The principles of computer-assisted optimization of chromatographic systems are well established. The elution response for a given parameter/component is modeled according to defined response curves, and an optimum value for the parameter is produced based on the success criteria of the user. In theory, the combination of a modeling toolset with modern automation can produce tremendous power to create optimal chromatographic methods with little onus on the chromatographer. In practice, there are considerable challenges that must be overcome by any approach to the efficient combination of modeling and automation. Perhaps most notable of these challenges is the problem of component detection and tracking in the context of changes in chromatographic variables. As modern instrumentation offers opportunities for exploration of new selectivities due to extremely fast run times, it introduces more challenges with regards to efficient reduction of data to a manageable amount of elution data.

This paper will describe a new system that incorporates experimental design principles, chemometric data extraction of LC/MS and LC/UV hyphenated traces, chromatographic modeling, and automation. Several real-world examples will be used to illustrate the practical application of both MS and UV detection, good experimental design principles, and user interaction with method development projects.