The analytical toolbox used to characterize surfactant mixtures in support of research, development, and manufacturing includes liquid and gas chromatography, spectroscopic techniques, and mass spectrometry. Two-dimensional liquid chromatography (2D-LC) is particularly well suited to the challenge of characterizing these mixtures because separations with complementary selectivities can be coupled to resolve molecules according to distributions of two or more functional groups. In this work we have discovered mobile phase conditions that can be used to resolve isomeric species present in mixtures of ethylene oxide (EO) - propylene oxide (PO) diblock copolymers. Specifically, we find that use of non-aqueous hydrophilic interaction (NA-HILIC) conditions, where the water typically used as the strong solvent is replaced by an alcohol, provide the selectivity needed to resolve copolymer isomers that only differ in the orientation of PO groups within the copolymer chain. When used in a 2D-LC method, these conditions enable highly selective separation of hundreds of peaks, both by the number of EO (first dimension) and PO (second dimension) groups, and according to PO isomer structure. Within analysis times of about four hours, we achieved peak capacities on the order of 1000, which we believe is a significant step forward in the characterization of EO-PO copolymers relative to prior published work and will be very useful for understanding the composition and behavior of these mixtures going forward.

Lipidomics is a powerful approach for investigating lipid alterations in complex biological systems. However, conventional liquid chromatography coupled to mass spectrometry (LC-MS) may be limited in non-targeted studies due to the high structural diversity and wide concentration range of lipid species.In this work, an optimized comprehensive two-dimensional liquid chromatography coupled to high-resolution mass spectrometry (LC×LC-HRMS) workflow was developed for non-targeted lipidomics. The method combines reversed-phase (RP) separation in the first chromatographic dimension with hydrophilic interaction liquid chromatography (HILIC) separation in the second dimension (RP×HILIC) and incorporates active solvent modulation (ASM) as an interface between the two chromatographic dimensions to improve analytical sensitivity and solvent compatibility across both dimensions. This approach improves sensitivity, solvent compatibility and lipidome coverage compared to conventional LC-MS workflows.The proposed workflow was applied to investigate lipidomic alterations in zebrafish (Danio rerio) eleutheroembryos exposed to the endocrine-disrupting chemical bisphenol A (BPA), using 17β-estradiol (E2) as an estrogenic control. The LC×LC-HRMS approach enabled enhanced lipidome coverage, resulting in the detection of 567 lipid features, of which 134 showed significant alterations associated with endocrine-disruptor exposure. Comparative analysis revealed lipidomic changes consistent with estrogenic responses for both BPA and E2 treatments, while additional lipid alterations suggested potential obesogenic effects under E2 exposure.In summary, the proposed LC×LC-HRMS workflow with ASM provides enhanced separation performance. The obtained results demonstrate the potential of comprehensive multidimensional chromatography combined with multivariate analysis tools for in-depth lipidomics studies in complex biological samples.

As the clinical applications of RNA-based medicines continue to grow, innovative analytical approaches are essential to assess quality attributes of these complex therapeutic molecules. Synthetic oligonucleotides (ONs) such as small interfering RNA and antisense oligonucleotides are an expanding sub-class of genetic medicines that typically consist of single- or double-stranded RNA or DNA molecules ranging from 20 to 30 nucleotides in length. Characterization of synthetic ONs presents considerable analytical challenges due to their relatively large molecular size, polyanionic nature, and the potential for numerous synthetic modifications and impurities. It is becoming increasingly clear that conventional chromatographic methodologies are not always sufficient to fully resolve the full impurity profile present in these samples. 2D-LC is a potentially effective solution, enabling rapid resolution of species that co-elute from the first dimension using a complementary second dimension separation. In this work we explore the potential utility of pairing HILIC separation in the second dimension as a complement to a first dimension ion-pairing reversed-phase separation. Using a 23-mer surrogate ON and several closely related structures representing potential impurities, we find that the selectivities of the IPRP and HILIC separations are highly complementary, and thus suitable for pairing in a 2D separation format. Moreover, the mass loadability of the two separations are similar under the conditions studied, which gives the user flexibility when choosing which separation to use in the first dimension. We then demonstrate that an iterative retention modeling approach can be used to systematically discover shallow second dimension gradients needed to resolve species that co-elute from the first dimension column. In an unexpected twist, we found that the interface conditions must be optimized when using Active Solvent Modulation, because the weakest diluent (i.e., high ACN for a HILIC separation) does not always yield the best second dimension separation. Finally, we developed IPRP-HILIC methods for two different ON sequences that demonstrate improved resolution of previously co-eluting impurities and sufficient sensitivity for detection at 0.1% relative to the full length product.

