Abstract
Objective: Silk fibroin based nanoparticles have been utilized extensively in biomedical fields. Amongst many preparation methods, desolvation is a favorable one. However, this method yields nanoparticles with unpredictable parameters. Thus, this investigation aimed to systematically study the effects of three independent variables including fibroin concentration (% w/v, X1), volume ratio between fibroin solution and ethanol (X2), formulation time (h, X3) on three main responses, particle size (nm, Y1), polydispersity index (Y2), zeta potential (mV, Y3).Methods: Fibroin was extracted from degummed Bombyx mori silk. The fibroin calibration curve was constructed by UV-spectrophotometer at 276 nm. The nanoparticles were prepared using the desolvation method of aqueous fibroin solution in ethanol. Design Expert® software was used to design the model. The mean particle size, polydispersity index and zeta potential were determined using ZetaPALS®analyzer.Results: By using D-optimal design with the quadratic model, the results showed that all X1, X2, and X3 variables had significant impacts on the fibroin nanoparticles characteristics Y1, Y2, and Y3. The generated model was also validated and demonstrated to be solid and reliable. The obtained optimal nanoparticles possessed Y1 of 238.1 nm, Y2 of 0.12, and Y3of-21.78 mV, which were in agreement with the predicted values, 224.8 nm, 0.13 and-19.31 mV, respectively. The optimal actual and theoretical particle characteristics were correlated with a desirable value of R2 = 0.8770. Conclusion: The D-optimal design proved its effectiveness in the prediction and optimization of fibroin nanoparticle properties.
Highlights
Nanoparticles have gained increasing attention in biomedical fields, especially in the area of cosmeceuticals and drug delivery systems [13]
By using D-optimal design with the quadratic model, the results showed that all X1, X2, and X3 variables had significant impacts on the fibroin nanoparticles characteristics Y1, Y2, and Y3
The D-optimal design proved its effectiveness in the prediction and optimization of fibroin nanoparticle properties
Summary
Nanoparticles have gained increasing attention in biomedical fields, especially in the area of cosmeceuticals and drug delivery systems [13]. Numerous types of nanoparticles have been proposed. They could be classified into three main categories; lipid nanoparticles such as liposomes and solid lipid nanoparticles; polymeric nanoparticles such as natural nanoparticles (i.e., chitosan, alginate, albumin) and synthetic nanoparticles (i.e., polyacrylamide, poly (lactic acid)); and inorganic nanoparticles such as carbon nanotubes and magnetic nanoparticles [2]. Polymeric nanoparticles are favorable due to ease of preparation, cheap ingredients and the ability to modify the surface to maximize the desired outcomes [4]. The synthetic polymers and their metabolites might cause toxicity to both the human and the environment. To avoid toxicity issue, natural polymers have been extensively explored
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