Cytotoxic Evaluation And Factorial Analysis Of 3D Photopolymerizable Thermoresponsive Composite Nanoparticle Hydrogels For Controlled Drug Delivery In Restenosis And Wound Healing
Sabnis, Abhimanyu Rajaram
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To develop a smart drug delivery system for restenosis and wound healing applications, we investigated photopolymerizable composite nanoparticle hydrogels which can release the drug in a temperature-responsive manner. Our novel system consisting of thermoresponsive poly(N-isopropylacrylamide-co-acrylamide) (PNIPA-AAm) nanoparticles and poly(ethylene glycol) diacrylate (PEGDA) as photo cross-linker can be formed in situ in presence of ultraviolet (UV) light and Irgacure 2959 photoinitiator (PI). The main aims of this project were to investigate the system cytotoxicity and optimize drug release characteristics by performing biocompatibility and factorial analysis studies, respectively. We evaluated the cell survival of human vascular smooth muscle cells and NIH/3T3 fibroblasts upon exposure to UV light and photoinitiator concentrations. At conditions required for photopolymerization of our composite system (UV=5 minutes, PI=0.015% w/v), the cell survival for both cell types was not significantly decreased. Addition of an anti-oxidant reagent, ascorbic acid, to hydrogel precursor solution further improved cell survival at higher PI concentrations, but increased the gelation times. Additionally, we performed a factorial analysis to evaluate the effects of PEGDA concentration (10% and 15% w/v) and molecular weight (3.4 KDa and 8 KDa) as well as PNIPA-AAm nanoparticle concentration (2% and 4% w/v) on the hydrogel gelation times, drug release profiles and swelling ratios. Our studies showed PNIPA-AAm nanoparticle concentration was the most important factor affecting the drug release at 40oC and thermoresponsiveness of the system. Additionally, PEGDA concentration affected gelation times while PEGDA molecular weight governed the swelling ratio. These findings have improved our understanding of the composite systems and will help in tailoring future systems with desired characteristics.