基于中药饮片物料分类的临方全粉末水丸制剂处方预测模型的构建研究

Establishment of prediction model for personalized water-paste pills based on classification of traditional Chinese medicine materials

为探究临方全粉末水丸制剂过程中,中药饮片物料分类与适宜黏合剂浓度、用量间的关系,建立适合全粉末水丸临方制剂的黏合剂浓度及用量的预测模型。研究中选取了5种不同物料中具有代表性的药物,以混料均匀设计法进行试验设计,以羟丙基甲基纤维素E5(hypromellose E5,HPMC E5)水溶液为黏合剂,采用挤出搓圆法制备丸剂,评价制剂中间体及丸剂成型质量,并对数据进行多元统计分析,从而建立黏合剂浓度、用量预测模型。黏合剂浓度预测模型Y1=0.378 6+0.570 1X_(A)+2.271 2X_(B)-0.894 5X_(C)-0.458 2X_(D)-1.145 4X_(E)(当Y_(1)<0,黏合剂浓度选择10%;当Y_(1)>0,黏合剂浓度选择20%),浓度预测结果正确率100%;黏合剂用量预测模型Y2=32.38+0.25X_(A)+1.85X_(B)-0.013X_(B)2-0.002 5X_(C)2(R^(2)=0.926 8,P<0.001)。结果表明,处方中纤维料占比与黏合剂浓度、用量成正相关,糖性料、脆性料占比与黏合剂浓度、用量呈负相关。此外根据得到的浓度、用量预测模型指导验证试验,所有验证处方均一次成型,说明通过对处方进行中药物料分类并计算其占比,可以根据所建立的数学模型预测临方全粉末水丸制剂过程中的黏合剂浓度及用量,从而减少大量制剂处方前研究,指导中药临方水丸的实际生产。

The purpose of the present study was to investigate the relationship of the classification of traditional Chinese medicine(TCM) materials with the suitable binder concentration and dosage in the preparation of personalized water-paste pills and establish a model for predicting the binder concentration and dosage. Five representative TCM materials were selected, followed by mixture uniform design. The water-paste pills were prepared by extrusion and spheronization with hypromellose E5(HPMC E5) as the binder. The quality of intermediates and final products was evaluated, and the resulting data were subjected to multivariate statistical analysis. The prediction models for binder concentration and dosage were established as follows: binder concentration: Y_(1)=0.378 6 + 0.570 1X_(A) + 2.271 2X_(B)-0.894 5X_(C)-0.458 2X_(D)-1.145 4X_(E)(when Y_(1)< 0, 10% HPMC E5 was required;when Y1 > 0, 20% HPMC E5 was required), with the accuracy reaching up to 100%;binder dosage: Y2=32.38 + 0.25X_(A) + 1.85X_(B)-0.013X_(B)2-0.002 5X_(C)2(R^(2)=0.932 6, P < 0.001). The results showed that the binder concentration and dosage were correlated positively with the proportion of fiber material but negatively with the proportions of sugar material and brittle material. Then the validation experiments were conducted with the prediction models and all the prescriptions could be successfully prepared at one time. These demonstrated that following the classification of TCM materials and the calculation of their proportions in the prescription, the established mathematical model could be adopted for predicting the binder concentration and dosage required in the preparation of personalized water-paste pills, which contributed to reducing the pre-formulation research and guiding the actual production of personalized water-paste pills.