Hydrophilic interaction ultra performance liquid chromatography retention prediction under gradient elution.

The development and application of new separation mechanisms such as hydrophilic interaction chromatography (HILIC) is of high importance for the simultaneous analysis of polar molecules such as primary metabolites. However the retention mechanism in HILIC is not fully understood and as a result retention prediction tools are not at hand for this chromatographic approach. In the present report we study the utility of a simple algorithm, based on a simple linear and/or a simple logarithmic retention model, for retention prediction in HILIC gradient separation of a mixture of 23 selected compounds including (poly)amines, amino acids, saccharides, and other molecules. Utilizing two types of gradient elution programs with or without an isocratic part, retention data were collected in order to build prediction models. Starting from at least three gradient runs the prediction of analyte retention was very satisfactory for all gradient programs tested, providing useful evidence of the value of such retention time prediction methodologies.

Retention prediction of a set of amino acids under gradient elution conditions in hydrophilic interaction liquid chromatography.

The analysis of amino acids presents significant challenges to contemporary analytical separations. The present paper investigates the possibility of retention prediction in hydrophilic interaction chromatography (HILIC) gradient elution based on the analytical solution of the fundamental equation of the multilinear gradient elution derived for reversed-phase systems. A simple linear dependence of the logarithm of the solute retention (ln k) upon the volume fraction of organic modifier (φ) in a binary aqueous-organic mobile is adopted. Utility of the developed methodology was tested on the separation of a mixture of 21 amino acids carried out with 14 different gradient elution programs (from simple linear to multilinear and curved shaped) using ternary eluents in which a mixture of methanol and water (1:1, v/v) was the strong eluting member and acetonitrile was the weak solvent. Starting from at least two gradient runs, the prediction of solute retention obtained under all the rest gradients was excellent, even when curved gradient profiles were used. Development of such methodologies can be of great interest for a wide range of applications.

Retention prediction in reversed-phase liquid chromatography systems with methanol/water mobile phases containing different alkanols as additives.

In an effort to gain enhancement of selectivity in reversed-phase liquid chromatography, retention was tuned in this study by introducing short and medium straight-chained-length alkanol additives (methanol (MeOH), ethanol, 1-propanol, 1-butanol, 1-pentanol, 1-hexanol or 1-heptanol) at low concentrations in mobile phases containing MeOH as the main organic solvent. A six-parameter retention model considering simultaneously the contents of the main organic modifier and of the alcohol additive as well as of the number of alkyl chain of additive was developed by a direct combination of equations expressing separately a linear dependence of the retention upon each of these factors. The effectiveness of the above model was tested in the retention prediction of a mixture of six alkylbenzenes under isocratic conditions with mobile phases containing as an additive any member of the homologues series of alkanols (with 1-7 carbon atoms) at different low concentrations in a wide range of MeOH-water mixtures. The prediction was excellent in all cases even when the alkanol additives used in experiments for the fitting procedure are different than those used in chromatographic runs done for testing the prediction ability of the proposed model.

Direct RP-HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detection.

The combined use of a dual-UV detector, a fluorimetric one and of a multiple electrochemical (EC) detector equipped with a dual electrode, consisting of a conventional size 3 mm diameter glassy carbon electrode (GCE) and of a pair of 30 mum thick carbon microfibers, is proposed for the determination of 15 amino acids, two dipeptides and creatinine. This online coupling of the above detection modes could partially replace amino acid analysis by derivatization methods, since it solves problems concerning the direct detection of selected underivatized amino acids. Additionally, it was proved that the use of multiple-detection allows positive peak identification in a single chromatographic run, yields more information for free amino acids and solves in some cases the problem of chromatographic resolution. In order to optimize the detection conditions of the underivatized amino acids and related compounds by different detectors, their detection characteristics were determined by adequate preliminary experiments. The electro-oxidation characteristics of the underivatized compounds of interest were determined by hydrodynamic voltammetry using a flow cell with a macrodisc GCE and by ex-situ voltammetry using both a GCE of conventional size and a carbon fiber disk microelectrode. Important practical advantages of microfiber and microdisk electrodes with respect to macroelectrodes were demonstrated.

Modeling the effects of different mobile phase compositions and temperatures on the retention of various analytes in HPLC.

A mathematical model is proposed for representing the combined effects of mobile phase solvent composition and temperature on the retention of various analytes in HPLC. The applicability of the model in describing the retention of four macrolides in aqueous mixtures of methanol and acetonitrile determined at 20-80 degrees C in various volume fractions of the organic modifiers was shown. The mean percentage deviation (MPD) was computed as an accuracy criterion in which the overall MPD of four analytes investigated in this work was 3.9+/-1.5% (N=72). The proposed model could be reduced to two simpler versions. The first version concerning the retention data of analytes in one organic modifier at various temperatures produced for the retention description of the above experimental system as well as for the retention of three benzodiazepines in aqueous mixtures of methanol at 25-40 degrees C an overall MPD of 3.6+/-1.8%. The more reduced version of the model for calculating the retention factor of one analyte in a given organic modifier at various temperatures produced an overall MPD of 1.7+/-1.1% for both the experimental systems studied. The accuracy of the proposed model is compared with recent models to predict the retention of an analyte with respect to solvent component of the mobile phase and the temperature of column in which the results were comparable. The main advantage of the proposed model is its capability to predict the retention of various analytes considering (i) temperature of the column, (ii) the mobile phase solvent composition, (iii) the chemical structure of the analytes and (iv) the nature of organic modifier.

Combined effect of temperature and organic modifier concentration on the retention under single mode gradient conditions in reversed-phase HPLC.

The combined effect of temperature, T, and organic modifier concentration, phi, on the retention under gradient conditions in RPLC is studied by considering, both theoretically and experimentally gradients, of phi at constant T and gradients of T at constant phi. Two approaches are examined: in the first approach the prediction of the elution time of a sample solute is based on the isocratic/isothermal properties of this solute. The second approach is based on a direct fitting procedure of a proper retention model to 2-D isocratic/T-gradient or isothermal/phi-gradient retention data. These approaches were tested using alkylbenzes in eluting systems modified by ACN. We found that both approaches can give excellent predictions under certain prerequisites. However, the first approach exhibits the notable advantage that it can be used effectively to predict retention times under any kind of phi-gradients at constant T or T-gradients at constant phi. The second approach has the advantage that it is relatively simple but its applicability is very restricted since its predictions are satisfactory only if the gradients are of the same kind with those used in the fitting procedure and the conditions lie within those used for fitting.

QSRR Modeling for Metabolite Standards Analyzed by Two Different Chromatographic Columns Using Multiple Linear Regression.

Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.

Modeling the effects of type and concentration of organic modifiers, column type and chemical structure of analytes on the retention in reversed phase liquid chromatography using a single model.

A previously proposed model for representing the retention factor (k) of an analyte in mixed solvent mobile phases was extended to calculate the k of different analytes with respect to the nature of analyte, organic modifier, its concentration and type of the stationary phase. The accuracy of the proposed method was evaluated by calculating mean percentage deviation (MPD) as accuracy criterion. The predicted vs. observed plots were also provided as goodness of fit criteria. The developed model prediction capability compared with a number of previous models (i.e. LSER, general LSER and Oscik equation) through MPD and fitting plots. The proposed method provided acceptable predictions with the advantage of modeling the effects of organic modifiers, mobile phase compositions, columns and analytes using a single equation. The accuracy of developed model was checked using the one column and one analyte out cross validation analyses and the results showed that the developed model was able to predict the unknown analyte retention and the analytes retentions on unknown column accurately.