中国中药杂志

2017, v.42(06) 1089-1094

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中药混合过程终点在线判定方法研究
Online endpoint detection algorithm for blending process of Chinese materia medica

林兆洲;杨婵;徐冰;史新元;张志强;付静;乔延江;
LIN Zhao-zhou;YANG Chan;XU Bing;SHI Xin-yuan;ZHANG Zhi-qiang;FU Jing;QIAO Yan-jiang;Beijing Hospital of Traditional Chinese Medicine,Capital Medical University;Institute of Clinical Pharmacy,Beijing Municipal Health Bureau;Beijing Key Laboratory for Production Process Control and Quality Evaluation of Traditional Chinese Medicine;Research Center of Traditional Chinese Medicine Information Engineering,Beijing University of Chinese Medicine,Beijing Municipal Sciences & Technology Commission;Beijin

摘要(Abstract):

混合过程是制剂生产过程的关键环节,它直接影响固体制剂质量的均一性和稳定性。随着《工业过程分析技术指南》的发布,在线分析技术在混合过程应用的研究报道越来越多,但对混合终点在线判断算法的研究尚处于起步阶段。该研究以移动块标准偏差法为原型,建立适于在线应用的混合终点判断方法——递增窗口移动块标准偏差,并将其用于中药配方颗粒混合过程终点的判断。通过在线学习调整窗口大小,将混合过程物料状态的变化实时体现在标准差的计算过程中。在3种不同中药饮片提取物和辅料糊精混合过程的应用中表明,与传统的移动块标准偏差法相比,基于递增窗口移动块标准偏差法计算得到的窗口尺寸变化可以更为清晰地反映混合过程物料状态变异,适于在线应用。
Blending process,which is an essential part of the pharmaceutical preparation,has a direct influence on the homogeneity and stability of solid dosage forms. With the official release of Guidance for Industry PAT,online process analysis techniques have been more and more reported in the applications in blending process,but the research on endpoint detection algorithm is still in the initial stage. By progressively increasing the window size of moving block standard deviation(MBSD),a novel endpoint detection algorithm was proposed to extend the plain MBSD from off-line scenario to online scenario and used to determine the endpoint in the blending process of Chinese medicine dispensing granules. By online learning of window size tuning,the status changes of the materials in blending process were reflected in the calculation of standard deviation in a real-time manner. The proposed method was separately tested in the blending processes of dextrin and three other extracts of traditional Chinese medicine. All of the results have shown that as compared with traditional MBSD method,the window size changes according to the proposed MBSD method(progressively increasing the window size) could more clearly reflect the status changes of the materials in blending process,so it is suitable for online application.

关键词(KeyWords): 混合过程;终点判断;递增窗口;移动块标准偏差;在线学习
blending process;endpoint detection;increasing windowsize;moving block standard deviation;online learning

Abstract:

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基金项目(Foundation): 国家自然科学基金项目(81603396);; 中药生产过程控制与质量评价北京市重点实验室2015年度科技创新基地培育与发展专项(Z151100001615065)

作者(Author): 林兆洲;杨婵;徐冰;史新元;张志强;付静;乔延江;
LIN Zhao-zhou;YANG Chan;XU Bing;SHI Xin-yuan;ZHANG Zhi-qiang;FU Jing;QIAO Yan-jiang;Beijing Hospital of Traditional Chinese Medicine,Capital Medical University;Institute of Clinical Pharmacy,Beijing Municipal Health Bureau;Beijing Key Laboratory for Production Process Control and Quality Evaluation of Traditional Chinese Medicine;Research Center of Traditional Chinese Medicine Information Engineering,Beijing University of Chinese Medicine,Beijing Municipal Sciences & Technology Commission;Beijin

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