Hroch Miloš
Department of Medical Biochemistry, Faculty of Medicine in Hradec Králové, Charles University, Šimkova 870, 500 03, Hradec Králové, Czech Republic.
Anal Bioanal Chem. 2025 Mar;417(6):1113-1125. doi: 10.1007/s00216-024-05705-y. Epub 2025 Jan 10.
The visual evaluation of data derived from screening and optimization experiments in the development of new analytical methods poses a considerable time investment and introduces the risk of subjectivity. This study presents a novel approach to processing such data, based on factor analysis of mixed data and hierarchical clustering - multivariate techniques implemented in the R programming language. The methodology is demonstrated in the early-stage screening and optimization of the chromatographic separation of 15 structurally diverse drugs that affect the central nervous system, using a custom R Language script. The presented explorative approach enabled the identification of key parameters affecting the separation and significantly reduced the time required to evaluate the comprehensive dataset from the screening experiments. Based on the data analysis results, the optimal combination of stationary phase and mobile phase composition was selected, considering retention, overall resolution, and peak shape of compounds. Additionally, compounds vulnerable to changes in selected chromatographic conditions were identified. As a complement to the presented R Language script, a web-based application ChromaFAMDeX has been developed to offer an intuitive interface that enhances the accessibility of the used statistical methods. Accompanying the publication, the R script and the link to the standalone application are provided, enabling replication and adaptation of the methodology.
在新分析方法开发过程中，对筛选和优化实验所得数据进行视觉评估需要投入大量时间，并且存在主观性风险。本研究提出了一种处理此类数据的新方法，该方法基于混合数据的因子分析和层次聚类——这是在R编程语言中实现的多元技术。使用自定义R语言脚本，在对15种影响中枢神经系统的结构各异的药物进行色谱分离的早期筛选和优化过程中展示了该方法。所提出的探索性方法能够识别影响分离的关键参数，并显著减少评估筛选实验综合数据集所需的时间。基于数据分析结果，在考虑化合物保留时间、整体分离度和峰形的基础上，选择了固定相和流动相组成的最佳组合。此外，还识别出了易受所选色谱条件变化影响的化合物。作为所展示的R语言脚本的补充，已开发了一个基于网络的应用程序ChromaFAMDeX，以提供一个直观的界面，增强所用统计方法的可及性。随论文一同提供了R脚本和独立应用程序的链接，以便能够复制和应用该方法。
