Real-time in situ monitoring of CRM-197 and polysaccharide conjugation reaction by fluorescence spectroscopy.

Aims: Process analytical technology (PAT) is increasingly being adopted within the pharmaceutical industry to build quality into a process. Development of PAT that provides real-time in situ analysis of critical quality attributes are highly desirable for rapid, improved process development. Conjugation of CRM-197 with pneumococcal polysaccharides to produce a desired pneumococcal conjugate vaccine is a significantly intricate process that can tremendously benefit from real-time process monitoring. Methods: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time. Results & conclusion: In this work, a fluorescence-based PAT methodology is described to elucidate CRM-197-polysacharide conjugation kinetics in real time.

Automated Hydrophobic Interaction Chromatography Screening Combined with In Silico Optimization as a Framework for Nondenaturing Analysis and Purification of Biopharmaceuticals.

The mounting complexity of new modalities in the biopharmaceutical industry entails a commensurate level of analytical innovations to enable the rapid discovery and development of novel therapeutics and vaccines. Hydrophobic interaction chromatography (HIC) has become one of the widely preferred separation techniques for the analysis and purification of biopharmaceuticals under nondenaturing conditions. Inarguably, HIC method development remains very challenging and labor-intensive owing to the numerous factors that are typically optimized by a "hit-or-miss" strategy (e.g., the nature of the salt, stationary phase chemistry, temperature, mobile phase additive, and ionic strength). Herein, we introduce a new HIC method development framework composed of a fully automated multicolumn and multieluent platform coupled with in silico multifactorial simulation and integrated fraction collection for streamlined method screening, optimization, and analytical-scale purification of biopharmaceutical targets. The power and versatility of this workflow are showcased by a wide range of applications including trivial proteins, monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), oxidation variants, and denatured proteins. We also illustrate convenient and rapid HIC method development outcomes from the effective combination of this screening setup with computer-assisted simulations. HIC retention models were built using readily available LC simulator software outlining less than a 5% difference between experimental and simulated retention times with a correlation coefficient of >0.99 for pharmaceutically relevant multicomponent mixtures. In addition, we demonstrate how this approach paves the path for a straightforward identification of first-dimension HIC conditions that are combined with mass spectrometry (MS)-friendly reversed-phase liquid chromatography (RPLC) detection in the second dimension (heart-cutting two-dimensional (2D)-HIC-RPLC-diode array detector (DAD)-MS), enabling the analysis and purification of biopharmaceutical targets.

Dual-Gradient Unified Chromatography: A New Paradigm for Versatility in Simultaneous Multicomponent Analysis.

Generality in analytical chemistry can be manifested in impactful platforms that can streamline modern organic synthesis and biopharmaceutical processes. We herein introduce a hybrid separation technique named Dual-Gradient Unified Chromatography (DGUC), which is built upon an automated dynamic modulation of CO2 , organic modifier, and water blends with various buffers. This concept enables simultaneous multicomponent analysis of both small and large molecules across a wide polarity range in single experimental runs. After a careful investigation of its fundamental aspects, a DGUC-DAD-MS screening workflow that combines multiple orthogonal column and mobile phase choices across a far-reaching universal elution profile is also reported. The power of this framework is demonstrated with new analytical applications guiding academic and industrial laboratories in the development of new (bio)pharmaceutical targets (e.g. synthetic intermediates, nucleosides, cyclic and linear peptides, proteins, antibody drug conjugates).

Deuterated Modifiers in Sub/Supercritical Fluid Chromatography for Streamlined NMR Structure Elucidation.

Isolation and chemical characterization of target components in fast-paced pharmaceutical laboratories can often be challenging, especially when dealing with mixtures of closely related, possibly unstable species. Traditionally, this process involves intense labor and manual intervention including chromatographic method development and optimization, fraction collection, and drying processes prior to NMR analyses for unambiguous structure elucidation. To circumvent these challenges, a foundational framework for the proper utilization of supercritical carbon dioxide (scCO2) and deuterated modifiers (CD3OD) in sub/supercritical fluid chromatography (SFC) is herein introduced. This facilitates a streamlined multicomponent isolation with minimized protic residues, further enabling immediate NMR analysis. In addition to bypassing tedious drying processes and minimizing analyte degradation, this approach (complementary to traditional reversed-phase liquid chromatography, RPLC) delivers highly efficient separations and automated fraction collection using readily available analytical/midscale SFC instrumentation. A series of diverse analytes across a wide spectrum of chemical properties (acid, basic, and neutral), combined with different stationary-phase columns in SFC are investigated using both a protic organic modifier (CH3OH) and its deuterated counterpart (CD3OD). The power of this framework is demonstrated with pharmaceutically relevant applications in the context of target characterization and analysis of complex multicomponent reaction mixtures from modern synthetic chemistry, demonstrating high isolation yields while reducing both the environmental footprint and manual intervention. This workflow enables unambiguous fast-paced structure elucidation on the analytical scale, providing results that are comparable to traditional, but time-consuming, RPLC purification approaches.

