1. 北京中医药大学中药信息学系
2. 北京市科委中药生产过程控制与质量评价北京市重点实验室
3. 教育部中药制药与新药开发关键技术工程研究中心
4. 北京康仁堂药业有限公司
5. 中药配方颗粒关键技术国家地方联合工程研究中心
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张坤峰, 王政, 曹君杰, 等. 中药口服固体制剂原辅料近红外光谱数据库的构建及应用[J]. 分析测试学报, 2021,40(1):1-9.
Scientific PapersEstablishment and Application of a Near Infrared Spectral Database for Pharmaceutical Excipients of Chinese Medicine Oral Solid Dosage Forms[J]. 2021,40(1):1-9.
建立了中药口服固体制剂原辅料近红外(NIR)光谱数据库,采用模式识别方法研究了NIR光谱数据在物料分类和物性预测中的应用。使用便携式近红外光谱仪快速测量149批原辅料粉末的NIR漫反射光谱数据,并录入iTCM数据库。利用主成分分析(PCA)法探究NIR光谱数据对已知结构物料的分类能力,采用偏最小二乘(PLS)法研究了NIR光谱对原辅料物性参数和直接压片片剂性能的预测能力。经标准正态变量变换(SNV)+Savitzky-Golay(SG)平滑+一阶导数处理后的NIR光谱数据对微晶纤维素、乳糖、乙基纤维素、交联聚维酮和羟丙基甲基纤维素这5类辅料的区分能力较好。NIR光谱数据与原辅料粉末粒径、密度和吸湿性的相关性较强。NIR光谱信息作为物料物理性质的补充,可提高粉末直接压片片剂性能预测模型的性能。NIR光谱数据是iTCM数据库物性参数数据的补充,物性参数与NIR光谱数据的结合能更全面地表征原辅料的性质。
A near infrared(NIR) spectral database for pharmaceutical powders of Chinese medicine oral solid dosage forms was established,and the application of NIR spectral data in material classification and material properties prediction was studied by pattern recognition method.NIR diffuse reflectance spectra for 149 batches of pharmaceutical powders were rapidly measured with portable near infrared spectrometer,and the NIR spectral data were input into the intelligent traditional Chinese medicine(iTCM) database.Principal component analysis(PCA) method was used to explore the classification ability of NIR spectral data for materials with known structures.Partial least squares(PLS) method was used to study the prediction ability of NIR spectra on the material properties of pharmaceutical powders and tablet properties in direct compression.The NIR spectra pretreated by standard normal variable transformation(SNV)+Savitzky-Golay(SG) smoothing+first derivative exhibited a good discrimination ability for five kinds of excipients,i.e.microcrystalline cellulose,lactose,ethyl cellulose,polyvinylpolypyrrolidone and hydroxypropyl methylcellulose.NIR spectra had a strong correlation with particle size,density and hygroscopicity.NIR spectral information could be used as a supplement for the material properties,which could improve the performance of the prediction model for tablet properties in direct compression.Meanwhile,NIR spectral data were also a kind of supplement for the material properties data of iTCM database.The combination of material properties and NIR spectral data could be used to comprehensively characterize the properties of pharmaceutical excipients.
近红外光谱法数据库物性表征模式识别药用辅料中药浸膏粉
near infrared spectroscopydatabasematerial characterizationpattern recognitionpharmaceutical excipientsChinese medicine extract powders
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