A high-throughput multivariate optimization for the simultaneous enantioseparation and detection of barbiturates in micellar electrokinetic chromatography-mass spectrometry.

The R- and S-configurations of barbiturates display differences in potency and biological activity. In this study, multivariate micellar electrokinetic chromatography-mass spectrometry (MEKC-MS) approach for the simultaneous analysis of three chiral barbiturates (mephobarbital, pentobarbital, and secobarbital) is developed using a polymeric chiral surfactant. After screening 11 amino acid polymeric surfactants, polysodium N-undecenoxycarbonyl-L-isoleucinate (poly-L-SUCIL) was found to be the best chiral selector. The multivariate central composite design (CCD) is used to optimize the chiral resolution, decrease the total analysis time, and improve the ESI-MS signal-to-noise (S/N) ratio. In the preliminary set of experiments, the ranges of the factors investigated in the multivariate approaches are determined. Next, the CCD design is conducted to determine the best overall chiral resolution with shortest possible run times. This optimization resulted in simultaneous enantioseparation in less than 32 min of all three barbiturates with 3-5 fold higher sensitivity by MS compared to UV detection. The adequacy of the multivariate model is validated by three replicate experimental runs at the predicted optimum conditions. The predicted results of MEKC-MS are found to be in good agreement with the experimental data for migration times, resolution, and S/N ratio. The optimized method provided good results in terms of linearity and recovery values of chiral barbiturates spiked in human serum after solid-phase extraction procedure.