Comparison of Packed-Column Supercritical Fluid Chromatography−Tandem Mass Spectrometry with Liquid Chromatography−Tandem Mass Spectrometry for Bioanalytical Determination of (R)- and (S)-Ketoprofen in Human Plasma Following Automated 96-Well Solid-Phase Extraction
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Abstract
The popularity of packed-column supercritical fluid, subcritical fluid, and enhanced fluidity liquid chromatographies (pcSFC) for enantiomeric separations has increased steadily over the past few years. The addition of a significant amount (typically 20-95%) of a viscosity lowering agent, such as carbon dioxide, to the mobile phase provides a number of advantages for chiral separations. For example, higher mobile-phase flow rates can often be attained without a concomitant loss in chromatographic efficiency since diffusion coefficients, and optimum velocities, are typically higher in pcSFC. Ultratrace enantioselective quantitation of drugs in biomatrixes is an ideal application for these chromatographic attributes. To demonstrate the utility of this approach, a pcSFC tandem mass spectrometry (pcSFC-MS/MS) method was compared to a LC-MS/MS method for quantitation of the (R)- and (S)-enantiomers of ketoprofen (kt), a potent nonsteroidal, anti-inflammatory drug, in human plasma. After preparation using automated solid-phase extraction in the 96-well format, kt enantiomers were separated on a Chirex 3005 analytical column using isocratic conditions. Validation data and study sample data from patients dosed with either orally or topically administered ketoprofen were generated using both pcSFC and LC as the chromatographic methods to compare and contrast these analytical approaches. Generally, most analytical attributes, including specificity, linearity, sensitivity, accuracy, precision, and ruggedness, for both of these methods were comparable with the exception that the pcSFC separation provided a roughly 3-fold reduction in analysis time. A 2.3-min pcSFC separation and a 6.5-min LC separation provided equivalent, near-baseline-resolved peaks, demonstrating a significant time savings for analysis of large batch pharmacokinetic samples using pcSFC.
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