Retention modeling and method development in hydrophilic interaction chromatography

A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography

Artificial intelligence and machine learning techniques are increasingly used for different tasks related to method development in liquid chromatography. In this study, the possibilities of a reinforcement learning algorithm, more specifically a deep deterministic policy gradient algorithm, are evaluated for the selection of scouting runs for retention time modeling. As a theoretical exercise, it is investigated whether such an algorithm can be trained to select scouting runs for any compound of interest allowing to retrieve its correct retention parameters for the three-parameter Neue-Kuss retention model. It is observed that three scouting runs are generally sufficient to retrieve the retention parameters with an accuracy (mean relative percentage error MRPE) of 1 % or less. When given the opportunity to select additional scouting runs, this does not lead to a significantly improved accuracy. It is also observed that the agent tends to give preference to isocratic scouting runs for retention time modeling, and is only motivated towards selecting gradient scouting runs when penalized (strongly) for large analysis/gradient times. This seems to reinforce the general power and usefulness of isocratic scouting runs for retention time modeling. Finally, the best results (lowest MRPE) are obtained when the agent manages to retrieve retention time data for % ACN at elution of the compound under consideration that spread the entire relevant range of ACN (5 % ACN to 95 % ACN) as well as possible, i.e., resulting in retention data at a low, intermediate and high % ACN. Based on the obtained results, we believe reinforcement learning holds great potential to automate and rationalize method development in liquid chromatography in the future.

Computer-driven optimization of complex gradients in comprehensive two-dimensional liquid chromatography

Method development in comprehensive two-dimensional liquid chromatography (LC × LC) is a complicated endeavor. The dependency between the two dimensions and the possibility of incorporating complex gradient profiles, such as multi-segmented gradients or shifting gradients, renders method development by "trial-and-error" time-consuming and highly dependent on user experience. In this work, an open-source algorithm for the automated and interpretive method development of complex gradients in LC × LC-mass spectrometry (MS) was developed. A workflow was designed to operate within a closed-loop that allowed direct interaction between the LC × LC-MS system and a data-processing computer which ran in an unsupervised and automated fashion. Obtaining accurate retention models in LC × LC is difficult due to the challenges associated with the exact determination of retention times, curve fitting because of the use of gradient elution, and gradient deformation. Thus, retention models were compared in terms of repeatability of determination. Additionally, the design of shifting gradients in the second dimension and the prediction of peak widths were investigated. The algorithm was tested on separations of a tryptic digest of a monoclonal antibody using an objective function that included the sum of resolutions and analysis time as quality descriptors. The algorithm was able to improve the separation relative to a generic starting method using these complex gradient profiles after only four method-development iterations (i.e., sets of chromatographic conditions). Further iterations improved retention time and peak width predictions and thus the accuracy in the separations predicted by the algorithm.

[Rapid determination of 10 fat-soluble vitamins in health foods by ultra performance convergence chromatography]