Rapid label-free cell-based Approach Membrane Permeability Assay using MALDI-hydrogen-deuterium exchange mass spectrometry for peptides.

Peptide therapeutics are a growing modality in the pharmaceutical industry and expanding these therapeutics to hit intracellular targets would require establishing cell permeability. Rapid measurement target-agnostic cell permeability of peptides is still analytically challenging. In this study, we demonstrate the development of a rapid high-throughput label-free methodology based on a MALDI-hydrogen-deuterium exchange mass spectrometry (MALDI-HDX-MS) approach to rank-order peptide cell membrane permeability using live THP-1 and AsPc-1 cells. Peptides were incubated in the presence of live cells and their permeability into the cells over time was measured by MALDI-HDX-MS. A differential hydrogen-deuterium exchange approach was used to distinguish the peptides outside of the cells from those inside. The peptides on the outside of the cells were labeled using sufficiently short exposure to deuterium oxide, while the peptides inside of the cells were protected from labeling as a result of permeation into the cells. The deuterium labeled and peak area ratios of unlabeled peptides were compared and plotted over time. The developed methodology, referred to as Cell-based Approach Membrane Permeability Assay (CAMPA), was applied to study an array of 24 diverse peptides including cell-penetrating peptides, stapled and macrocyclic peptides. The cell membrane permeability results observed by CAMPA were corroborated by previously reported in literature data. The CAMPA MALDI-MS analysis was fully automated including MS data processing using internally developed Python scripts. Moreover, CAMPA was demonstrated to be useful for differentiating passive and active cell transportation by using an endocytosis inhibitor in cell incubation media for selected peptides.

Parallel chiral sub/supercritical fluid chromatography screening as a framework for accelerated purification of pharmaceutical targets.

Chiral sub/supercritical fluid chromatography (SFC) has established itself as one of the preferred techniques for enantioseparations at both analytical and preparative scale. Herein, we introduce a parallel multicolumn SFC screening for automated chiral method development in fast-paced settings. The practicality and speed advantages of this approach are illustrated with parallel screening of a diverse set of chiral molecules across ten columns with five different organic modifiers/CO2 based eluents enabling rapid identification of suitable enantioseparation conditions for accelerated purification of pharmaceutical targets. Rapid delivery turnarounds of pure enantiomers of less than 1 h from screening to target isolation are demonstrated illustrating the power of this approach.

Automated ion exchange chromatography screening combined with in silico multifactorial simulation for efficient method development and purification of biopharmaceutical targets.

Bioprocess development of increasingly challenging therapeutics and vaccines requires a commensurate level of analytical innovation to deliver critical assays across functional areas. Chromatography hyphenated to numerous choices of detection has undeniably been the preferred analytical tool in the pharmaceutical industry for decades to analyze and isolate targets (e.g., APIs, intermediates, and byproducts) from multicomponent mixtures. Among many techniques, ion exchange chromatography (IEX) is widely used for the analysis and purification of biopharmaceuticals due to its unique selectivity that delivers distinctive chromatographic profiles compared to other separation modes (e.g., RPLC, HILIC, and SFC) without denaturing protein targets upon isolation process. However, IEX method development is still considered one of the most challenging and laborious approaches due to the many variables involved such as elution mechanism (via salt, pH, or salt-mediated-pH gradients), stationary phase's properties (positively or negatively charged; strong or weak ion exchanger), buffer type and ionic strength as well as pH choices. Herein, we introduce a new framework consisting of a multicolumn IEX screening in conjunction with computer-assisted simulation for efficient method development and purification of biopharmaceuticals. The screening component integrates a total of 12 different columns and 24 mobile phases that are sequentially operated in a straightforward automated fashion for both cation and anion exchange modes (CEX and AEX, respectively). Optimal and robust operating conditions are achieved via computer-assisted simulation using readily available software (ACD Laboratories/LC Simulator), showcasing differences between experimental and simulated retention times of less than 0.5%. In addition, automated fraction collection is also incorporated into this framework, illustrating the practicality and ease of use in the context of separation, analysis, and purification of nucleotides, peptides, and proteins. Finally, we provide examples of the use of this IEX screening as a framework to identify efficient first dimension (1D) conditions that are combined with MS-friendly RPLC conditions in the second dimension (2D) for two-dimensional liquid chromatography experiments enabling purity analysis and identification of pharmaceutical targets.

