Development and Validation of Methods for Characterization of Multi-Component Systems in Preparative LC
Sammanfattning: This thesis concerns the development and validation of methods for characterization of multi-component preparative LC systems. Measurements of competitive adsorption isotherms are performed to gain detailed information about the interactions inside the chromatography column. This information increases our understanding of the separation process and makes it possible to perform computer simulations and numerical optimizations to find optimal operating conditions.The methods under focus are called “the tracer-pulse method”, “the inverse method”, and “the inverse method on plateaus”. They are extensions of existing methods, with new experimental and numerical procedures to enable rapid and accurate multi-component adsorption isotherm determination. In the validation it was shown that they can produce results agreeing with traditional methods and that the acquired adsorption isotherm parameters can be used in simulations to accurately predict the outcome of preparative LC separations.The methods were used to characterize several complex LC systems and two phenomena were discovered and theoretically treated: 1) The presence of invisible deformed peaks in single-component systems. 2) Peak deformations encountered with modern chiral stationary phases, caused by strongly adsorbed eluent additives. The latter type of deformation was highly tuneable and it was possible to adjust the enantiomer peak shapes so that the peaks tailed in opposite directions with the sharp sides in between, yielding baseline resolution at remarkably high sample loads.In a final applied study both the LC-based perturbation peak method and a biosensor method based on surface plasmon resonance (SPR) were used for the first time for detailed characterization of chiral drug-protein interactions. The fundamental properties of the two very different methods were compared and it was found that the LC method is more suitable for multi-component analysis and that the SPR method is more suitable for stronger interactions.
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