Fat-soluble vitamins are important efficacy indicators in health foods because they are essential for human physiological functions. The existing method for the simultaneous determination of fat-soluble vitamins has various problems, such as limited determination components, complex sample, pretreatment process, and high requirements for personnel operating ability. Therefore, establishing a fast, simple, and accurate method that can detect various common fat-soluble vitamins at the same time is necessary. In this study, a method for the simultaneous determination of 10 commonly used fat-soluble vitamins such as vitamin A acetate (VA acetate), vitamin A palmitate (VA palmitate), vitamin E acetate (VE acetate), vitamin K1 (VK1), α-tocopherol, β-tocopherol, γ-tocopherol, δ-tocopherol, vitamin D2(VD2) and vitamin D3 (VD3) in health foods was established by ultra performance convergence chromatography (UPC2). First, the contents of about 1.0 g of capsule samples were accurately weighed. A grinder was used to grind tablet samples into powder. The powder mixture was then precisely weighed at 2.0 g. Both substances were placed in 50 mL brown stopper tubes. The test tube was then filled with 20 mL 75% dimethylsulfoxide (DMSO) aqueous solution for demulsification. The tubes were then sonicated before being extracted with n-hexane. The centrifuged supernatant was added to vials for detection. Viridis HSS C18 SB column (100 mm×3.0 mm, 1.8 μm) was applied and CO2 was used as the mobile phase A. After comparing the influence of acetonitrile, methanol, and their mixture on chromatographic peak separation, acetonitrile-methanol (85∶15, v/v) was used as the mobile phase B. The injection volume was 1 μL. Using simulator software, the optimal chromatographic conditions were obtained after a set of three-factor orthogonal experiments of flow rate, gradient slope, and column temperature. The flow rate and column temperature were both set at 1.9 mL/min and 30 ℃. Furthermore, the maximum absorption wavelength of these 10 fat-soluble vitamins was selected for detection. Ten vitamins were baseline separated after 7 min of gradient elution. The limits of detection (LODs) and quantification (LOQs) of capsule samples were 0.4-60 μg/g and 2-150 μg/g, respectively, whereas the results for tablet samples were 0.2-30 μg/g and 0.8-75 μg/g. The linear ranges of the 10 fat-soluble vitamins were 0.1-100 μg/mL. The recoveries of spiked samples ranged from 96.5% to 113.9%, with RSD values less than 4%. Precision, stability, and repeatability RSD values were all less than 2%. By comparison, the determination results of this method were basically consistent with the existing national food safety standards. This method is simple, rapid, sensitive, and accurate, and it can meet the detection requirements of the 10 fat-soluble vitamins in health foods. Simultaneously, this method lays the foundation for the rapid and simultaneous detection of fat-soluble vitamins in existing health foods.

Accuracy of retention model parameters obtained from retention data in liquid chromatography

In liquid chromatography (LC), it is often very useful to have an accurate model of the retention factor, k, over a wide range of isocratic elution conditions. In principle, the parameters of a retention model can be obtained by fitting either isocratic or gradient retention factor data. However, in spite of many of our own attempts to accurately predict isocratic k values using retention models trained with gradient retention data, this has not worked in our hands. In the present study we have used synthetic isocratic and gradient retention data for small molecules under reversed-phase LC conditions. This allows us to discover challenges associated with predicting isocratic k's without the confounding influences of experimental issues that are difficult to model or eliminate. The results indicate that it is not currently possible to consistently predict isocratic retention factors for small molecules with accuracies better than 10%, even when using synthetic gradient retention data. Two distinct challenges in fitting gradient retention data were identified: 1) a lack of 'uniqueness' in the parameters; and 2) an inability to find the global optimum fit in a complex fitting landscape. Working with experimental data where measurement noise is unavoidable will only make the accuracy worse. This article is protected by copyright. All rights reserved.

Application of retention modeling in chiral method development. I. Selection of isocratic composition for preparative separation with SFC

Preparative chiral separations are carried out using chiral stationary-phases (CSP) employing isocratic composition mode to take advantage of stacking multiple injections within a single continuous operation. Development of the separation method, however, is not conducted directly in the preparative systems. Chromatographic systems at analytical scale are set up to screen multiple CSPs with various mobile-phases (MP) to detect a suitable CSP-MP combination. For faster method screening, solvent-gradients are implemented - operating from low to higher modifier composition, e.g. 5 to 70%. Once the right CSP-MP pair is detected, the isocratic method for preparative separation is developed through further experimental trials in the analytical system. The scope of the trial steps is generally limited to detecting a "good-enough" separation condition through one or two isocratic experiments. Ideally, the analyst should scout all possible isocratic conditions to detect the most suitable method; which, however, is not possible in high-throughput separation laboratories. In this report we demonstrate the utility of a simple set of algebraic equations, supported by an experimental protocol, in generating complete isocratic method options based on minimum number of experimental trials. The approach presented here was developed for chiral separation with supercritical-fluid chromatography. We also suggest an approach to identify an isocratic composition for the purification step. The process proposed in this report should be useful in developing better preparative separation methods in high-throughput laboratories.

