Determination of the enantiomeric composition of some molecules of pharmaceutical interest by chemometric analysis of the UV spectra of guest–host complexes formed with modified cyclodextrins

Multivariate regression modeling techniques (PLS-1 regression modeling) were applied to ordinary UV spectral absorption data obtained on solutions containing inclusion complexes formed between homochiral modified cyclodextrins (methyl-β-cyclodextrin, α-, β-, and γ-carboxymethyl cyclodextrins and α-, β-, and γ-hydroxypropyl cyclodextrins) and four guest molecules of pharmaceutical interest (ephedrine, norephedrine, norepinephrine-l-bitartrate, and tryptophan methyl ester). The PLS-1 regression models were developed by correlating the known enantiomeric composition of laboratory prepared samples with ordinary UV absorption spectral data. The regression models were subsequently validated with laboratory-prepared test sets. The rms percent relative error in the predicted mol fraction of (1S, 2R)-(+)-ephedrine, (1S, 2R)-(+)-norephedrine, (R)-(−)-norepinephrine-l-bitartrate, and d-tryptophan methyl ester obtained with the independently prepared test sets was heavily dependent on the host molecule used.