Optimization strategies in chiral liquid chromatography
The advent of new LC column technology for the separation of chiral drugs and metabolites has transformed the practice of enantiomer separation for the quality control of chiral drugs and for biological studies on chiral entities. The wide variety of separation principles now exploited for chiral analysis has led to the development of more than 40 different columns, plus the complementary technology where a chiral mobile phase additive is used with a regular reversed-phase column. The multiplicity of choice for chiral separations can present major difficulties in selecting a suitable starting point for a particular enantiomer separation. However, for a particular chiral modality, the problem is then to rapidly assess its suitability for a given analyte, and then the optimize the enantiomeric resolution observed. These objectives can be achieved by using a combination of systematic optimization strategies, together with diagnostic tests for peak resolution and homogeneity. Thus factorial design (Berridge 1985) can be used to assess the practical range and extent of interaction of those eluent parameters that determine chiral resolution. This can then be followed by computer-aided sequential simplex optimization to establish the conditions for the best available resolution on the specific chiral system selected (Fell et al . 1989). The central composite (factorial) design requires 1) experiments for k factors, and permits a second-order polynomial to be fitted to the data, with the advantage that the model so developed can be used predictively (Berridge 1985). Simplex lattice design is a form of simultaneous optimization design based on isoeluotropic mixtures of mobile phase to generate data that allow a linear model to be developed for predictive purposes (Schoenmakers 1986).