Development and validation of global prediction models for monitoring the manufacturing process of herbal medicine by ultraviolet spectroscopy

Jie Zhao, Zimei Zhou, Fang Zhao, Xu Yan, Jianyang Pan, Hai-bin Qu
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引用次数: 2

Abstract

Abstract Objective: Process monitoring for traditional Chinese medicine (TCM) preparations is necessary to ensure quality of the product. A typical pharmaceutical process of TCM preparations consists of multiple manufacturing units, such as ethanol precipitation, concentration, and water precipitation, among others. Compared with the traditional practice of one prediction model for one unit, the global model covers the variation from samples with different backgrounds or processes and can be used to monitor intermediates from substeps. Methods: We used ultraviolet (UV) spectroscopy to establish global models for a typical TCM preparation—Danhong injection. The concentrations of danshensu, protocatechualdehyde, rosmarinic acid, salvianolic acid A, salvianolic acid B, and hydroxyl safflor yellow A and the total phenolic and total sugar contents were quantified for every intermediate from operation units of Danhong injection. New samples prepared by mixing different intermediates were introduced for the calibration set to cover more variations. An accuracy profile was employed to validate the developed method from the aspects of specificity, trueness, precision, accuracy, linearity, and robustness. Results: The developed models showed a high determination coefficient (R2) value up to 0.97 and a low root-mean-square error of the prediction set. Five components of the models passed all validation tests, whereas the total sugar was not suitable for modeling with UV and was not applicable to the whole process. Conclusions: This study indicates that the global models of UV spectroscopy for the quantitative determination of phenolic acids are feasible and reliable with a simple, rapid, and non-destructive method.
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利用紫外光谱技术监测草药生产过程的全球预测模型的开发和验证
摘要目的:中药制剂的工艺监控是保证产品质量的必要手段。中药制剂的典型制药工艺包括多个生产单元,如乙醇沉淀、浓缩和水沉淀等。与传统的一个单元一个预测模型的做法相比,全局模型涵盖了来自不同背景或过程的样本的变化,并可用于从子步骤监测中间产物。方法:采用紫外光谱法建立典型中药制剂丹红注射液的整体模型。测定丹红注射液各操作单元中丹参素、原儿茶醛、迷迭香酸、丹酚酸A、丹酚酸B、羟基红花黄A的浓度及总酚和总糖含量。通过混合不同中间体制备的新样品被引入校准集以覆盖更多的变化。从特异性、真实度、精密度、准确度、线性度和稳健性等方面对所建立的方法进行了验证。结果:所建立的模型具有较高的决定系数(R2),预测集的均方根误差较小,R2值可达0.97。模型的5个组分均通过了所有验证测试,而总糖不适合用UV建模,也不适用于整个过程。结论:建立的紫外光谱法测定酚酸的整体模型是可行、可靠的,方法简单、快速、无损。
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