Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Molecules. 2022 Jul 25;27(15):4733. doi: 10.3390/molecules27154733.
The breadth and depth of traditional Chinese medicine (TCM) applications have been expanding in recent years, yet the problem of quality control has arisen in the application process. It is essential to design an algorithm to provide blending ratios that ensure a high overall product similarity to the target with controlled deviations in individual ingredient content. We developed a new blending algorithm and scheme by comparing different samples of ginkgo leaves. High-consistency samples were used to establish the blending target, and qualified samples were used for blending. Principal component analysis (PCA) was used as the sample screening method. A nonlinear programming algorithm was applied to calculate the blending ratio under different blending constraints. In one set of calculation experiments, the result was blended by the same samples under different conditions. Its relative deviation coefficients (RDCs) were controlled within ±10%. In another set of calculations, the RDCs of more component blending by different samples were controlled within ±20%. Finally, the near-critical calculation ratio was used for the actual experiments. The experimental results met the initial setting requirements. The results show that our algorithm can flexibly control the content of TCMs. The quality control of the production process of TCMs was achieved by improving the content stability of raw materials using blending. The algorithm provides a groundbreaking idea for quality control of TCMs.
近年来，中医药的应用广度和深度不断扩大，但在应用过程中出现了质量控制问题。设计一种算法来提供混合比例，确保产品与目标的整体相似度高，同时控制个别成分含量的偏差，这一点至关重要。我们通过比较不同的银杏叶样本开发了一种新的混合算法和方案。高一致性样本用于建立混合目标，合格样本用于混合。主成分分析（PCA）用作样本筛选方法。非线性规划算法用于在不同的混合约束下计算混合比例。在一组计算实验中，相同的样本在不同条件下进行混合。其相对偏差系数（RDC）控制在±10%以内。在另一组计算中，不同样本的更多成分混合的 RDC 控制在±20%以内。最后，使用接近临界的计算比例进行实际实验。实验结果符合初始设定要求。结果表明，我们的算法可以灵活控制中药的含量。通过混合使用提高原材料含量稳定性，实现了中药生产过程的质量控制。该算法为中药质量控制提供了一个开创性的思路。