Dwight Stoll and Martin Gilar describe the utility of liquid chromatography coupled with mass spectrometric detection (LC–MS) for analysis of oligonucleotides (ONs), discuss recommended LC modes and mobile phases, and highlight challenges encountered in these applications, along with potential solutions.

The “autosampler” is an indispensable component of modern high-performance liquid chromatography (HPLC) systems. Contemporary technology enables automated, rapid, and precise injections of samples with very little carryover. However, the rotor/stator assembly at the heart of injection valves used in these samplers is also a weak point. Routine wear of the rotor can lead to leaks and release debris into the mobile phase, leading to obstructions downstream from the injection valve. In this installment of “LC Troubleshooting,” we take a close look at how the commonly used “flow-through needle” sampler works, discuss how and where leaks can develop, and solutions to the problems when they do occur.

Reversed-phase liquid chromatography (RPLC) method development remains resource-intensive due to the iterative optimization required to achieve fit-for-purpose separations. While machine learning-enabled quantitative structure-retention relationships (QSRRs) offer predictive capabilities, current models suffer from poor stereoisomer discrimination, uncertain applicability domains, and limited practical integration. This work develops an XGBoost-based QSRR model using 43,329 retention measurements from 86 solutes on 13 stationary phases measured with isocratic mobile phases in the range of 2-90% organic content. The model combines standard 2D Mordred molecular descriptors with 37 custom stereochemical and geometric descriptors that distinguish R/S and E/Z configurations from SMILES strings. Feature selection reduced the descriptor set to 29, achieving a test-set root mean square error (RMSE) of 0.12 (ln selectivity scale), with the addition of custom isomer descriptors providing 2.5-fold improvement in stereoisomer prediction accuracy. The model demonstrated reliable interpolation (RMSE ≤ 0.05, selectivity scale) when molecular descriptor values are within the training-set bounds but showed degraded performance during extrapolation (RMSE 0.11-0.20, selectivity scale). Paired-solute analysis across the 13 stationary phases linked column-dependent prediction failures to descriptors omitted or pruned from the model, (e.g., acid-base character, halogen content, H-bond capacity). This computationally accessible framework provides systematic approaches for assessing prediction reliability across mobile phase compositions and stationary phase chemistries, establishing clear boundaries for trustworthy model application.

Two-dimensional liquid chromatography (2D-LC) is one of the highest-resolution techniques available to chromatographers for the separation of analytes in complex mixtures. However, data analysis and data visualization remain challenging, especially for home-built systems that do not utilize commercial software packages. Even these packages are not capable of effectively displaying data generated from systems where multiple columns are used for the second-dimension separation. Here, an open-source software package with a graphical user interface used to plot and characterize 2D-LC data is described. In addition to plotting imported data, a 2D-LC simulator is included to generate both 1D and 2D chromatograms. The HSV (hue, saturation, value) color wheel is used to combine multiple 2D-LC contour plots into a single graphic, creating a new visualization strategy for 2D-LC systems in which multiple columns are used sequentially or in parallel column arrays in the second dimension. Use of the package for both experimental and random simulated data is presented as a demonstration of its capabilities.

