Using silk fibroin as the base material, the drug‐loaded microspheres are prepared by an emulsification method. In order to determine the drug‐loading and drug‐release performance parameters of the microspheres, the central composite design method is used to design and investigate the effects of the parameters of the microsphere preparation process, such as the oil–water ratio, stirring temperature, and stirring rate, on the microsphere particle size, drug‐loading rate, and drug release rate. The “overall desirability” is taken as a comprehensive evaluation index, and the response surface method (RSM) and genetic algorithm–backpropagation (GA–BP) neural network GA–BP model are used to predict and evaluate the parameters of the drug‐loaded microsphere preparation process. The root‐mean‐square error values obtained from the RSM and BP–GA model experiments are 0.000325 and 0.00022, respectively. The results show that the BP–GA model has better prediction accuracy and optimization ability than the RSM. The optimal microsphere preparation process conditions were determined to be as follows: a water–oil ratio of 10:1, at a temperature of 45°C with stirring at a speed of 400 rpm, the particle size of the microspheres is 1.392 μm, the drug‐loading rate is 3.218%, and the drug release rate is 51.991%. The results of this study indicate that this approach is an effective method for the optimization of the parameters of the drug‐loaded microsphere preparation process.

中文翻译：

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基于响应面法和遗传算法-反向传播神经网络模型的丝素蛋白载药微球制备参数优化

以丝素蛋白为基材，通过乳化法制备载药微球。为确定微球的载药和释药性能参数，采用中心复合设计法设计研究微球制备过程中油水比、搅拌温度等参数的影响。和搅拌速率对微球粒径、载药率和药物释放率的影响。以“总体合意性”为综合评价指标，采用响应面法（RSM）和遗传算法-反向传播（GA-BP）神经网络GA-BP模型对载药参数进行预测评价。微球制备过程。从 RSM 和 BP-GA 模型实验中获得的均方根误差值分别为 0.000325 和 0.00022。结果表明BP-GA模型比RSM具有更好的预测精度和优化能力。最佳微球制备工艺条件确定为：水油比10:1，温度45℃，转速400 rpm，微球粒径1.392 μm，载药率为3.218%，释药率为51.991%。本研究结果表明，该方法是优化载药微球制备工艺参数的有效方法。最佳微球制备工艺条件确定为：水油比10:1，温度45℃，转速400 rpm，微球粒径1.392 μm，载药率为3.218%，释药率为51.991%。本研究结果表明，该方法是优化载药微球制备工艺参数的有效方法。最佳微球制备工艺条件确定为：水油比10:1，温度45℃，转速400 rpm，微球粒径1.392 μm，载药率为3.218%，释药率为51.991%。本研究结果表明，该方法是优化载药微球制备工艺参数的有效方法。