基于多样本系统参数的全球保留模型,用于优化药用植物的染色指纹
P Peiró-Vila1, M C García-Alvarez-Coque1, J R Torres-Lapasió1
1Department of Analytical Chemistry, Faculty of Chemistry, Universitat de València, C/ Dr. Moliner 50, 46100, Burjassot, Spain.
Analytica chimica acta
|January 20, 2025
概括
全球模型简化了复杂的传统医学产品的液体染色学方法开发. 通过整合多种植物数据,这些模型可以准确地预测新植物样本的最佳分离,使用最少的实验,提高质量控制.
科学领域:
- 分析化学 分析化学
- 染色体学 染色体学 是一种染色学.
- 化学测量 化学测量 化学测量
背景情况:
- 由于未识别的化合物,传统医学的液体染色学方法开发是复杂的.
- 监管机构要求进行染色指纹分析以进行质量控制.
- 传统的建模方法与复杂的样本作斗争.
研究的目的:
- 以全球模型来证明使用分离系统进行表征的可行性.
- 为了使各种植物矩阵的梯度程序的优化.
- 评估MATLAB全球优化工具箱的性能,以适应全球模型.
主要方法:
- 使用来自多种植物 (香,绿茶,) 独立实验设计的染色体.
- 开发了综合列,溶剂和溶解物特定参数的通用全球模型.
- 应用MATLAB全球优化工具箱用于模型拟合和与交替回归进行比较.
主要成果:
- 全球模型成功地描述了分离系统,并为多个工厂实现了梯度程序优化.
- 一般化模型允许准确预测外部植物 (薄荷,pennyroyal) 的最佳分离,只需进行一个额外的实验.
- 使用全球模型预测的最佳分离显示了与特定溶液模型可比的准确性.
结论:
- 采用多种植物数据的增强型全球模型提供了对色谱系统的可靠特征.
- 一般化模型提供可转移的系统参数和准确的预测,以最小的实验输入为新的样品.
- 这种方法有效地将系统属性与溶液保留分开,在没有单个化合物标准的情况下实现高预测精度.
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