Successive remodeling of IgG glycans using a solid-phase enzymatic platform.

The success of glycoprotein-based drugs in various disease treatments has become widespread. Frequently, therapeutic glycoproteins exhibit a heterogeneous array of glycans that are intended to mimic human glycopatterns. While immunogenic responses to biologic drugs are uncommon, enabling exquisite control of glycosylation with minimized microheterogeneity would improve their safety, efficacy and bioavailability. Therefore, close attention has been drawn to the development of glycoengineering strategies to control the glycan structures. With the accumulation of knowledge about the glycan biosynthesis enzymes, enzymatic glycan remodeling provides a potential strategy to construct highly ordered glycans with improved efficiency and biocompatibility. In this study, we quantitatively evaluate more than 30 enzymes for glycoengineering immobilized immunoglobulin G, an impactful glycoprotein class in the pharmaceutical field. We demonstrate successive glycan remodeling in a solid-phase platform, which enabled IgG glycan harmonization into a series of complex-type N-glycoforms with high yield and efficiency while retaining native IgG binding affinity.

In Silico Method Development of Achiral and Chiral Tandem Column Reversed-phase Liquid Chromatography for Multicomponent Pharmaceutical Mixtures.

Tandem column liquid chromatography (LC) is a convenient, cost-effective approach to resolve multicomponent mixtures by serially coupling columns on readily available one-dimensional separation systems without specialized user training. Yet, adoption of this technique remains limited, mainly due to the difficulty in identifying optimal selectivity out of many possible tandem column combinations. At this point, method development and optimization require laborious "hit-or-miss" experimentation and "blind" screening when investigating different column selectivity without standard analytes. As a result, many chromatography practitioners end up combining two columns of similar selectivity, limiting the scope and potential of tandem column LC as a mainstay for industrial applications. To circumvent this challenge, we herein introduce a straightforward in silico multifactorial approach as a framework to expediently map the separation landscape across multiple tandem columns (achiral and chiral) and eluent combinations (isocratic and gradient elution) under reversed-phase LC conditions. Retention models were built using commercially available LC simulator software showcasing less than 2% difference between experimental and simulated retention times for analytes of interest in multicomponent pharmaceutical mixtures (e.g., metabolites and cyclic peptides).

Trapping-Enrichment Multi-dimensional Liquid Chromatography with On-Line Deuterated Solvent Exchange for Streamlined Structure Elucidation at the Microgram Scale.

At the forefront of chemistry and biology research, development timelines are fast-paced and large quantities of pure targets are rarely available. Herein, we introduce a new framework, which is built upon an automated, online trapping-enrichment multi-dimensional liquid chromatography platform (TE-Dt-mDLC) that enables: 1) highly efficient separation of complex mixtures in a first dimension (1 D-UV); 2) automated peak trapping-enrichment and buffer removal achieved through a sequence of H2 O and D2 O washes using an independent pump setup; and 3) a second dimension separation (2 D-UV-MS) with fully deuterated mobile phases and fraction collection to minimize protic residues for immediate NMR analysis while bypassing tedious drying processes and minimizing analyte degradation. Diverse examples of target isolation and characterization from organic synthesis and natural product chemistry laboratories are illustrated, demonstrating recoveries above 90 % using as little as a few micrograms of material.

Utilizing in situ spectroscopic tools to monitor ketal deprotection processes.

The use of protection groups to shield a functional group during a synthesis is employed throughout many reactions and organic syntheses. The role of a protection group can be vital to the success of a reaction, as well as increase reaction yield and selectivity. Although much work has been done to investigate the addition of a protection group, the removal of the protection group is just as important - however, there is a lack of methods employed within the literature for monitoring the removal of a protection group in real time. In this work, the process of removing, or deprotecting, a ketal protecting group is investigated. Process analytical technology tools are incorporated for in situ analysis of the deprotection reaction of a small molecule model compound. Specifically, Raman spectroscopy and Fourier transform infrared spectroscopy show that characteristic bands can be used to track the decrease of the reactant and the increase of the expected products over time. To the best of our knowledge, this is the first report of process analytical technology being used to monitor a ketal deprotection reaction in real time. This information can be capitalized on in the future for understanding and optimizing pharmaceutically-relevant deprotection processes and downstream reactions.

