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In European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V

The linings of the oral cavity are excellent needle-free vaccination sites, able to induce immune responses at distal sites and confer systemic protection. However, owing to the mucosal tissues' intrinsic characteristics, the design of effective antigen-delivery systems is not an easy task. In the present work, we propose to develop and characterize thermosensitive and mucoadhesive hydrogels for orotransmucosal vaccination taking advantage of artificial intelligence tools (AIT). Hydrogels of variable composition were obtained combining Pluronic® F127 (PF127), Hybrane® S1200 (HS1200) and Gantrez® AN119 (AN119) or S97 (S97). Systems were characterized in terms of physicochemical properties, adhesion capacity to mucosal tissues and antigen-like microspheres release. Additionally, polymers biocompatibility and their immune-stimulation capacity was assessed in human macrophages. Interestingly, cells treated with HS1200 exhibited a significant proliferation enhancement compared to control. The use of AIT allowed to determine the effect of each polymer on formulations properties. The used proportions of PF127 and Gantrez® are mainly the factors controlling gelation temperature, mucoadhesion, adhesion work and gel strength. Meanwhile, cohesion and short-term microsphere release are dependent on the PF127 concentration. However, long-term microsphere release varies depending on the Gantrez® variety and the PF127 concentration used. Hydrogels prepared with S97 showed slower microsphere release. The use of AIT allowed to establish the conditions able to produce ternary hydrogels with immune-stimulatory properties together with adequate mucoadhesion capacity and antigen-like microspheres release.

Garcia-Del Rio Lorena, Diaz-Rodriguez Patricia, Landin Mariana


Antigen delivery, Artificial intelligence, Hydrogel design, Mucoadhesive networks, Mucosal vaccination, Thermosensitive platforms