Microencapsulation of Acalypha indica Linn. Extracts Using Chitosan-Polycaprolactone Blends

Maizatul Akmal Johari, Fathilah Ali, A. S. Azmi, H. Anuar, J. Jamaluddin, R. Hasham
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Abstract

Polymer encapsulation is commonly adopted in drug delivery systems to form encapsulation that can assist in delivering active compounds to the targeted area. Acalypha indica (AI) crude extract was obtained from AI plants through ultrasound-assisted extraction. It is naturally unstable in the external environment and, thus, needs to be encapsulated to protect against volatility. Herein, this study emphasized the development of the encapsulations of AI extracts using a chitosan-polycaprolactone (PCL) blend by emulsion-solvent evaporation and freeze-dried methods. Four parameters for Al encapsulation were studied by fixing one parameter at a time. The percentage of encapsulation efficiency (EE%) was recorded as a response for each parameter. The study proceeded with central composite design (CCD) as the response surface methodology (RSM) optimization tool to study the interactions between the factors. Central points were taken from the preliminary data obtained in one-parameter experiments. The validation was carried out with two data of the highest and lowest EE% suggested by CCD. The highest EE% recorded was 98.70%, and the lowest EE% was 87.80%. The results showed a difference between predicted and experimental values at a percentage lower than 7.5%. Fourier Transform Infrared Spectroscopy (FTIR), scanning electron microscopy (SEM), particle size analyzer, and zeta potential were used to analyze the properties of selected microencapsulated samples. Overall, the encapsulation of AI extracts was successful and has the potential to be used in drug delivery.
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用壳聚糖-聚己内酯混合物微胶囊化 Acalypha indica Linn.使用壳聚糖-聚己内酯混合物的提取物微胶囊技术
给药系统中通常采用聚合物包囊技术来形成包囊,以帮助将活性化合物输送到目标区域。Acalypha indica(AI)粗提取物是通过超声辅助提取从 AI 植物中获得的。它在外部环境中天然不稳定,因此需要封装以防止挥发。在此,本研究强调使用壳聚糖-聚己内酯(PCL)混合物,通过乳化-溶剂蒸发和冷冻干燥方法开发 AI 提取物的封装。通过每次固定一个参数,研究了铝包封的四个参数。封装效率百分比(EE%)被记录为每个参数的响应。研究采用中心复合设计(CCD)作为响应面法(RSM)优化工具,研究各因素之间的相互作用。中心点取自单参数实验获得的初步数据。利用 CCD 提出的最高和最低 EE% 两个数据进行了验证。记录的最高 EE% 为 98.70%,最低 EE% 为 87.80%。结果显示,预测值和实验值之间的差异低于 7.5%。傅立叶变换红外光谱(FTIR)、扫描电子显微镜(SEM)、粒度分析仪和 zeta 电位被用来分析所选微胶囊样品的特性。总之,人工合成萃取物的封装是成功的,具有用于药物输送的潜力。
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