward non-inflammatory phenotypes was assessed by CD80/CD206 expression ratios.

Results: CALM, optimized by machine learning to achieve a cannabinoid-to-polymer ratio of 0.1 and an average particle size of ~89 µm, demonstrated high loading efficiency (91.7%) and a biphasic release profile, with ~40% released within 24 h and ~60% sustained over 6 days. CALM exhibited enhanced cytotoxic and pro-apoptotic effects in PANC2 and A549 cancer cells, indicating both receptor-dependent and independent mechanisms with a sustained-release advantage over free cannabinoids. In macrophages, CALM suppressed cAMP and pro-inflammatory cytokines and reprogrammed M1 macrophages toward a tolerogenic M2-like phenotype.

Conclusion: CALM provides a localized, sustained-release cannabinoid platform with enhanced anti-cancer efficacy, reduced off-target toxicity, and immunomodulatory activity, representing a potential localized tumor pain control and tumor growth suppression.