Comparison of the Fitting Performance of Retention Models and Elution Strength Behaviour in Hydrophilic-Interaction and Reversed-Phase Liquid Chromatography

Hydrophilic interaction liquid chromatography (HILIC) is able to separate from polar to highly polar solutes, using similar eluents to those in the reversed-phase mode (RPLC) and a polar stationary phase, where water is adsorbed onto its surface. It is widely accepted that multiple modes of interaction take place in the HILIC environment, which can be far more complex than the interactions in an RPLC column. The behaviour in HILIC should be adequately modelled to predict the retention with optimisation purposes and improve the understanding on retention mechanisms, as is the case for RPLC. In this work, the prediction performance of several retention models is studied for seven HILIC columns (underivatised silica, and silica containing diol, amino and sulfobetaine functional groups, together with three columns recently manufactured with neutral, anionic, and cationic character), using uracil and six polar nucleosides (adenosine, cytidine, guanosine, thymidine, uridine, and xanthosine) as probe compounds. The results in HILIC are compared with those that were offered by the elution of several polar sulphonamides and diuretics analysed with two C18 columns (Chromolith Speed ROD and Zorbax Eclipse XDB). It is shown that eight retention models, which only consider partitioning or both partitioning and adsorption, give similar good accuracy in predictions for both HILIC and RPLC columns. However, the study on the elution strength behaviour, at varying mobile phase composition, reveals similarities (or differences) between RPLC and HILIC columns of diverse nature. The particular behaviour for the HILIC and RPLC columns was also revealed when the retention, in both modes, was fitted to a model that describes the change in the elution strength with the modifier concentration.

A review of retention mechanism studies for packed column supercritical fluid chromatography

The packed column supercritical fluid chromatography has risen as a promising alternative separation technique to the conventional liquid chromatography and gas chromatography. Although the packed column supercritical fluid chromatography has many advantages compared to other chromatographic techniques, its separation mechanism is not fully understood due to the complex combination effects of many chromatographic parameters on separation quality and the lacking of global strategies for studying separation mechanisms. This review aims to provide recent information regarding the chromatographic behaviors and the effects of the parameters on the separation, discuss the results, and point out the remaining bottlenecks in the packed column supercritical fluid chromatography retention mechanism studies.

Peak-tracking algorithm for use in comprehensive two-dimensional liquid chromatography - Application to monoclonal-antibody peptides

A peak-tracking algorithm was developed for use in comprehensive two-dimensional liquid chromatography coupled to mass spectrometry. Chromatographic peaks were tracked across two different chromatograms, utilizing the available spectral information, the statistical moments of the peaks and the relative retention times in both dimensions. The algorithm consists of three branches. In the pre-processing branch, system peaks are removed based on mass spectra compared to low intensity regions and search windows are applied, relative to the retention times in each dimension, to reduce the required computational power by elimination unlikely pairs. In the comparison branch, similarity between the spectral information and statistical moments of peaks within the search windows is calculated. Lastly, in the evaluation branch extracted-ion-current chromatograms are utilized to assess the validity of the pairing results. The algorithm was applied to peptide retention data recorded under varying chromatographic conditions for use in retention modelling as part of method optimization tools. Moreover, the algorithm was applied to complex peptide mixtures obtained from enzymatic digestion of monoclonal antibodies. The algorithm yielded no false positives. However, due to limitations in the peak-detection algorithm, cross-pairing within the same peaks occurred and six trace compounds remained falsely unpaired.

Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatography

An important challenge in chromatography is the development of adequate separation methods. Accurate retention models can significantly simplify and expedite the development of adequate separation methods for complex mixtures. The purpose of this study was to introduce reinforcement learning to chromatographic method development, by training a double deep Q-learning algorithm to select optimal isocratic scouting runs to generate accurate retention models. These scouting runs were fit to the Neue-Kuss retention model, which was then used to predict retention factors both under isocratic and gradient conditions. The quality of these predictions was compared to experimental data points, by computing a mean relative percentage error (MRPE) between the predicted and actual retention factors. By providing the reinforcement learning algorithm with a reward whenever the scouting runs led to accurate retention models and a penalty when the analysis time of a selected scouting run was too high (> 1h); it was hypothesized that the reinforcement learning algorithm should by time learn to select good scouting runs for compounds displaying a variety of characteristics. The reinforcement learning algorithm developed in this work was first trained on simulated data, and then evaluated on experimental data for 57 small molecules - each run at 10 different fractions of organic modifier (0.05 to 0.90) and four different linear gradients. The results showed that the MRPE of these retention models (3.77% for isocratic runs and 1.93% for gradient runs), mostly obtained via 3 isocratic scouting runs for each compound, were comparable in performance to retention models obtained by fitting the Neue-Kuss model to all (10) available isocratic datapoints (3.26% for isocratic runs and 4.97% for gradient runs) and retention models obtained via a "chromatographer's selection" of three scouting runs (3.86% for isocratic runs and 6.66% for gradient runs). It was therefore concluded that the reinforcement learning algorithm learned to select optimal scouting runs for retention modeling, by selecting 3 (out of 10) isocratic scouting runs per compound, that were informative enough to successfully capture the retention behavior of each compound.

