Objective: Literature study revealed the poor mechanical strength of chitosan-based microparticles. Our research aimed at developing sufficient strength of microparticle with a suitable concentration of chitosan and non-ionic surfactants such as poloxamer-188 (pluronic). It also aimed to develop and study the effect of variables for prepared microparticles utilizing insilico screening methodology, such as reduced factorial design, followed by optimization.

Methods: Preliminary trial batches were prepared with variable concentration of chitosan and poloxamer-188 utilizing cross-linked ion-gelation technique. A 20% w/v sodium citrate solution was used as a cross-linking solution. The resolution-IV of 24-1 reduced factorial design was selected to screen the possible and significant independent variables or factors in the dosage form design. A total number of eight runs were suggested by statistical software and responses were recorded. The responses such as spreadability, pH, viscosity and percentage of drug released at 12 h were considered in the screening study. Based on the result, selected factors were included in the optimization technique, including graphical and numerical methods.

Results: The signified factors based on reduced two-level factorial screening design with randomized subtype, were identified by Half-normal and Pareto chart. Mathematical fitting and analysis were performed by the factorial equation during the optimization process. The validation and fitting of models were suggested and evaluated by p-value, adjusted R2, and predicted R2 values. The significant and non-significant terms were evaluated, followed by finding the optimal concentration and region with yellow color highlighted in an overlay plot. Based on the data obtained by the overlay study, the final formulation batch was prepared and the observed value was found to be pretty much nearer as compared to predicted values. Drug-polymer interaction study included attenuated total reflectance, differential scanning calorimetry, and X-Ray diffraction study.

Conclusion: The principal of the study design was based on finding the prefixed set parameter values utilizing the concept of in-silico screening technique and optimization with a minimal number of trials and study expenses. It concluded that Poloxamer-188 (0.94%), chitosan (2.38%), swelling time (1.81 h), and parts of chitosan (78.51%) in a formulation batch would fulfill the predetermined parameter with specific values.

目的：文献研究表明，壳聚糖基微粒的机械强度较差。我们的研究旨在通过适当浓度的壳聚糖和非离子表面活性剂（例如poloxamer-188（普流尼克））开发出足够强度的微粒。它还旨在利用计算机筛选方法（例如减少的因子设计，然后进行优化）来开发和研究变量对制备的微粒的影响。

方法：采用交联离子凝胶技术，制备了不同浓度的壳聚糖和泊洛沙姆-188的初步试验批次。使用20％w / v的柠檬酸钠溶液作为交联溶液。选择24-1减少因子设计的IV分辨率以筛选剂型设计中可能的和重要的独立变量或因素。统计软件建议总共运行八次，并记录响应。在筛选研究中考虑了诸如在12小时时的可扩展性，pH，粘度和药物释放百分比的响应。根据结果​​，选择的因素包括在优化技术中，包括图形和数值方法。

结果：通过减少半水平因子筛选设计和随机亚型的显着因素，通过半正态图和帕累托图进行鉴定。在优化过程中，通过阶乘方程进行了数学拟合和分析。提出了模型的验证和拟合，并通过p值，调整后的R2和预测的R2值进行了评估。评估有效项和非重要项，然后找到最佳浓度和最佳区域，并在叠加图中突出显示黄色。根据叠加研究获得的数据，制备了最终的配方批次，发现观测值与预测值相比非常接近。药物-聚合物相互作用研究包括衰减全反射率，差示扫描量热法，

结论：研究设计的原则是基于利用计算机内筛选技术的概念找到前缀的设定参数值，并以最少的试验和研究费用进行优化。结论是，配方批次中的泊洛沙姆188（0.94％），壳聚糖（2.38％），溶胀时间（1.81 h）和部分壳聚糖（78.51％）将满足预定参数的特定值。