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

Two-dimensional size exclusion reversed-phase liquid chromatography for quantitative analysis of L1 proteins in complex vaccine matrices

The quantitation of the major capsid protein L1 is an important metric during the pharmaceutical manufacturing of human papilloma virus (HPV) vaccines, as they are critical components of virus like particles (VLPs) that form the core of the drug product. During the production of VLPs, the L1 protein is present in multiple states, including monomer, multimer, fully formed VLPs and aggregate species, whose expression levels provides an important read-out of upstream productivity and downstream purification efficiency through the measurement of step yields. However, quantitation of total L1 protein is challenging not only due to its presence in multiple states, but also due to the matrix complexity and purification stage of the samples, which spans complex cell lysate to cleaner post purification material. Current analytical methods typically implemented for L1 quantitation includes direct UV measurement (such as SoloVPE), which is robust and easily deployed, but best suited to analysis of purified samples. Automated capillary electrophoresis techniques such as Simple Western are well established but dependent on reproducible binding to accessible L1 epitopes and potentially susceptible to antibody lot to lot reproducibility which may pose an operational risk. Mass spectrometry-based techniques provide excellent sensitivity and characterization advantages but are challenging to deploy in a manufacturing setting. Additionally, conventional one-dimensional liquid chromatography separation of L1 from host cell protein or cellular components is ineffective particularly in high-complexity lysate samples and intermediates prior to chromatographic purification steps. Herein, we present a sample preparation strategy and analytical method that is capable of total L1 quantitation regardless of its multimeric state and is compatible with sample matrices ranging from crude lysate to purified samples, without the use of complicated and serotype-specific reagents. We employ reduction and heat-denaturation during sample preparation to simplify the multimeric states of L1 to its monomer form and utilize two-dimension liquid chromatography (2D-LC) with first dimension (1D) size exclusion and peak heart-cutting to second dimension (2D) reversed-phase separation modes coupled to diode array and fluorescence detectors. In addition, a reliable method for total L1 quantitation in multiple process intermediate steps (upstream and downstream) is demonstrated with evaluation of analytical figures of merit including limit of quantitation, linearity, and repeatability.

Digitally Enabled Generic Analytical Framework Accelerating the Pace of Liquid Chromatography Method Development for Vaccine Adjuvant Formulations

The growing use of adjuvants in the fast-paced formulation of new vaccines has created an unprecedented need for meaningful analytical assays that deliver reliable quantitative data from complex adjuvant and adjuvant-antigen mixtures. Due to their complex chemical and physical properties, method development for the separation of vaccine adjuvants is considered a highly challenging and laborious task. Reversed-phase liquid chromatography (RPLC) is among the most important tests in the (bio)pharmaceutical industry for release and stability indicating measurements including adjuvant content, identity, and purity profile. However, the time constraints of developing "on-demand" robust quantitative methods prior to each change in formulation can easily lead to sample analysis becoming a bottleneck in vaccine development. Herein, a simple and efficient generic analytical framework capable of chromatographically resolving the most commonly used non-aluminum-based adjuvants across academic and industrial sectors is introduced. This was designed to seek a more proactive approach for fast-paced assay development endeavors that evolved from extensive stationary phase screening in conjunction with multifactorial in silico simulations of adjuvant retention time (RT) as a function of gradient time, temperature, organic modifier blending, and buffer concentration. The multifactorial retention models yield 3D resolution maps with excellent baseline separation of all adjuvants in a single run, which was found to be very accurate, with differences between experimental and simulated retention times of less than 1%. The analytical framework described here also includes the introduction of a more versatile approach to method development by introducing a dynamic RT database for adjuvants covering the entire library of adjuvants with broad mechanisms of action across numerous vaccine formulations with excellent linearity, accuracy, precision, and specificity. The power of this framework was also demonstrated with numerous analytical assays that can be generated rapidly from simulations guiding vaccine processes in the development of new adjuvant formulations. Analytical assay in this work covers content, purity profile by LC with diode array detector (DAD) and charged aerosol detector (CAD), and component identification by LC with mass spectrometry (MS) across complex vaccine formulations, including the use of surfactants (e.g., polysorbates) as well as their separation from adjuvant targets.