Global retention models and their application to the prediction of chromatographic fingerprints

The resolution of samples containing unknown compounds of different nature, or without standards available, as is the case of chromatographic fingerprints, is still a challenge. Possibly, the most problematic aspect that prevents systematic method development is finding models that describe without bias the retention behaviour of the compounds in the samples. In this work, the use of global models (able to describe the whole sample) is proposed as an alternative to the use of individual models for each solute. Global models contain parameters that are specific for each solute, while other parameters ‒related to the column and solvent‒ are common for all solutes. A special regression procedure is presented for the construction of global models, which are applied to predict highly complex chromatograms, such as chromatographic fingerprints, for diverse experimental conditions in isocratic and gradient elution. Another interesting application is the prediction of molecular properties, such as log P_o/w, from the specific solute parameters of the global models. The examined adapted models are based on the equations proposed by Snyder, Schoenmakers, Neue and Kuss, Jandera, and Bosch Rosés to describe the retention. In all cases, the predictive capability was very satisfactory. Two cases of study were considered: chromatograms of camomile extracts analysed using acetonitrile gradients, and a set of 145 known compounds in a wide range of structures and functionalities, eluted isocratically with acetonitrile/water mobile phases.

Measuring and using scanning-gradient data for use in method optimization for liquid chromatography

The use of scanning gradients can significantly reduce method-development time in reversed-phase liquid chromatography. However, there is no consensus on how they can best be used. In the present work we set out to systematically investigate various factors and to formulate guidelines. Scanning gradients are used to establish retention models for individual analytes. Different retention models were compared by computing the Akaike information criterion and the prediction accuracy. The measurement uncertainty was found to influence the optimum choice of model. The use of a third parameter to account for non-linear relationships was consistently found not to be statistically significant. The duration (slope) of the scanning gradients was not found to influence the accuracy of prediction. The prediction error may be reduced by repeating scanning experiments or - preferably - by reducing the measurement uncertainty. It is commonly assumed that the gradient-slope factor, i.e. the ratio between slopes of the fastest and the slowest scanning gradients, should be at least three. However, in the present work we found this factor less important than the proximity of the slope of the predicted gradient to that of the scanning gradients. Also, interpolation to a slope between that of the fastest and the slowest scanning gradient is preferable to extrapolation. For comprehensive two-dimensional liquid chromatography (LC × LC) our results suggest that data obtained from fast second-dimension gradients cannot be used to predict retention in much slower first-dimension gradients.

Reducing the influence of geometry-induced gradient deformation in liquid chromatographic retention modelling

Rapid optimization of gradient liquid chromatographic (LC) separations often utilizes analyte retention modelling to predict retention times as function of eluent composition. However, due to the dwell volume and technical imperfections, the actual gradient may deviate from the set gradient in a fashion unique to the employed instrument. This makes accurate retention modelling for gradient LC challenging, in particular when very fast separations are pursued. Although gradient deformation has been addressed in method-transfer situations, it is rarely taken into account when reporting analyte retention parameters obtained from gradient LC data, hampering the comparison of data from various sources. In this study, a response-function-based algorithm was developed to determine analyte retention parameters corrected for geometry-induced deformations by specific LC instruments. Out of a number of mathematical distributions investigated as response-functions, the so-called "stable function" was found to describe the formed gradient most accurately. The four parameters describing the model resemble the statistical moments of the distribution and are related to chromatographic parameters, such as dwell volume and flow rate. The instrument-specific response function can then be used to predict the actual shape of any other gradient programmed on that instrument. To incorporate the predicted gradient in the retention modelling of the analytes, the model was extended to facilitate an unlimited number of linear gradient steps to solve the equations numerically. The significance and impact of distinct gradient deformation for fast gradients was demonstrated using three different LC instruments. As a proof of principle, the algorithm and retention parameters obtained on a specific instrument were used to predict the retention times on different instruments. The relative error in the predicted retention times went down from an average of 9.8% and 12.2% on the two other instruments when using only a dwell-volume correction to 2.1% and 6.5%, respectively, when using the proposed algorithm. The corrected retention parameters are less dependent on geometry-induced instrument effects.

