Optimization of Cardiovascular Stent against Restenosis: Factorial Design-Based Statistical Analysis of Polymer Coating Conditions

The objective of this study was to optimize the physicodynamic conditions of polymeric system as a coating substrate for drug eluting stents against restenosis. As Nitric Oxide (NO) has multifunctional activities, such as regulating blood flow and pressure, and influencing thrombus formation, a continuous and spatiotemporal delivery of NO loaded in the polymer based nanoparticles could be a viable option to reduce and prevent restenosis. To identify the most suitable carrier for S-Nitrosoglutathione (GSNO), a NO prodrug, stents were coated with various polymers, such as poly (lactic-co-glycolic acid) (PLGA), polyethylene glycol (PEG) and polycaprolactone (PCL), using solvent evaporation technique. Full factorial design was used to evaluate the effects of the formulation variables in polymer-based stent coatings on the GSNO release rate and weight loss rate. The least square regression model was used for data analysis in the optimization process. The polymer-coated stents were further assessed with Differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy analysis (FTIR), Scanning electron microscopy (SEM) images and platelet adhesion studies. Stents coated with PCL matrix displayed more sustained and controlled drug release profiles than those coated with PLGA and PEG. Stents coated with PCL matrix showed the least platelet adhesion rate. Subsequently, stents coated with PCL matrix were subjected to the further optimization processes for improvement of surface morphology and enhancement of the drug release duration. The results of this study demonstrated that PCL matrix containing GSNO is a promising system for stent surface coating against restenosis.