Application of Principal Components Analysis to TLC Data for 596 Basic and Neutral Drugs in Four Eluent Systems
Open Access
- 1 December 1984
- journal article
- research article
- Published by Oxford University Press (OUP) in Journal of Chromatographic Science
- Vol. 22 (12), 538-547
- https://doi.org/10.1093/chromsci/22.12.538
Abstract
Principal component analysis (PCA) of the Rf values for 596 basic and neutral drugs in four eluent mixtures provided a significant two-component model which explained 77% of the total variance. Each drug was characterized on a plane by two principal component scores. The loading plot shows that three eluent mixtures are clustered into the same group providing similar information. For identification of unknowns, the method provided a drastic reduction of the range of possibilities to a few candidates.This publication has 2 references indexed in Scilit:
- Identification of Drugs by Principal Components Analysis of Rf Data Obtained by TLC in Different Eluent SystemsJournal of Analytical Toxicology, 1983
- Cross-Validatory Estimation of the Number of Components in Factor and Principal Components ModelsTechnometrics, 1978