@article{SEBASTIAN_PRIYA_P. JAMES_M. M._SANNIDHI_PRABHU_2022, title={COMPUTATIONAL TOOLS ASSISTED FORMULATION OPTIMIZATION OF NEBIVOLOL HYDROCHLORIDE LOADED PLGA NANOPARTICLES BY 32 FACTORIAL DESIGNS}, volume={14}, url={https://journals.innovareacademics.in/index.php/ijap/article/view/44865}, DOI={10.22159/ijap.2022v14i4.44865}, abstractNote={<p><strong>Objective: </strong>The aim of the present study was to formulate and optimize the PLGA polymeric nanoparticle of Nebivolol Hydrochloride for sustain release of drug</p> <p><strong>Methods: </strong>The drug-excipients interaction was explored by molecular docking studies by <em>in silico</em> tools. The drug-loaded polymeric nanoparticles prepared by emulsion solvent evaporation method using 3<sup>2</sup> factorial design and characterized for particle size, zeta potential, and entrapment efficiency. Shape and surface morphology was analysed by SEM and TEM. <em>In vitro</em> drug release study was performed by using a diffusion membrane.</p> <p><strong>Results: </strong>The docking analysis inferred that the drug has interacted well with PLGA and PF-68, which could prevent the drug crystal formation. The optimized polymeric nanoparticles had a particle size of 291 nm and entrapment efficiency of 83.4% and were found to be within 95% of CI of the predicted value, which is acceptable. SEM and TEM studies showed that the formed polymeric nanoparticles were smooth, spherical in shape and uniform in size. <em>In vitro </em>drug release study of optimized formulation showed sustained release for prolonged time period</p> <p><strong>Conclusion: </strong>Based on the computational studies and<em> in vitro</em> release studies, the developed Nebivolol hydrochloride loaded in PLGA nanoparticles could be a promising formulation in oral drug delivery for the treatment of hypertension.</p>}, number={4}, journal={International Journal of Applied Pharmaceutics}, author={SEBASTIAN, GRACE and PRIYA, SNEH and P. JAMES, JAINEY and M. M., ABHILASH and SANNIDHI and PRABHU, VINAY KIRAN}, year={2022}, month={Jul.}, pages={251–258} }