In situ real time monitoring of emulsification and homogenization processes for vaccine adjuvants.

Adjuvants are commonly employed to enhance the efficacy of a vaccine and thereby increase the resulting immune response in a patient. The activity and effectiveness of emulsion-based adjuvants has been heavily studied throughout pharmaceuticals; however, there exists a lack in research which monitors the formation of a stable emulsion in real time. Process analytical technology (PAT) provides a solution to meet this need. PAT involves the collection of in situ data, thereby providing real time information about the monitored process as well as increasing understanding of that process. Here, three separate PAT tools - optical particle imaging, in situ particle analysis, and Raman spectroscopy - were used to monitor two key steps involved in the formation of a stable emulsion product, emulsification and homogenization, as well as perform a stability assessment. The obtained results provided new insights-particle size decreases during emulsification and homogenization, and molecular changes do not occur during either the emulsification or homogenization steps. Further, the stability assessment indicated that the coarse emulsion product obtained from the emulsification step is stable over the course of 24 hours when mixed. To the best of our knowledge, this is the first report of an analytical methodology for in situ, real time analysis of emulsification and homogenization processes for vaccine adjuvants. Using our proposed analytical methodology, an improved understanding of emulsion-based vaccine adjuvants can now be achieved, ultimately impacting the ability to develop and deliver successful pharmaceuticals.

Process monitoring of polysaccharide deketalization for vaccine bioconjugation development using in situ analytical methodology.

Pneumococcal conjugate vaccines (PCVs) are formed by bioconjugation of a carrier protein to the purified capsular polysaccharide (Ps) from multiple serological strains of Streptococcus pneumoniae. The associated bioconjugation chemistry relies on initial selective modifications to the Ps backbone structure. Among these modifications, removal of a ketal functional group, termed deketalization, is one that is important for pharmaceutical PCV production. Herein, we report a process monitoring investigation into the deketalization of a polysaccharide relevant to PCV process development. We have applied process analytical technology (PAT) for in situ process monitoring to study the deketalization reaction in real time. We find that in situ FTIR spectroscopy elucidates multiple classes of reaction kinetics, one of which correlates strongly with the deketalization reaction of interest. This PAT approach to real time reaction monitoring offers the possibility of improved process monitoring in the pharmaceutical production of PCVs. To our knowledge, this report represents the first PAT investigation into Ps deketalization. Our findings suggest that broader application of PAT to the chemical modifications associated with PCV bioconjugation, as well as other pharmaceutically relevant bioconjugation processes, carries the power to enhance process understanding, control, and efficiency through real time process monitoring.

Selective Plate-Based Assay for Trace EDTA Analysis via Boron Trifluoride-methanol Derivatization UHPLC-QqQ-MS/MS Enabling Biologic and Vaccine Processes.

The employment of ethylenediaminetetraacetic acid (EDTA) across several fields in chemistry and biology has required the creation of a high number of quantitative assays. Nonetheless, the determination of trace EDTA, especially in biologics and vaccines, remains challenging. Herein, we introduce an automated high-throughput approach based on EDTA esterification in 96-well plates using boron trifluoride-methanol combined with rapid analysis by ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). Derivatization of EDTA to its methyl ester (Me-EDTA) serves to significantly improve chromatographic performance (retention, peak shape, and selectivity), while also delivering a tremendous enhancement of sensitivity in the positive ion mode electrospray ionization (ESI+). This procedure, in contrast to previous EDTA methods based on complexation with metal ions, is not affected by high concentration of other metals, buffers, and related salts abundantly present in biopharmaceutical processes (e.g., iron, copper, citrate, etc.). Validation of this assay for the determination of ng·mL-1 level EDTA in monoclonal antibody and vaccine products demonstrated excellent performance (repeatability, precision, and linear range) with high recovery from small sample volumes while also providing an advantageous automation-friendly workflow for high-throughput analysis.

Enantioselective UHPLC Screening Combined with In Silico Modeling for Streamlined Development of Ultrafast Enantiopurity Assays.

