Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia.
Molecules. 2022 Jul 13;27(14):4468. doi: 10.3390/molecules27144468.
Various chitosan (CS)-based nanoparticles (CS-NPs) of ciprofloxacin hydrochloride (CHCl) have been investigated for therapeutic delivery and to enhance antimicrobial efficacy. However, the Box-Behnken design (BBD)-supported statistical optimization of NPs of CHCl has not been performed in the literature. As a result, the goal of this study was to look into the key interactions and quadratic impacts of formulation variables on the performance of CHCl-CS-NPs in a systematic way. To optimize CHCl-loaded CS-NPs generated by the ionic gelation process, the response surface methodology (RSM) was used. The BBD was used with three factors on three levels and three replicas at the central point. Tripolyphosphate, CS concentrations, and ultrasonication energy were chosen as independent variables after preliminary screening. Particle size (PS), polydispersity index (PDI), zeta potential (ZP), encapsulation efficiency (EE), and in vitro release were the dependent factors (responses). Prepared NPs were found in the PS range of 198-304 nm with a ZP of 27-42 mV. EE and drug release were in the range of 23-45% and 36-61%, respectively. All of the responses were optimized at the same time using a desirability function based on Design Expert modeling and a desirability factor of 95%. The minimum inhibitory concentration (MIC) of the improved formula against two bacterial strains, and , was determined. The MIC of the optimized NPs was found to be decreased 4-fold compared with pure CHCl. The predicted and observed values for the optimized formulation were nearly identical. The BBD aided in a better understanding of the intrinsic relationship between formulation variables and responses, as well as the optimization of CHCl-loaded CS-NPs in a time- and labor-efficient manner.
各种盐酸环丙沙星（CHCl）的壳聚糖（CS）纳米粒子（CS-NPs）已被研究用于治疗药物输送和提高抗菌效果。然而，文献中尚未对 CHCl 的 NPs 进行基于 Box-Behnken 设计（BBD）的统计优化。因此，本研究的目的是系统地研究配方变量对 CHCl-CS-NPs 性能的关键相互作用和二次影响。为了优化通过离子凝胶化过程生成的载盐酸环丙沙星的 CS-NPs，使用了响应面法（RSM）。BBD 采用三因素三水平和中心点的三个重复。经过初步筛选，选择三聚磷酸钠、CS 浓度和超声能量作为独立变量。粒径（PS）、多分散指数（PDI）、Zeta 电位（ZP）、包封效率（EE）和体外释放是依赖因素（响应）。所制备的 NPs 的 PS 范围为 198-304nm，ZP 为 27-42mV。EE 和药物释放分别在 23-45%和 36-61%的范围内。所有响应均通过基于 Design Expert 建模的适用性函数和 95%的适用性因子同时进行优化。测定了改进配方对两种细菌株 和 的最小抑菌浓度（MIC）。与纯 CHCl 相比，优化后的 NPs 的 MIC 降低了 4 倍。优化配方的预测值和观察值非常接近。BBD 有助于更好地理解配方变量和响应之间的内在关系，并以高效省时的方式优化载盐酸环丙沙星的 CS-NPs。
