Efficiency of Solvatic Sorption Model for Predicting the Retention in Multi-step Gradient RP-LC with Different Stationary Phases (original) (raw)
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Proceedings of the Estonian Academy of Sciences, 2016
Currently several different approaches are used for speed-up and cost reduction for new method development in reversed-phase high-performance liquid chromatography. During this research, application of a solvatic retention model of reversed-phase high-performance liquid chromatography was studied to predict the retention of phenylisothiocyanate derivatives of 25 natural amino acids, working with different stationary phases. The gradient elution mode was used, with methanol and acetonitrile as the aqueous mobile phases. Retention factors were calculated from the molecular parameters of the structures of the analytes and stationary and mobile phase properties. Such step-by-step methods, which include the first-guess prediction of initial conditions from structural formulae and fine tuning parameters of the retention model using data from successive runs, can save time and consequently will reduce the cost of method development and optimization.
Latvian Journal of Chemistry, 2014
We report our experience with highly polar and charged analyte retention parameter prediction for a reversed-phase high-performance liquid chromatographic method. The solvatic retention model has been used to predict retention of phenylisothiocyanate derivatives of 25 natural amino acids under gradient elution conditions. Retention factors have been calculated from molecular parameters of analyte structures and from the column and eluent characteristics. A step-by-step method which includes the first guess prediction of initial conditions from structural formula and fine tuning of the retention model parameters using data from successive runs can substantially save method development time
Acta Chimica Slovenica, 2019
There are several different approaches for LC method development; beside traditional, different software programs for method development and optimization are available. The solvatic retention model of reversed-phase LC was applied for prediction of retention in the gradient elution mode for aripiprazole and its related substances described in European Pharmacopoeia. As some of these compounds have very similar and others quite different chemical structure, their separation is challenge. Prediction was suitable on examined stationary phases (C18, C8 and phenyl-hexyl) with 0.1% phosphoric acid as aqueous mobile phase and acetonitrile or methanol as organic modifier. Predicted retention times take into account structural formulae of compounds and properties of stationary and mobile phases result in average difference of 14-17% compared to experimental ones on phenyl-hexyl stationary phase, where the highest matching was obtained. After utilisation of the retention models with data from one experimental run, the average difference decrease to maximal 7% and after contribution of data from two experimental runs, to maximal 2%. For majority of studied compounds difference between predicted and experimental values on all examined stationary phases is lower than 3%.
Analytical …, 2009
The theory of multimode gradient elution in liquid chromatography involving combined gradients of the mobilephase composition with flow rate and column temperature is presented, and a very simple stepwise method that allows for the calculation of the elution time of a sample solute under all gradient conditions is proposed. The theory is successfully applied to the separation of 12 o-phthalaldehyde derivatives of amino acids in eluting systems modified by acetonitrile. Average errors below 2.9% have been found in the retention prediction using the above method, which is supported by adequate models and algorithms capable of describing the chromatographic behavior of solutes upon changes in the separation factors, such as the modifier content, flow rate, and temperature.
Analytical chemistry, 2006
The coupling of stepwise mobile phase gradient elution and flow programming is proposed as an integrated approach to the general elution problem in reversed-phase liquid chromatography. A model is developed to describe the above separation process performed under simultaneous programming of two separation parameters by extending our previous work on the rigorous derivation of the fundamental equation governing the concentration gradient of organic modifier in the mobile phase, that is, a single gradient elution mode (Anal. ). The theory was tested in the retention prediction and separation optimization of 18 o-phthalaldehyde derivatives of amino acids in eluting systems modified by acetonitrile or methanol. The retention prediction obtained for all solutes under all dual-mode gradient conditions was excellent. In addition, it has been shown that the combination of mobile phase and flow rate programming modes is particularly favorable, whereas the separations among the analytes were considerably improved by using the acetonitrile eluting system, as compared to those obtained by the methanol system.
Talanta, 2011
In an effort to enhance complex mixture separations by using small amounts of a homologous series of alkanols as additives in the mobile phases, it was proposed an optimization algorithm based on a sixth-parameter retention model. This model considers simultaneously the contents of the main organic modifier and of the alkanol additive in the mobile phase as well as of the number of alkyl chain of the additive. This model is in fact a modification of a previously one derived in a recently published paper for the retention description of a mixture of purely hydrophobic alkylbenzenes under isocratic conditions with mobile phases containing alkanol additives. The effectiveness of the new retention model as well as the optimization algorithm was successfully applied to the separation of ten o-phthalaldehyde (OPA) derivatives of amino acids. Indeed, the new retention model exhibited an excellent prediction performance since the obtained overall predictive error between calculated and experimental times was only 2.8% for all isocratic runs by using a variety of mobile phase compositions containing any alkanol homologue even different than those used in the starting/fitting experiments. Moreover, a perfect resolution of the above amino acid mixture was achieved within only 7.4 min in the chromatogram recorded using the optimal mobile phase determined by means of the simple optimization algorithm proposed in this study.
Journal of Chromatography A, 2002
The polarity parameter model previously developed: log k = (log k) 0 + p(P N m − P N s) has been successfully applied to study several chromatographic systems involving new generation RPLC columns (Luna C18, Resolve C18, XTerra MSC18, and XTerra RP18). In this model the retention of the solutes (log k) is related to a solute parameter (p), a mobile phase parameter (P N m) and two chromatographic system parameters [P N s and (log k) 0 ]. The studied systems have been characterized with different acetonitrile-water and methanol-water mobile phases, using a set of 12 neutral solutes of different chemical nature. The polarity parameter model allows prediction of retention of any solute in any mobile phase composition just using the retention data obtained in one percentage of organic modifier and the polarity parameters established in the characterization of the chromatographic systems. This model also allows the solute polarity data transference between RPLC characterized systems, so it is possible to predict the retention in various RPLC systems working experimentally with just one of them. Moreover, the global solvation parameter model has also been applied to the same chromatographic systems using a wide set of solutes in order to compare its predictive ability with the one of the polarity parameter model. The results clearly show that both models predict retention with very similar accuracy but the polarity parameter model requires much less preliminary experimental measurements to achieve equivalent results than the global solvation approach.
ELECTROPHORESIS, 2019
The hydrophobic subtraction model (HSM) combined with quantitative structure‐retention relationships (QSRR) methodology was utilized to predict retention times in reversed‐phase liquid chromatography (RPLC). A selection of new analytes and new RPLC columns that had never been used in the QSRR modeling process were used to verify the proposed approach. This work is designed to facilitate early prediction of co‐elution of analytes in pharmaceutical drug discovery applications where it is advantageous to predict whether impurities might be co‐eluted with the active drug component. The QSRR models were constructed through partial least squares regression combined with a genetic algorithm (GA‐PLS) which was employed as a feature selection method to choose the most informative molecular descriptors calculated using VolSurf+ software. The analyte hydrophobicity coefficient of the HSM was predicted for subsequent calculation of retention. Clustering approaches based on the local compound ty...