Enantioselective chromatography has been the preferred technique for the determination of enantiomeric excess across academia and industry. Although sequential multicolumn enantioselective supercritical fluid chromatography screenings are widespread, access to automated ultra-high-performance liquid chromatography (UHPLC) platforms using state-of-the-art small particle size chiral stationary phases (CSPs) is an underdeveloped area. Herein, we introduce a multicolumn UHPLC screening workflow capable of combining 14 columns (packed with sub-2 µm fully porous and sub-3 µm superficially porous particles) with nine mobile phase eluent choices. This automated setup operates under a vast selection of reversed-phase liquid chromatography, hydrophilic interaction liquid chromatography, polar-organic mode, and polar-ionic mode conditions with minimal manual intervention and high success rate. Examples of highly efficient enantioseparations are illustrated from the integration of chiral screening conditions and computer-assisted modeling. Furthermore, we describe the nuances of in silico method development for chiral separations via second-degree polynomial regression fit using LC simulator (ACD/Labs) software. The retention models were found to be very accurate for chiral resolution of single and multicomponent mixtures of enantiomeric species across different types of CSPs, with differences between experimental and simulated retention times of less than 0.5%. Finally, we illustrate how this approach lays the foundation for a streamlined development of ultrafast enantioseparations applied to high-throughput enantiopurity analysis and its use in the second dimension of two-dimensional liquid chromatography experiments.

Quantitation and speciation of residual protein within active pharmaceutical ingredients using image analysis with SDS-PAGE.

Recent advances in biocatalysis and directed enzyme evolution has led to a variety of enzymatically-driven, elegant processes for active pharmaceutical ingredient (API) production. For biocatalytic processes, quantitation of any residual protein within a given API is of great importance to ensure process robustness and quality, pure pharmaceutical products. Typical analytical methods for analyzing residual enzymes within an API, such as enzyme-linked immunosorbent assays (ELISA), colorimetric assays, and liquid chromatographic techniques, are limited for determining only the concentration of known proteins and require harsh solvents with high API levels for analysis. For the first time, total residual protein content in a small molecule API was quantitated using image analysis applied to SDS-PAGE. Herein, a proposed methodology for residual protein detection, quantitation, and size-based speciation is presented, in which an orthogonal technique is offered to traditional analysis methods, such as ELISA. Results indicate that our application of the analytical methodology is able to reliably quantitate both protein standards and the total residual protein present within a final API, with good agreement as compared to traditional ELISA results. Further, speciation of the residual protein within the API provides key information concerning the individual residual proteins present, including their molecular weight, which can lead to improved process development efforts for residual protein rejection and control. This analytical methodology thus offers an alternative tool for easily identifying, quantitating, and speciating residual protein content in the presence of small molecule APIs, with potential for wide applicability across industry for biocatalytic or directed enzyme evolution efforts within process development.

In Silico Multifactorial Modeling for Streamlined Development and Optimization of Two-Dimensional Liquid Chromatography.

Continued adoption of two-dimensional liquid chromatography (2D-LC) in industrial laboratories will depend on the development of approaches to make method development for 2D-LC more systematic, less tedious, and less reliant on user expertise. In this paper, we build on previous efforts in these directions by describing the use of multifactorial modeling software that can help streamline and simplify the method development process for 2D-LC. Specifically, we have focused on building retention models for second dimension (2D) separations involving variables including gradient time, temperature, organic modifier blending, and buffer concentration using LC simulator (ACD/Labs) software. Multifactorial retention modeling outcomes are illustrated as resolution map planes or cubes that enable straightforward location of 2D conditions that maximize resolution while minimizing analysis time. We also illustrate the practicality of this approach by identifying conditions that yield baseline separation of all compounds co-eluting from a first dimension (1D) separation using a single combination of 2D stationary phase and elution conditions. The multifactorial retention models were found to be very accurate for both the 1D and 2D separations, with differences between experimental and simulated retention times of less than 0.5%. Pharmaceutical applications of this approach for multiple heartcutting 2D-LC were demonstrated using IEC-IEC or achiral RPLC-chiral RPLC for 2D separations of multicomponent mixtures. The framework outlined here should help make 2D-LC method development more systematic and streamline development and optimization for a variety of 2D-LC applications in both industry and academia.

In silico method development for the reversed-phase liquid chromatography separation of proteins using chaotropic mobile phase modifiers.