Recent applications of retention modelling in liquid chromatography

Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention‐mechanism studies, for determining physical parameters, such as lipophilicity, and for various more‐practical purposes, including method development and optimization, method transfer, and stationary‐phase characterization and comparison. The review focusses on the effects of mobile‐phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most‐common models are addressed in detail, i.e. the log‐linear (linear‐solvent‐strength) model, the quadratic model, the log–log (adsorption) model, the mixed‐mode model, and the Neue–Kuss model. Isocratic and gradient‐elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one‐ and two‐dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.

Recent applications of chemometrics in one- and two-dimensional chromatography

The proliferation of increasingly more sophisticated analytical separation systems, often incorporating increasingly more powerful detection techniques, such as high-resolution mass spectrometry, causes an urgent need for highly efficient data-analysis and optimization strategies. This is especially true for comprehensive two-dimensional chromatography applied to the separation of very complex samples. In this contribution, the requirement for chemometric tools is explained and the latest developments in approaches for (pre-)processing and analyzing data arising from one- and two-dimensional chromatography systems are reviewed. The final part of this review focuses on the application of chemometrics for method development and optimization.

Dual-retention mechanism of dopamine-related compounds on monolithic stationary phase with zwitterion functionality

Seven retention models have been selected to describe a dual-retention behavior of ten dopamine-related compounds on polymer-based monolithic stationary phase with zwitterion sulfobetaine functionality. Regression quality, as well as a statistical significance of individual regression parameters, have been evaluated. Better regression performance showed two four-parameter models when compared to three-parameter models. On the other hand, limited number of experimental points disqualified statistical robustness of four-parameter models. Among three-parameter models, retention description introduced by Horváth and Liang provided comparable quality of regression at significantly improved robustness. Multivariate analysis of the best three-parameter models provided the description of physicochemical properties of dopamine precursors and metabolites. Principal component analysis and logistic regression allowed structural characterization of dopamine-related compounds based solely on regression parameters extracted from an isocratic elution data. Both polarity and type of functional groups has been correctly assigned for 3-methoxytyramine that has not been part of an evaluation study. Among applied dual-retention models, Horváth´s model, initially developed to describe a retention of ionic compounds on nonpolar stationary phases, provided robust regression of experimental data and allowed an extraction of structural characteristics of dopamine-related compounds.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial

Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.

Detailed efficiency analysis of columns with a different packing quality and confirmation via total pore blocking

We report on a systematic study involving columns with a clearly different efficiency (4 distinct quality groups) obtained by packing the columns that were C₁₈ bonded and endcapped with a different carbon loading. Using B-term analysis (via peak parking) and theoretical models to estimate the magnitude of the C_m- and C_s-term contributions, it could be concluded that the difference in efficiency among the groups was entirely due to a difference in eddy dispersion. As such, the columns provided an ideal testing ground to verify how well the total pore blocking (TPB)-method can be used to probe differences in packing heterogeneity. In agreement with earlier literature observations, it turns out the TPB-method is much more sensitive to packing heterogeneities than the eddy dispersion (H_eddy)-contribution measured under open-pore conditions via B- and C- term subtraction. Typically, differences in H_eddy on the order of 0.1-0.5μm translate into a difference on the order of 0.5-2μm in the TPB mode. This confirms the TPB as a powerful technique to make very sensitive measurements of the homogeneity of packed beds.

