Optimizing multiple chromatographic parameters (<i>e.g.</i> temperature, gradient elution, pH, buffer concentration, <i>etc</i>.) during analytical method development can often be a very tedious task, especially when dealing with complex mixtures of closely related species in reaction mixtures. For such difficult separations, building a matrix for optimizing temperature and gradient conditions is necessary, which can be virtually impossible without the aid of a modeling software. Herein, several examples of using chromatography modeling software (ACD labs/LC simulator) to develop robust analytical methods for challenging separation and analysis of multicomponent mixtures are presented. Examples include recently published work such as: 1) development of a generic IC-CD method for analysis of 20 nucleotides, 2) UHPLC procedure using chaotropic agents for analysis new drug products and related impurities, and 3) Generic ID-CD methodology for determination of residual palladium scavengers in drug products. The strong agreement between both simulated and experimental outcomes illustrates the power of modern computer-assisted separation modeling as a framework for developing robust chromatographic methods. Some of the optimized analytical methods were successfully translated into separations at preparative scale, and also also used as an effective tool to improve the productivity of methods for purification of new drug substances.

Computer-assisted separation modeling in analytical space translated into improved preparative chromatography productivity

2019 Fall National Meeting

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