Advances in Separation Science : . Molecular Imprinting: Development of Spherical Beads and Optimization of the Formulation by Chemometrics

Sammanfattning: An intrinsic mathematical model for simulation of fixed bed chromatography was demonstrated and compared to more simplified models. The former model was shown to describe variations in the physical, kinetic, and operating parameters better than the latter ones. This resulted in a more reliable prediction of the chromatography process as well as a better understanding of the underlying mechanisms responsible for the separation. A procedure based on frontal liquid chromatography and a detailed mathematical model was developed to determine effective diffusion coefficients of proteins in chromatographic gels. The procedure was applied to lysozyme, bovine serum albumin, and immunoglobulin γ in Sepharose™ CL-4B. The effective diffusion coefficients were comparable to those determined by other methods.Molecularly imprinted polymers (MIPs) are traditionally prepared as irregular particles by grinding monoliths. In this thesis, a suspension polymerization providing spherical MIP beads is presented. Droplets of pre-polymerization solution were formed in mineral oil with no need of stabilizers by vigorous stirring. The droplets were transformed into solid spherical beads by free-radical polymerization. The method is fast and the performance of the beads comparable to that of irregular particles. Optimizing a MIP formulation requires a large number of experiments since the possible combinations of the components are huge. To facilitate the optimization, chemometrics was applied. The amounts of monomer, cross-linker, and porogen were chosen as the factors in the model. Multivariate data analysis indicated the influence of the factors on the binding and an optimized MIP composition was identified. The combined use of the suspension polymerization method to produce spherical beads with the application of chemometrics was shown in this thesis to drastically reduce the number of experiments and the time needed to design and optimize a new MIP.