Recent advances in biomedical and pharmaceutical processes has enabled a notable increase of protein- and peptide-based drug therapies and vaccines that often contain a higher-order structure critical to their efficacy. Hyphenation of chromatographic and spectrometric techniques is at the center of all facets of biopharmaceutical analysis, purification and chemical characterization. Although computer-assisted chromatographic modeling of small molecules has reached a mature stage across the pharmaceutical industry, software-based method optimization approaches for large molecules has yet to see the same revitalization. Conformational changes of biomolecules under chromatographic conditions have been identified as the major culprit in terms of sub-optimal modeling outcomes. In order to circumvent these challenges, we herein investigate the outcomes generated via computer-assisted modeling from using different chaotropic and denaturing mobile phases (trifluoroacetic acid, sodium perchlorate and guanidine hydrochloride in acetonitrile/water-based eluents). Linear and polynomial regression retention models using ACD/Labs software were built as a function of gradient slope, column temperature and mobile phase buffer for eight different model proteins ranging from 12 to 670 kDa (holo-transferrin, cytochrome C, apomyoglobin, ribonuclease A, ribonuclease A type I-A, albumin, y-globulin and thyroglobulin bovine). Correlation between experimental and modeled outputs was substantially improved by using strong chaotropic and denaturing modifiers in the mobile phase, even when using linear regression modeling as typically observed for small molecules. On the contrary, the use of conventional TFA buffer concentrations at low column temperatures required the used of polynomial regression modeling indicating potential conformational structure changes of proteins upon chromatographic conditions. In addition, we illustrate the power of modern computer-assisted chromatography modeling combined with chaotropic agents in the developing of new RPLC assays for protein-based therapeutics and vaccines.

Charged aerosol detection in early and late-stage pharmaceutical development: selection of regressionmodels at optimum power function value.

In recent years, the use of quantitative liquid chromatography (LC) coupled charged aerosol detection (CAD) for poor UV absorbing analytes in multicomponent mixtures has grown exponentially across academic and industrial sectors. The ballpark of previous LC-CAD reports is focused on practical applications, as well as optimization of critical parameters such as: response dependencies on temperature, nebulization process, analyte volatility, and mobile-phase composition. However, straightforward approaches to deal with the characteristic nonlinear response of CAD still scarce. A highly overlooked parameter is the power function value (PFV), whose optimization enables a detection signal that is more linear with higher signal-to-noise ratio (S/N) and lower relative standard deviation (RSD) of area counts. Herein, a systematic investigation of different regression models (log-log, first-and second-degree polynomial) by both interpolation and extrapolation process in conjunction with PFV optimization throughout the development of LC-CAD assays is reported. The accuracy of the results via interpolation is always good (< 5%) when operating in the vicinity of the optimum PFV regardless the regression model choice. On the contrary, extrapolation process only worked when applying log-log regression at the optimum PFV (accuracy <5%). This outcome indicates that a first-order regression via interpolation can be a safe and simple choice for quantitative LC-CAD in highly regulated laboratories (GLP, GMP, etc.). Whereas a straightforward extrapolation combined with log-log regression can enable the deployment of high-throughput LC-CAD assays, especially but not limited to laboratories where the synthetic process route is undergoing rapid change and optimization (medicinal chemistry, discovery, biocatalysis, process chemistry, etc.). This approach is crucial in developing quantitative LC-CAD assays for poor UV absorbing pharmaceuticals that are sensitive, precise, accurate and robust across early and late-stage pharmaceutical development.

Mapping the Separation Landscape in Two-Dimensional Liquid Chromatography: Blueprints for Efficient Analysis and Purification of Pharmaceuticals Enabled by Computer-Assisted Modeling.

Recent developments in two-dimensional liquid chromatography (2D-LC) now make separation and analysis of very complex mixtures achievable. Despite being such a powerful chromatographic tool, current 2D-LC technology requires a series of arduous method development activities poorly suited for a fast-paced industrial environment. Recent introductions of new technologies including active solvent modulation and a support for multicolumn 2D-LC are helping to overcome this stigma. However, many chromatography practitioners believe that the lack of a systematic way to effectively optimize 2D-LC separations is a missing link in securing the viability of 2D-LC as a mainstay for industrial applications. In this work, a computer-assisted modeling approach that dramatically simplifies both offline and online 2D-LC method developments is introduced. Our methodology is based on mapping the separation landscape of pharmaceutically relevant mixtures across both first (1D) and second (2D) dimensions using LC Simulator (ACD/Labs) software. Retention models for 1D and 2D conditions were built using a minimal number of multifactorial modeling experiments (2 × 2 or 3 × 3 parameters: gradient slope, column temperature, and different column and mobile phase combinations). The approach was first applied to online 2D-LC analysis involving achiral and chiral separations of complex mixtures of enantiomeric species. In these experiments, the retention models proved to be quite accurate for both the 1D and 2D separations, with retention time differences between experiments and simulations of less than 3.5%. This software-based concept was also demonstrated for offline 2D-LC purification of drug substances.