Abstract

Objective(s): Response surface methodology (RSM) by central composite design (CCD) was applied to statistically optimize the preparation of Rutin-Quercetin (Ru-Qr) dual drug loaded human hair keratin nanoparticles as well as evaluate the characteristics. Materials and Methods: The effects of three independent parameters, namely, temperature (X1:10-40 C), surfactant (X2: SDS (1), SLS (2), Tween-20 (3)), and organic solvents (X3: acetone (1), methanol (2), chloroform (3)) were investigated to optimize the preparation of dual drug loaded keratin nanoparticles, and to understand the effects of dependent parameters namely, drug releasing capacity, average particle size, total antioxidant power, zeta potential, and polydispersity index of Ru-Qr nanoparticles. Optimization was executed by CCD and RSM using statistical software (Design Expert, version 8.0.7.1, Stat-Ease, Inc., Minneapolis, MN, USA). The optimal Ru-Qr dual drug loaded keratin nanoparticles were obtained at temperature (X1): 40UC, SDS (X2), and acetone (X3). Results: Under this conditions to achieve highest drug releasing capacity of 98.3%, average size of nanoparticles are 125 nm, total antioxidant power 98.68%, zeta potential 28.09 mV, and polydispersity index of 0.54. Although majority of the experimental values were relatively well matched with the predicted values. Conclusion: This optimization study could be useful in pharmaceutical industry, especially for the preparation of new nano-therapeutic formulations encapsulated with drug molecules. This nanotechnology based drug delivery system is to overcome multi drug resistance and site specific action without affecting other organs and tissues. The methodology adopted in this work shall be useful in improvement of quality of human health.

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