Sequential Surrogate Optimization for Supercritical Fluid Extraction–Supercritical Fluid Chromatography–Tandem Mass Spectrometry Method Development
Kevin Schug explains how surrogate optimization streamlines SFE–SFC–MS method development, achieving R² values up to 0.97 while boosting sensitivity by 15%
Method development in supercritical fluid extraction–supercritical fluid chromatography (SFE–SFC) has long been complicated by the sheer number of interacting variables—extraction pressure, dynamic and static extraction time, modifier concentration, flow rate, chromatography pressure, and loading split ratio, among others—that traditional one-factor-at-a-time and even standard design-of-experiments approaches struggle to handle efficiently. A new study in Analytica Chimica Acta, "Sequential Surrogate Optimization for Supercritical Fluid Extraction – Supercritical Fluid Chromatography – Tandem Mass Spectrometry Method Development,"1 aims to address this problem by applying an iterative surrogate-modelling strategy to optimize seven SFE–SFC variables simultaneously across a panel of structurally diverse analytes, including reserpine, vigabatrin, hydromorphone, and hydrocodone. Rather than front-loading a full experimental matrix, the approach builds and refines a model using molecular similarity metrics to guide how the design space expands from one analyte to the next. The result, according to the authors, is a more data-efficient route to robust methods capable of handling complex, multi-analyte targets. LCGC International spoke with Kevin Schug to find out more about the benefits this approach offers the analyst.