Peak-Tracking Algorithm for Use in Automated Interpretive Method-Development Tools in Liquid Chromatography

A peak-tracking algorithm for chromatograms recorded using liquid chromatography and mass spectrometry was developed. Peaks are tracked across chromatograms using the spectrometric information, the statistical moments of the chromatographic peaks, and the relative retention. The algorithm can be applied to pair chromatographic peaks in two very different chromatograms, obtained for different samples using different methods. A fast version of the algorithm was specifically tailored to process chromatograms obtained during method development or optimization, where a few similar mobile-phase-composition gradients (same eluent components, but different ranges and programming rates) are applied to the same sample for the purpose of obtaining model parameters to describe the retention of sample components. Due to the relative similarity between chromatograms, time-saving preselection protocols can be used to locate a candidate peak in another chromatogram. The algorithm was applied to two different samples featuring isomers. The automatically tracked peaks and the resulting retention parameters generally yielded prediction errors of less than 1%.

Simultaneous determination of twelve polar pteridines including dihydro- and tetrahydropteridine in human urine by hydrophilic interaction liquid chromatography with tandem mass spectrometry

Pteridines and their derivatives are important cofactors in the process of cell metabolism, and the level of urinary excretion of these compounds is considered as an important clinical criterion. In this work, a new separation method involving hydrophilic interaction chromatography (HILIC) with tandem mass spectrometric detection has been developed for the simultaneous analysis of 12 pteridines including oxidized, di- and tetrahydroforms, namely neopterin, 7,8-dihydroneopterin, biopterin, 7,8-dihydrobiopterin, 5,6,7,8-tetrahydrobiopterin, dimethylpterin, dimethyltetrahydropterin, pterin, isoxanthopterin, xanthopterin, sepiapterin and pterin-6-carboxylic acid, in human urine without oxidative pretreatments. The stabilizing agent (dithiothreitol) at various concentrations and the stability of oxidized, di- and tetrahydroforms during the sample's short-term storage and processing and of the extracts were tested. In the developed method, 12 pteridines were chromatographically separated on an ZIC-HILIC column by gradient elution, and the run time was 20 min. Matrix effect was evaluated and several dilutions of urine were tested in order to study the evolution of signal suppression. Spiked recovery studies demonstrated that the technique was both accurate (83.1-116.7%) and precise (RSD 1.4-15.6%). Finally, several clinical urine specimens without oxidative pretreatments were examined with the new technique and compared with previous reports.

Mobile phase effects in reversed-phase and hydrophilic interaction liquid chromatography revisited

Correct adjustment of the mobile phase is equally important as the selection of the appropriate column for the separation of polar compounds in LC. Both solvophobic and selective polar interactions control the retention in the Reversed Phase and Hydrophilic Interaction modes. The retention models describing the effects of the volume fraction of the strong eluent component in binary mobile phases on the sample retention factors apply in a limited mobile phase composition range. We introduced a three-parameter retention model, which provides improved prediction of retention over a broad mobile phase range, under isocratic and gradient elution conditions. The model does not imply any assumptions concerning either adsorption or partition distribution mechanism, but allows estimating retention in pure strong and in pure weak mobile phase components. The experimental retention data for phenolic acids and flavones on several core-shell columns with different types of stationary phases agree with the theory. Many polar columns with important structural hydrophobic moieties show dual retention mechanism, (Reversed Phase in water rich mobile phases and Hydrophilic Interaction at high acetonitrile concentrations). It is possible to select the mobile phase compositions in each of the two modes for separations of samples containing compounds largely differing in polarity. The three-parameter model describes the retention in each mode, with separately determined best-fit parameters. We applied the two-mode model to the retention data of sulfonamides and benzoic acid related compounds on a new polymethacrylate zwitterionic monolithic micro-column.

Peptide retention prediction using hydrophilic interaction liquid chromatography coupled to mass spectrometry

A model that predicts retention for peptides using a HALO® penta-HILIC column and gradient elution was created. Coefficients for each amino acid were derived using linear regression analysis and these coefficients can be summed to predict the retention of peptides. This model has a high correlation between experimental and predicted retention times (0.946), which is on par with previous RP and HILIC models. External validation of the model was performed using a set of H. pylori samples on the same LC-MS system used to create the model, and the deviation from actual to predicted times was low. Apart from amino acid composition, length and location of amino acid residues on a peptide were examined and two site-specific corrections for hydrophobic residues at the N-terminus as well as hydrophobic residues one spot over from the N-terminus were created.

