Multiobjective optimization of effect-directed planar chromatography as a promising tool for fast selection of polypotent natural products.

A new method for efficiently selecting polypotent natural products is proposed in this study. The method involves using effect-directed HPTLC data and multiobjective optimization algorithms to extract chromatographic signals from HPTLC bioassay images. Three different multiobjective optimization methods, namely Derringer's desirability approach, Technique for order of preference by similarity to ideal solution (TOPSIS), and Sum of ranking differences (SRD), were applied to the chromatographic signals.