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1.南京中医药大学,南京 210023
2.江苏康缘药业股份有限公司,中药制药过程新技术国家重点实验室,中成药智能制造国家地方联合工程研究中心,中药提取精制新技术重点研究室,江苏 连云港 222001
3.北京中医药大学,北京 100029
[第一作者] 夏春燕,在读硕士,从事新型中药制剂的研究与开发,Tel:0518-81152363,E-mail:xiachytz46@163.com
*肖伟,博士生导师,研究员级高级工程师,从事中药新药的研究与开发工作,Tel:025-87181851,E-mail:kanionlunwen@163.com
收稿日期:2019-06-26,
网络出版日期:2019-08-02,
纸质出版日期:2020-01-05
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夏春燕, 徐芳芳, 张欣, 等. 近红外光谱分析技术快速测定天舒片的包衣薄膜厚度[J]. 中国实验方剂学杂志, 2020,26(1):118-124.
Chun-yan XIA, Fang-fang XU, Xin ZHANG, et al. Rapid Determination of Coating Film Thickness of Tianshu Tablets by Near Infrared Spectroscopy[J]. Chinese journal of experimental traditional medical formulae, 2020, 26(1): 118-124.
夏春燕, 徐芳芳, 张欣, 等. 近红外光谱分析技术快速测定天舒片的包衣薄膜厚度[J]. 中国实验方剂学杂志, 2020,26(1):118-124. DOI: 10.13422/j.cnki.syfjx.20192251.
Chun-yan XIA, Fang-fang XU, Xin ZHANG, et al. Rapid Determination of Coating Film Thickness of Tianshu Tablets by Near Infrared Spectroscopy[J]. Chinese journal of experimental traditional medical formulae, 2020, 26(1): 118-124. DOI: 10.13422/j.cnki.syfjx.20192251.
目的:
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探讨近红外光谱分析技术应用于检测天舒片包衣薄膜厚度的可行性。
方法:
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采集9批天舒片包衣过程样品的近红外漫反射光谱,运用Kennard-Stone算法将样本集划分为校正集和验证集。优选预处理方法,并采用组合间隔偏最小二乘法(siPLS)和移动窗口偏最小二乘法(mwPLS)优选光谱区间,建立测定包衣厚度的偏最小二乘法(PLS)定量模型。
结果:
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在标准正态变量变换+一阶导数+Norris Derivative平滑对光谱进行预处理并结合siPLS的优选区间建立的模型中,校正集预测值与实测值的相关系数0.966,验证集预测值与实测值的相关系数0.991,表明预测值与实测值的相关性较好。校正均方根误差(RMSEC)0.198%,预测均方根误差(RMSEP)0.062%,表明模型的预测性能良好。
结论:
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近红外光谱分析技术用于天舒片包衣薄膜厚度的测定具有很高的准确性,能够为中药片剂生产过程中包衣厚度的在线检测提供技术支持。
Objective:
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To investigate the feasibility of near-infrared spectroscopy for detecting the coating film thickness of Tianshu tablets.
Method:
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Nine batches of Tianshu tablets were taken during the coating process. Then
their near-infrared diffuse reflection spectra were collected. The sample set was divided into calibration set and validation set by Kennard-Stone algorithm. The preprocessing method was selected. The synergy interval partial least squares (siPLS) and moving window partial least squares (mwPLS) were employed to screen the optimal spectral interval. And the corresponding quantitative calibration model of partial least squares (PLS) were established. Some evaluation parameters were adopted to assess the performance of the model.
Result:
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The method of first derivative and Norris Derivative smoothing combined with standard normal variate transformation was suitable for processing the spectra. The optimal PLS model was established in the preferred band interval of siPLS. The correlation coefficient between the predicted value and the measured value of calibration set was 0.966
and the correlation coefficient between the predicted value and the measured value of validation set was 0.991.Both root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) values were small
which showed the fitness and predictive performance of the model were favorable.
Conclusion:
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The near-infrared spectroscopy technique can be used to determine coating film thickness of Tianshu tablets with high accuracy
which provides technical supports for the in-line determination of coating thickness in the production process of traditional Chinese medicine tablets.
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