As conventional liquid chromatography (LC) increasingly proves insufficient for addressing complex analytical challenges, two-dimensional LC is gaining growing interest from industrial laboratories. When coupling complementary separation mechanisms, one major challenge that continues to receive attention is mobile phase mismatch. To address this challenge, several strategies have been described in the literature for combining solvent streams to achieve dilution, they commonly involve a T-type geometry. After the convergence of two solvent streams, under laminar flow conditions, segregated flow streams may persist and reach the column inlet without significant mixing. This study explores this phenomenon and its impact on chromatography in detail, specifically in the context of modulation for two-dimensional liquid chromatography. The presence of insufficiently mixed solvents can have serious implications for analyte retention and peak shape. To address this issue, mixing can be achieved through radial dispersion by utilizing coiled tubing, which helps maintain analyte retention along with narrow and symmetrical peak shapes. In addition to modulation in 2D-LC, feed injection has also been investigated and benefits from increased radial mixing.

Determination of quality attributes of antisense oligonucleotides (ASOs) such as purity, potency, and sequence is challenging due to their relatively large size, polyanionic nature, and large number of synthetic modifications. Chromatography technologies are evolving rapidly to meet these challenges, and one area of particularly rapid change at this time is the use of hydrophilic interaction liquid chromatography (HILIC) for oligonucleotide (ON) separations. Relatively little has been published on the factors that dictate the kinetics of these separations. This knowledge gap consequently makes it difficult to know what gains might be made during method development by changing flow rate or particle size, for example. In this work we have taken initial steps to address this gap by examining the dependence of plate height and resolution on flow rate for separations of 23-mer ASOs under HILIC conditions. Such work is complicated by the fact that the retention of these molecules decreases dramatically with increasing pressure. After adjusting mobile phase composition to hold retention factor nominally constant for each flow rate used, we find that plate height increases strongly with increasing flow rate such that the plate height increases about ten-fold over the range of flow rate of 0.1 to 4.0 mL/min. when using a 4.6 mm i.d. column. However, the minimum reduced plate height observed at the lowest flow rate is quite impressive at around 2. Finally, we find that this dependence of plate height on flow rate translates, as expected, to an improvement in resolution as flow rate is decreased, both in conventional one-dimensional separations, and in the second dimension of a two-dimensional separation. We expect to use this work as a foundation to build on as we deepen our understanding of the kinetics of ON separations.

As the importance of therapeutic oligonucleotides (ONs) continues to grow in the pharmaceutical industry, the importance of high performing analytical methods needed to characterize them also grows. The characteristics of these molecules (e.g., highly charged phosphate backbone, and small but important modifications such as methylation and fluorination) make them difficult to analyze thoroughly using conventional liquid chromatography (LC) conditions. Recently, other research groups have been emphasizing the utility of ultra-short (<< 50 mm) columns for proteins and other large biomolecules, and have remarked that long columns only add unnecessary peak dispersion without providing additional resolution over short columns. These statements naturally call into question the long-established theory for small molecule LC separations that asserts that separation performance is maximized by working at the highest available operating pressure, and then choosing the longest column possible while working at the van Deemter optimum flow rate. This apparent contradiction in turn raises the question - for which types of large biomolecule does the established chromatographic theory no longer apply? In this study we have carried out experiments and calculations aimed at answering this question for ion-pairing reversed-phase separations of therapeutic ONs with masses on the order of 6 kDa. This included measuring isocratic plate heights for these molecules after establishing an empirical relationship between retention, mobile phase composition, and flow rate, because retention of the ONs is extremely sensitive to pressure (20 % increase in k per bar pressure drop), and thus retention varies with flow rate at a constant mobile phase composition. After taking these factors into account, we find that resolution of the oligonucleotides does increase with the square root of column length, as predicted by the well-established theory for small molecules. However, we also find that this relationship is only found when the gradient slope is held constant while varying the column length, and that if this is not done it is actually possible to observe that resolution decreases with increasing column length. Thus, the design of experiments used to evaluate the role of column length in separation performance is critical. In addition to the importance of these findings to development of LC methods for ON separations in general, they will be especially impactful in two-dimensional (2D) separations of ONs where there is more or less freedom to choose parameters from a wide range of possibilities depending on the mode of 2D separation that is used.

