2022
DOI: 10.3390/gels8020103
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QbD Supported Optimization of the Alginate-Chitosan Nanoparticles of Simvastatin in Enhancing the Anti-Proliferative Activity against Tongue Carcinoma

Abstract: The goal of the current study is to develop a chitosan alginate nanoparticle system encapsulating the model drug, simvastatin (SIM-CA-NP) using a novel polyelectrolytic complexation method. The formulation was optimized using the central composite design by considering the concentrations of chitosan and alginate at five different levels (coded as +1.414, +1, 0, −1, and −1.414) in achieving minimum particle size (PS-Y1) and maximum entrapment efficiency (EE-Y2). A total of 13 runs were formulated (as projected … Show more

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Cited by 23 publications
(19 citation statements)
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“…Every response was limited to the maximum to obtain an inlay graph to augment the non-dependent variables. All three possible independent variables were encompassed in the design for optimization [ 25 ]. The independent variables (ideal level) in the desirability function plot in Figure 4 reflected a maximum desirability value of 1.000 for both responses.…”
Section: Resultsmentioning
confidence: 99%
“…Every response was limited to the maximum to obtain an inlay graph to augment the non-dependent variables. All three possible independent variables were encompassed in the design for optimization [ 25 ]. The independent variables (ideal level) in the desirability function plot in Figure 4 reflected a maximum desirability value of 1.000 for both responses.…”
Section: Resultsmentioning
confidence: 99%
“…The experimental results were compared with theoretical values to validate the experiential design. The relative error was less than 2%, which confirms the preciseness of the design and high degree of internal consistency [ 48 ].…”
Section: Resultsmentioning
confidence: 83%
“…As seen by the ANOVA results, the Lack of Fit is non-significant ( p > .05), confirming the suitability of the chosen design. ANOVA was used to examine the quantitative impacts of certain variables on responses (Rizg et al, 2022 ). Multiple regression was used to the collected data to generate polynomial equations.…”
Section: Resultsmentioning
confidence: 99%