Optimizing separations in online comprehensive two-dimensional liquid chromatography

Online comprehensive two-dimensional liquid chromatography has become an attractive option for the analysis of complex nonvolatile samples found in various fields (e.g. environmental studies, food, life, and polymer sciences). Two-dimensional liquid chromatography complements the highly popular hyphenated systems that combine liquid chromatography with mass spectrometry. Two-dimensional liquid chromatography is also applied to the analysis of samples that are not compatible with mass spectrometry (e.g. high-molecular-weight polymers), providing important information on the distribution of the sample components along chemical dimensions (molecular weight, charge, lipophilicity, stereochemistry, etc.). Also, in comparison with conventional one-dimensional liquid chromatography, two-dimensional liquid chromatography provides a greater separation power (peak capacity). Because of the additional selectivity and higher peak capacity, the combination of two-dimensional liquid chromatography with mass spectrometry allows for simpler mixtures of compounds to be introduced in the ion source at any given time, improving quantitative analysis by reducing matrix effects. In this review, we summarize the rationale and principles of two-dimensional liquid chromatography experiments, describe advantages and disadvantages of combining different selectivities and discuss strategies to improve the quality of two-dimensional liquid chromatography separations.

Chemometric-assisted method development in hydrophilic interaction liquid chromatography: A review

With an enormous growth in the application of hydrophilic interaction liquid chromatography (HILIC), there has also been significant progress in HILIC method development. HILIC is a chromatographic method that utilises hydro-organic mobile phases with a high organic content, and a hydrophilic stationary phase. It has been applied predominantly in the determination of small polar compounds. Theoretical studies in computer-aided modelling tools, most importantly the predictive, quantitative structure retention relationship (QSRR) modelling methods, have attracted the attention of researchers and these approaches greatly assist the method development process. This review focuses on the application of computer-aided modelling tools in understanding the retention mechanism, the classification of HILIC stationary phases, prediction of retention times in HILIC systems, optimisation of chromatographic conditions, and description of the interaction effects of the chromatographic factors in HILIC separations. Additionally, what has been achieved in the potential application of QSRR methodology in combination with experimental design philosophy in the optimisation of chromatographic separation conditions in the HILIC method development process is communicated. Developing robust predictive QSRR models will undoubtedly facilitate more application of this chromatographic mode in a broader variety of research areas, significantly minimising cost and time of the experimental work.

Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles

Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase we used, column distortion is an important factor to take into account in retention projection in HILIC that is not usually important in RPLC.

Effect of reference conditions on flow rate, modifier fraction and retention in supercritical fluid chromatography

When using compressible mobile phases such as fluidic CO2, the density, the volumetric flow rates and volumetric fractions are pressure dependent. The pressure and temperature definition of these volumetric parameters (referred to as the reference conditions) may alter between systems, manufacturers and operating conditions. A supercritical fluid chromatography system was modified to operate in two modes with different definition of the eluent delivery parameters, referred to as fixed and variable mode. For the variable mode, the volumetric parameters are defined with reference to the pump operating pressure and actual pump head temperature. These conditions may vary when, e.g. changing the column length, permeability, flow rate, etc. and are thus variable reference conditions. For the fixed mode, the reference conditions were set at 150bar and 30°C, resulting in a mass flow rate and mass fraction of modifier definition which is independent of the operation conditions. For the variable mode, the mass flow rate of carbon dioxide increases with system pump operating pressure, decreasing the fraction of modifier. Comparing the void times and retention factor shows that the deviation between the two modes is almost independent of modifier percentage, but depends on the operating pressure. Recalculating the set volumetric fraction of modifier to the mass fraction results in the same retention behaviour for both modes. This shows that retention in SFC can be best modelled using the mass fraction of modifier. The fixed mode also simplifies method scaling as it only requires matching average column pressure.

Computer assisted liquid chromatographic method development for the separation of therapeutic proteins

This review summarizes the use of computer assisted liquid chromatographic method development for the analytical characterization of protein biopharmaceuticals.