Determination of enantiomeric composition of samples by multivariate regression modeling of spectral data obtained with cyclodextrin guest–host complexes—Effect of an achiral surfactant and use of mixed cyclodextrins

The determination of the enantiomeric composition of samples by chemometric modeling of spectral data was investigated for samples of N,N′-bis-(α-methylbenzyl) sulfamide and tryptophan methyl ester hydrochloride. Multivariate regression models (PLS-1) were developed from spectral data obtained on solutions containing N,N′-bis-(α-methylbenzyl)sulfamide or tryptophan methyl ester hydrochloride in the presence of sodium dodecyl sulfate and mixed cyclodextrin host molecules. The regression models were subsequently used to predict the enantiomeric composition of laboratory-prepared test samples of N,N′-bis(α-methylbenzyl)sulfamide or tryptophan methyl ester hydrochloride. The capability of the models to accurately predict the enantiomeric composition was evaluated in terms of the root-mean-square percent relative error (RMS %R.E.) as calculated from the results obtained with independently prepared validation sets of samples. It was found that the presence of SDS in most cases either had little effect on the predictive ability of the model or it actually reduced the predictive ability of the model. Moreover, it was found that the use of mixed CDs, either in the presence or absence of SDS, reduced the predictive ability of the regression model when compared with results obtained with individual CDs.