Molecules encountered in the early-phase of drug development present a diverse set of challenges to HPLC analysis, as well as purification workflows. Finding conditions that yield adequate resolution of a target product peak can be difficult when limited to the conventional C18 stationary phases. Successful preparative chromatography relies on adequate peak capacity, resolution in the vicinity of the target peak, and increased loading capacity to achieve high chromatographic method productivity. In this article, we discuss both the benefits (improved peak shape/loading) and challenges (excessive interaction) associated with charge-doped reversed-phase (RP) columns for both analytical and preparative separations.

The Pittsburgh Conference, more commonly known as Pittcon, is the largest conference focused on analytical chemistry in the United States. It was held in Boston during the first week of March. With multiple technical oral presentation sessions held in parallel, it can be difficult to decide exactly which talks to attend. This year was no exception, but my choices did not disappoint; I walked away from the conference with new troubleshooting knowledge related to multiple topics including oligonucleotide analysis by mass spectrometry, and analysis of anthropogenic compounds in the environment. In this installment of “LC Troubleshooting,” I touch on highlights from these talks, as well as troubleshooting advice distilled from a lifetime of work in separation science by LCGC Award winner Christopher Pohl.

Buffered solutions that resist changes in pH are very important to various aspects of the practice of liquid chromatography. Unfortunately, the buffering additives that are best for chromatographic performance sometimes cause problems with detection, such as baseline drift and noise, or decreases in sensitivity. In this installment, I primarily discuss considerations to keep in mind when choosing buffering additives that will be used for LC methods involving UV absorbance detection. Keeping these ideas in mind at the start of the method development process can help prevent problems from developing during the lifetime of a new method, as well as help troubleshoot problems with existing methods that are buffer-related.

Hydroxypropyl methyl cellulose (HPMC) is a type of cellulose derivative with properties that render it useful in e.g. food, cosmetics, and pharmaceutical industry. The substitution degree and composition of the β-glucose subunits of HPMC affect its physical and functional properties, but HPMC characterization is challenging due to its high structural heterogeneity, including many isomers. In this study, comprehensive two-dimensional liquid chromatography-mass spectrometry was used to examine substituted glucose monomers originating from complete acid hydrolysis of HPMC. Resolution between the different monomers was achieved using a C18 and cyano column in the first and second LC dimension, respectively. The data analysis process was structured to obtain fingerprints of the monomers of interest. The results revealed that isomers of the respective monomers could be selectively separated based on the position of substituents. The examination of two industrial HPMC products revealed differences in overall monomer composition. While both products contained monomers with a similar degree of substitution, they exhibited distinct regioselectivity.

Buffered solutions that resist changes in pH are very important to various aspects of the practice of liquid chromatography (LC). In this installment, I discuss several essential principles related to when and why buffers are important, as well as practical factors such as commonly used buffering agents that are recommended for use with different types of detectors. This installment is intended as a prelude to subsequent installments that will explore specific troubleshooting scenarios that are impacted by effective use of buffered solutions.

Two-dimensional liquid chromatography (2D-LC) is a technique that extends the separation capabilities of conventional liquid chromatography by adding a second separation step to resolve compounds that are coeluted from a first column. This approach holds tremendous potential to solve difficult separation challenges in fields ranging from pharmaceutical analysis to biofuel characterization. Currently, method development is a significant bottleneck impeding more widespread implementation of 2D-LC methods, particularly for new users who are uncertain about how to proceed. In this month’s column, I highlight some of the primary considerations we face in method development and point to resources that can help users overcome uncertainty and develop highly effective 2D-LC methods.

The analogy that electrons flowing in wires is like water flowing through a tube can be remarkably effective for teaching and learning about fluid flow in LC systems. In this installment, we apply the concepts developed in last month’s installment by demonstrating how they can be used to help troubleshoot problems in LC involving pressure and flow. We also introduce several free tools that can be used to calculate pressure drops in different elements of LC systems, including connecting capillaries and packed columns. Knowing what pressure drops to expect for system components under different chromatographic conditions is very valuable in many troubleshooting situations.

