Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, PR China.
School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing 210023, PR China.
Spectrochim Acta A Mol Biomol Spectrosc. 2022 Jan 15;265:120363. doi: 10.1016/j.saa.2021.120363. Epub 2021 Sep 4.
Carbonized traditional Chinese medicine (TCM) is a kind of distinctive traditional drug which has been widely used in various bleeding syndromes for over two thousand years, and most of them are still in clinical use. Although they share similar processing method: stir-frying, there are no specific quality standards and few quality control researches carried out on carbonized TCM up until now. Carbonized Typhae Pollen (CTP) is a typical carbonized TCM with efficacy of eliminating blood stasis and stanching bleeding. In this study, a novel process quality control model coupled with near infrared spectroscopy was established, called Gradient-based Discriminant Analysis method (GDA). Compared with conventional modeling methods (Convolutional Neural Network, Linear Discriminant Analysis, Standard Normal Variate-LDA), GDA model applied in fiber optic probe acquisition mode exhibited highest test accuracy (0.961), satisfactory correct identification (internal validation, 100%; external validation, 97.1%) and excellent model stability. This method provided a perfect guideline for process quality control of Carbonized TCM as well as ensured their clinical efficacy.
炭化中药是一种具有特色的传统药物，两千多年来广泛用于各种出血症，其中大部分仍在临床应用。虽然它们的炮制方法相似：炒制，但迄今为止，对炭化中药还没有具体的质量标准和很少的质量控制研究。炭化蒲黄是一种典型的炭化中药，具有化瘀止血的功效。本研究建立了一种新的过程质量控制模型，结合近红外光谱，称为基于梯度的判别分析方法（GDA）。与常规建模方法（卷积神经网络、线性判别分析、标准正态变量-LDA）相比，在光纤探头采集模式下应用的 GDA 模型表现出最高的测试精度（0.961）、令人满意的正确识别（内部验证，100%；外部验证，97.1%）和出色的模型稳定性。该方法为炭化中药的过程质量控制提供了完美的指导，保证了其临床疗效。
