Application of multiobjective optimization in the deisgn of simulated moving bed systems for chiral drug separation

点击翻译按钮获取中文摘要

The sale of chiral drugs is close to one third of all drug sales worldwide. Ordinary chemical production methods for chiral drugs produce a racemic mixture containing enantiomers having identical chemical compositions but different structrtal orientation in space. It is quite common to find that one isomeric form of a chiral drug has a therapeutic effect on the human body while its enantiomer is harmful. When one isomer is 'good' and the other 'bad', there is obvious benefit from separating the two enantiomers to enhance its safety and tolerability. The Simulated Moving Bed (SMB) system is a viable technology for obtaining pure single enantiomers. Lately, there has been increased interest in the pharmaceutical industry for using SMB technology for enantio-separations due to recent developments in chiral stationary phases and nonlinear chromatographic theory, as well as stringent drug administration policy. Enhanced productivity satisfying stringent product qualities and significant cost savings are possible if optimal design of the SMB is made. In this project, we propose to study in detail the separation and purification of chiral drugs, particularly, for racemate mixtures containing more than two enantiomers. Our main emphasis is in new design and development, and application of multi-objective optimization and advanced real-time control to SMB systems. Detailed simulation models would be developed, which will subsequently be verified experimentally. Thereafter, optimal operating conditions will be computed using multiple objectives and constraints. An adaptation of the state-of-the-art optimization technique, genetic algorithm, will be used. Finally, optimal operating performance would be validated experimentally. These studies would help optimize several objectives while simultaneously satisfying numerous real-life constraints encountered in industry.