The gradient delay volume is arguably one of the most important, yet least appreciated, parameters that affect how gradient elution separations in LC work. This has implications both for method development and for method transfer during the lifecycle of a LC method. In this installment, I will review the concept of gradient delay volume, its physical connection to the LC instrument, and how it can impact method development and separation quality.

Reversed-phase (RP) liquid chromatography is an important tool for the characterization of materials and products in the pharmaceutical industry. Method development is still challenging in this application space, particularly when dealing with closely-related compounds. Models of chromatographic selectivity are useful for predicting which columns out of the hundreds that are available are likely to have very similar, or different, selectivity for the application at hand. The hydrophobic subtraction model (HSM1) has been widely employed for this purpose; the column database for this model currently stands at 750 columns. In previous work we explored a refinement of the original HSM1 (HSM2) and found that increasing the size of the dataset used to train the model dramatically reduced the number of gross errors in predictions of selectivity made using the model. In this paper we describe further work in this direction (HSM3), this time based on a much larger solute set (1014 solute/stationary phase combinations) containing selectivities for compounds covering a broader range of physicochemical properties compared to HSM1. The molecular weight range was doubled, and the range of the logarithm of the octanol/water partition coefficients was increased slightly. The number of active pharmaceutical ingredients and related synthetic intermediates and impurities was increased from four to 28, and ten pairs of closely related structures (e.g., geometric and cis-/trans- isomers) were included. The HSM3 model is based on retention measurements for 75 compounds using 13 RP stationary phases and a mobile phase of 40/60 acetonitrile/25 mM ammonium formate buffer at pH 3.2. This data-driven model produced predictions of ln α (chromatographic selectivity using ethylbenzene as the reference compound) with average absolute errors of approximately 0.033, which corresponds to errors in α of about 3%. In some cases, the prediction of the trans-/cis- selectivities for positional and geometric isomers was relatively accurate, and the driving forces for the observed selectivity could be inferred by examination of the relative magnitudes of the terms in the HSM3 model. For some geometric isomer pairs the interactions mainly responsible for the observed selectivities could not be rationalized due to large uncertainties for particular terms in the model. This suggests that more work is needed in the future to explore other HSM-type models and continue expanding the training dataset in order to continue improving the predictive accuracy of these models. Additionally, we release with this paper a much larger data set (43,329 total retention measurements) at multiple mobile phase compositions, to enable other researchers to pursue their own lines of inquiry related to RP selectivity.

Method development in online comprehensive two-dimensional liquid chromatography (LC × LC) requires the selection of a large number of experimental parameters. The complexity of this process has led to several computer-based LC × LC optimization algorithms being developed to facilitate LC × LC method development. One particularly relevant challenge for predictive optimization software is to accurately model the effect of second dimension (2D) injection band broadening under sample solvent mismatch and/or sample volume overload conditions. We report a novel methodology that combines a chromatographic numerical simulation model capable of predicting elution profiles of analytes under conditions where peak distortion occurs with a predictive multiparameter Pareto optimization approach for online LC × LC. Preliminary method optimization is performed using a theoretical model to predict 2D injection profiles, and optimal experimental configurations obtained from the Pareto fronts are then subjected to further optimization using the simulation model. This approach drastically reduces the number of simulations and therefore the computational demand. We show that the optimal experimental conditions obtained in this manner are similar to those obtained using a complete optimization using only the simulation model. Online HILIC × RP-LC separation of phenolic compounds was used to compare experimental data to simulated two- and three-dimensional contour plots. The main advantage of the proposed approach is the ability to predict the formation of split or deformed peaks in the 2D, a significant benefit in online LC × LC method optimization, especially for separation combinations with mismatched mobile phases. A further benefit is that simulated elution profiles can be used for the visualization of predicted two-dimensional chromatograms for method selection.