Computer Assisted Method Development in Liquid Chromatography

This paper describes potential applications of computer-assisted chemometrics in method development in liquid chromatography. These include modeling of retention (isocratic, gradient, molecular modeling, artificial neural networks), assessment of separation (peak capacity), single and multiple objective optimization approach, advanced optimization algorithms (genetic algorithms, simulated annealing) and method transfer issues (transfer of methods between instruments and/or laboratories). Selected topics provide an accessible source of information needed for successful increase of chromatographic efficiency and economic feasibility (higher sample throughput) in liquid chromatography.