首页|基于中药物料语义分类的临方水丸制剂处方预测模型优化

基于中药物料语义分类的临方水丸制剂处方预测模型优化

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为优化前期已建立的临方水丸制剂处方预测模型,该研究选择山药、益母草、党参、苦杏仁、煅牡蛎分别为粉性料、纤维性料、糖性料、油性料、脆性料的代表性中药,利用混料均匀设计得到模型处方,以羟丙甲纤维素(HPMC-E5)水溶液为黏合剂,采用挤出搓圆法制备临方水丸.结合丸剂制备过程中的评价指标和多个模型的统计分析,优化并验证临方水丸制剂处方预测模型.得到临方水丸黏合剂浓度预测方程Y1=-4.172+3.63XA+15.057XB+1.838XC-0.997XD(Y1＜0时黏合剂质量分数为10％,Y1＞0时黏合剂质量分数为20％),黏合剂浓度预测模型整体正确率为96.0％;黏合剂用量预测方程Y2=6.051+94.944 XA1.5+161.977 XB+70.078 XC2+12.016 XD0.3+27.493 XE0.3-2.168 XF-1(R2=0.954,P＜0.001).同时采用中药物料分类的语义预测模型对验证处方包含的中药物料进行分类,制备丸剂,验证临方水丸制剂处方预测模型,验证处方在制丸过程中均一次成型,且成型质量优于前期所建方法,实现了临方水丸制剂处方预测模型的优化.
Optimization of prediction model for personalized water pills based on semantic analysis of traditional Chinese medicine materials
This study aims to optimize the prediction model of personalized water pills that has been established by our research group.Dioscoreae Rhizoma,Leonuri Herba,Codonopsis Radix,Armeniacae Semen Amarum,and calcined Oyster were selected as model medicines of powdery,fibrous,sugary,oily,and brittle materials,respectively.The model prescriptions were obtained by uniform mixing design.With hydroxypropyl methylcellulose E5(HPMC-E5)aqueous solution as the adhesive,personalized water pills were prepared by extrusion and spheronizaition.The evaluation indexes in the pill preparation process and the multi-model statistical analysis were employed to optimize and evaluate the prediction model of personalized water pills.The prediction equation of the adhesive concentration was obtained as follows:Y1=-4.172+3.63XA+15.057XB+1.838XC-0.997XD(adhesive concentration of 10％when Y1＜0,and 20％whenY1＞0).The overall accuracy of the prediction model for adhesive concentration was 96.0％.The prediction equation of adhesive dosage was Y2=6.051+94.944XA1.5+161.977XB+70.078XC2+12.016XD0.3+27.493XE0.3-2.168XF-1(R2=0.954,P＜0.001).Furthermore,the semantic prediction model for material classification of traditional Chinese medicines was used to classify the materials contained in the prescription,and thus the prediction model of personalized water pills was evaluated.The results showed that the prescriptions for model evaluation can be prepared with one-time molding,and the forming quality was better than that established by the research group earlier.This study has achieved the optimization of the prediction model of personalized water pills.

personalized water pillsprediction modelsemantic analysismaterial classification of traditional Chinese medicines

李云琪、田文秀、薛爱乐、李文杰、赵立杰、洪燕龙

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上海中医药大学上海中医健康服务协同创新中心,上海 201203

上海健康医学院附属周浦医院,上海 201318

上海中医药大学创新中药研究院,上海 201203

中药现代制剂技术教育部工程研究中心,上海 201203

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临方水丸 预测模型 语义分析 中药物料分类

国家自然科学基金上海市"科技创新行动计划"技术标准项目上海中医药慢性病防治与健康服务省部共建协同创新中心项目上海市自然科学基金面上项目上海市浦东新区周浦医院院级人才培养项目上海市浦东新区卫生系统临床药学重要薄弱学科建设项目

8197349020DZ22009002021科技02-3723ZR1463500ZPRC-2023A-04PWZbr2022-11

2024

10.19540/j.cnki.cjcmm.20231220.302

中国中药杂志
中国药学会

中国中药杂志

CSTPCD北大核心
影响因子：1.718
ISSN：1001-5302
年,卷(期)：2024.49(3)
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