Abstract

The hydrophobicity and specific hydrophobic surface area of 21 commercial anticancer drugs were determined by reversed-phase high-performance liquid chromatography on an octadecyl-silica column using methanol-water mixtures as eluents. Linear correlations were calculated between the log k' values and the methanol concentration of the eluent, the intercept and slope were considered as the best estimation of the hydrophobicity and specific hydrophobic surface area. The relationship between retention characteristics and physicochemical parameters of drugs was evaluated by multivariate mathematical statistical methods, such as principal component analysis followed by two-dimensional non-linear mapping, varimax rotation and by cluster analysis. Anticancer drugs can be well separated by reversed-phase HPLC. Various multivariate mathematical statistical calculations indicate that the retention of the investigated drugs is mainly governed by hydrophobic and steric parameters. The results suggest that the use of principal component analysis followed by two-dimensional non-linear mapping is superior to cluster analysis for the evaluation of large retention data matrices.

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