Program for the interpretive optimization of two-dimensional resolution

Abstract

The challenge of fully optimizing LC×LC separations is horrendous. Yet, it is essential to address this challenge if sophisticated LC×LC instruments are to be utilized to their full potential in an efficient manner. Currently, lengthy method development is a major obstacle to the proliferation of the technique, especially in industry. A program was developed for the rigorous optimization of LC×LC separations, using gradient-elution in both dimensions. The program establishes two linear retention models (one for each dimension) based on just two LC×LC experiments. It predicts LC×LC chromatograms using a simple van-Deemter model to generalize band-broadening. Various objectives (analysis time, resolution, orthogonality) can be implemented in a Pareto-optimization framework to establish the optimal conditions. The program was successfully applied to a separation of a complex mixture of 54 aged, authentic synthetic dyestuffs, separated by ion-exchange chromatography and ion pair chromatography. The main limitation experienced was the retention-time stability in the first (ion-exchange) dimension. Using the PIOTR program LC×LC method development can be greatly accelerated, typically from a few months to a few days.

Optimizing separations in online comprehensive two‐dimensional liquid chromatography

“…See Supporting Information S3 for a more detailed clarification on the chromatographic conditions, analyte mixture, and the optimization parameters used to arrive at this PO‐plot. Plot created using the Program for Interpretive Optimization of 2D Resolution (PIOTR) …”

“…Sarrut and co-workers pointed out that the 2 D column equilibration and dwell F I G U R E 1 4 Schematic representation of an algorithmic optimization procedure. Reproduced from [187] with permission volume play a significant role in the optimization of the total analysis time [35].…”

“…See Supporting Information S3 for a more detailed clarification on the chromatographic conditions, analyte mixture, and the optimization parameters used to arrive at this PO-plot. Plot created using the Program for Interpretive Optimization of 2D Resolution (PIOTR) [187] and mobile phase, significantly influence the type of interactions between analyte and stationary-phase packing [105,188]. As a result, the selected retention model may not adequately describe the retention behavior, resulting in incorrect predictions.…”

Optimizing gradient conditions in online comprehensive two‐dimensional reversed‐phase liquid chromatography by use of the linear solvent strength model

“…Various combinations of runs were used to calibrate model parameters, k w and S, for each dimension and each PC. The combined runs used for calibration were as follows: all (1 model with 24 runs used for calibration, 0 runs to predict); the leave-one-out approach with all runs but one (24 models with each 23 runs used for calibration, 24 runs to predict); the split-half approach with calibration performed using either run 3,5,6,7,10,11,13,14,18,19,22,23 (1 model with 12 runs used for calibration, 12 other runs to predict), or run 1,2,4,8,9,12,15,16,17,20,21,24 (1 model with 12 runs used for calibration, other 12 runs to predict); six runs, namely, 1, 20-24 (1 model with 6 runs used for calibration, 18 runs to predict), or two runs namely 1 and 20 (1 model with two runs used for calibration, 22 runs to predict). The root mean square error (RMSE) or the root mean square error of prediction (RMSEP) was calculated for all six approaches, both approaches essentially estimate the average distance from the modeled (RMSE) or predicted (RMSEP) f cov to the measured f cov .…”

“…The aim of this study was therefore to develop and test a novel model to predict the separation space occupied by peaks as a fraction of the total available separation space, that is, f cov , for a sample in a particular RP × RP system. In 2016, an elegantly executed approach based on IEC and ion pairing chromatography, was published by Pirok and Schoenmakers et al [20]. These authors obtained good predictions of ion pairing chromatographic retention using the linear solvent strength (LSS) model, but the prediction of IEC retention was less accurate.…”