王学重,王亦卓,张冉,侯光昊,吴韬

• 1:北京石油化工学院新材料与化工学院
• 2:恩泽生物质精细化工北京市重点实验室

摘要(Abstract)：

为了实现药物包衣层厚度分布的实时在线检测，解决离线检测平均厚度或称重不能满足均匀性分析及判断终点等问题，以蛋白哂双凸片的包衣过程为例，采用探头式拉曼光谱仪实时在线采集片剂表面拉曼光谱的同时，离线采集并统计包衣层厚度分布。分别采用偏最小二乘法(PLS)和卷积神经网络(CNN)两种方法建立包衣厚度定量校正模型。结果表明，PLS模型预测相关性R_p~2为0.923,CNN模型R_p~2高达0.996，其模型的泛化能力更高，较PLS模型展现出更好的准确性。且CNN模型预测的包衣层厚度分布与离线统计的厚度分布结果较为一致(包衣时间为60 min，最可几厚度和分布宽度偏差仅为0.44%和1.24%)，实现了药物包衣层厚度分布的准确预测。

关键词(KeyWords)： 在线拉曼光谱;包衣厚度统计分布;偏最小二乘法;主成分分析-卷积神经网络;包衣均匀性

Abstract:

Keywords:

基金项目(Foundation): 北京市科技新星计划(Z211100002121024)

作者(Author): 王学重,王亦卓,张冉,侯光昊,吴韬

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