In-silico method development and optimization of on-line comprehensive two-dimensional liquid chromatography via a shortcut model

Comprehensive two-dimensional liquid chromatography (LCxLC) represents a valuable alternative to conventional single column, or one-dimensional, liquid chromatography (1D-LC) for resolving multiple components in a complex mixture in a short time. However, developing LCxLC methods with trial-and-error experiments is challenging and time-consuming, which is why the technique is not dominant despite its significant potential. This work presents a novel shortcut model to in-silico predicting retention time and peak width within an RPLCxRPLC separation system (i.e., LCxLC systems that use reversed-phase columns (RPLC) in both separation dimensions). Our computationally effective model uses the hydrophobic-subtraction model (HSM) to predict retention and considers limitations due to the sample volume, undersampling and the maximum pressure drop. The shortcut model is used in a two-step strategy for sample-dependent optimization of RPLCxRPLC separation systems. In the first step, the Kendall's correlation coefficient of all possible combinations of available columns is evaluated, and the best column pair is selected accordingly. In the second step, the optimal values of design variables, flow rate, pH and sample loop volume, are obtained via multi-objective stochastic optimization. The strategy is applied to method development for the separation of 8, 12 and 16 component mixtures. It is shown that the proposed strategy provides an easy way to accelerate method development for full-comprehensive 2D-LC systems as it does not require any experimental campaign and an entire optimization run can take less than two minutes.

Development and Validation of Novel HPLC Methods for Quantitative Determination of Vitamin D3 in Tablet Dosage Form

In the present work, an efficient isocratic HPLC method was developed for the precise and accurate estimation of vitamin D3 in tablet form. The chromatographic conditions comprised an L3 silica column (5 µm in particle size, 4.6 mm × 250 mm) with a mobile phase n-hexane/ethyl acetate (85:15 v/v) with a flow rate of 2.0 mL/min and a detection wavelength of 292 nm. The new methodology was validated for accuracy, precision, specificity, robustness, and quantification limits according to an official monograph of USP/BP and ICH guidelines. The peak areas of the six replicates of the homogeneous sample were recorded. The mean value obtained was 67,301, and the relative standard deviation (RSD) was 0.1741. The linearity and range were in the acceptable bounds, i.e., 0.999, which was calculated using regression line analysis. The results show that the method is truly acceptable as the RSD, as the flow rate was 0.81%, while for the mobile phase composition, it was 0.72%, which lies in the acceptable range. The limit of detection (LOD) and the limit of quantification (LOQ) values were 0.0539 µg/mL and 0.1633 µg/mL, respectively. The % RSD of the intra and inter-day precision of the method was deemed acceptable according to the international commission for harmonization guidelines. The developed method has potential to be used for the detection and quantification of vitamin D3 during routine analysis for tablets in dosage form.

Universal ion chromatography method for anions in active pharmaceutical ingredients enabled by computer-assisted separation modeling

Ion Chromatography (IC) is one of the most widely used methods for analyzing ionic species in pharmaceutical samples. A universal IC method that can separate a wide range of different analytes is highly desired as it can save a lot of time for method development and validation processes. Herein we report the development of a universal method for anions in active pharmaceutical ingredients (APIs) using computer-assisted chromatography modeling tools. We have screened three different IC columns (Dionex IonPac AS28-Fast 4 µm, AS19 4 µm and AS11-HC 4 µm) to determine the best suitable column for universal IC method development. A universal IC method was then developed using an AS11-HC 4 µm column to separate 31 most common anionic substances in 36 mins. This method was optimized using LC Simulator and a model which precisely predicts the retention behavior of 31 anions was established. This model demonstrated an excellent match between predicted and experimental analyte retention time (R2 =0.999). To validate this universal IC method, we have studied the stability of sulfite and sulfide analytes in ambient conditions. The method was then validated for a subset of 29 anions using water and organic solvent/water binary solvents as diluents for commercial APIs. This universal IC method provides an efficient and simple way to separate and analyze common anions in APIs. In addition, the method development process combined with LC simulator modeling can be effectively used as a starting point during method development for other ions beyond those investigated in this study.

Improved assay development of pharmaceutical modalities using feedback-controlled liquid chromatography optimization

Development of meaningful and reliable analytical assays in the (bio)pharmaceutical industry can often be challenging, involving tedious trial and error experimentation. In this work, an automated analytical workflow using an AI-based algorithm for streamlined method development and optimization is presented. Chromatographic methods are developed and optimized from start to finish by a feedback-controlled modeling approach using readily available LC instrumentation and software technologies, bypassing manual user intervention. With the use of such tools, the time requirement of the analyst is drastically minimized in the development of a method. Herein key insights on chromatography system control, automatic optimization of mobile phase conditions, and final separation landscape for challenging multicomponent mixtures are presented (e.g., small molecules drug, peptides, proteins, and vaccine products) showcased by a detailed comparison of a chiral method development process. The work presented here illustrates the power of modern chromatography instrumentation and AI-based software to accelerate the development and deployment of new separation assays across (bio)pharmaceutical modalities while yielding substantial cost-savings, method robustness, and fast analytical turnaround.

Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings

The (bio)pharmaceutical industry is rapidly moving towards complex drug modalities that require a commensurate level of analytical enabling technologies that can be deployed at a fast pace. Unsystematic method development and unnecessary manual intervention remain a major barrier towards a more efficient deployment of meaningful analytical assay across emerging modalities. Digitalization and automation are key to streamline method development and enable rapid assay deployment. This review discusses the use of computer-assisted multifactorial chromatographic method development strategies for fast-paced downstream characterization and purification of biopharmaceuticals. Various chromatographic techniques such as reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), ion exchange chromatography (IEX), hydrophobic interaction chromatography (HIC), and supercritical fluid chromatography (SFC) are addressed and critically reviewed. The most significant parameters for retention mechanism modelling, as well as mapping the separation landscape for optimal chromatographic selectivity and resolution are also discussed. Furthermore, several computer-assisted approaches for optimization and development of chromatographic methods of therapeutics, including linear, nonlinear, and multifactorial modelling are outlined. Finally, the potential of the chromatographic modelling and computer-assisted optimization strategies are also illustrated, highlighting substantial productivity improvements, and cost savings while accelerating method development, deployment and transfer processes for therapeutic analysis in industrial settings.

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.

[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.

Expediting the chromatographic analysis of COVID-19 antibody therapeutics with ultra-short columns, retention modeling and automated method development

The COVID-19 pandemic necessitated the emergency use authorization (EUA) of several new therapeutics and vaccines. Several monoclonal antibodies (mAbs) were among those authorized for use, and they have served a purpose to provide passive immunity and to help minimize dangerous secondary effects in at-risk and hospitalized patients infected with SARS-CoV-2. With an EUA submission, scientific data on a drug candidate is often collected near simultaneously alongside drug development. In such a situation, there is little time to allow misguided method development nor time to wait on traditional turnaround times. We have taken this dilemma as a chance to propose new means to expediting the chromatographic characterization of protein therapeutics. To this end, we have combined the use of automated, systematic modeling and ultrashort LC columns to quickly optimize high throughput RP, IEX, HILIC and SEC separations for two COVID-19-related mAbs. The development and verification of these four complementary analytical methods required only 2 days of experimental work. In the end, one chromatographic analysis can be performed with a sub-2 min run time such that it is feasible to comprehensively characterize a COVID-19 mAb cocktail by 4 different profiling techniques within a 1-hour turnaround time.

The Future of Method Development for Two-Dimensional Liquid Chromatography – Work Smarter, Not Just Harder?

The potential for wider use of two-dimensional liquid chromatography (2D-LC) is becoming more evident as the complexity of samples that must be handled continues to increase in application areas ranging from biopharmaceuticals to biosourced consumer products. Although the sophistication and ease of use have improved in recent years for commercial 2D-LC instruments, many analysts are still intimidated by the method development process for 2D methods because of the larger number of variables involved compared to conventional liquid chromatography. In this article, I share my perspective on the trends in this area, and the developments we are likely to see in the field in the near future.

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.

Ultrahigh-Performance Supercritical Fluid Chromatography and Detection of Multiple Biogenic Amines in Gentamicin Sulfate: Method Development Using Computer-Assisted Modeling

In order to solve the problem of difficult separation of various biogenic amines (BAs), which have similar structures or very different polarities, in gentamicin, by conventional liquid chromatography, a new ultrahigh-performance supercritical fluid chromatography (UHPSFC) method was developed. In this method, 10 BAs were derivatized precolumn using dansyl chloride and separated using a UHPSFC system. By computational simulation, complete separation of 10 BAs was successfully achieved. Detection was performed using a photodiode array (PDA) and single-quadrupole mass spectrometry (MS) together with electrospray ionization (ESI). A wide linear range (10-2500 ng/mL) was achieved, with the limits of detection (LODs) between 1.2 and 10.0 ng/mL and the limits of quantification (LOQs) between 5.0 and 25.0 ng/mL. Apart from high sensitivity, this UHPSFC-PDA/ESI-MS detection method also displayed high accuracy, the matrix effect was reduced by an appreciable extent, and the recovery rates of the 10 BAs were between 84.1 and 117.1%. For comparison, high-performance liquid chromatography-tandem mass spectrometry (MS/MS) was also used for the detection of underivatized BAs in gentamicin, showing good linearity and high sensitivity (LODs from 0.05 to 1.00 ng/mL and LOQs from 1.00 to 12.50 ng/mL) for all BAs except for spermine and spermidine. Although single-quadrupole MS is inferior to MS/MS in terms of sensitivity, the UHPSFC method could detect more BAs. It also achieved the quantification limits required for impurity determination, demonstrating a potential strategy to offer a map overview of possible BA presence in fermentation antibiotics.

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.

Biological roles of RNA m5C modification and its implications in Cancer immunotherapy

Epigenetics including DNA and RNA modifications have always been the hotspot field of life sciences in the post-genome era. Since the first mapping of N6-methyladenosine (m6A) and the discovery of its widespread presence in mRNA, there are at least 160-170 RNA modifications have been discovered. These methylations occur in different RNA types, and their distribution is species-specific. 5-methylcytosine (m5C) has been found in mRNA, rRNA and tRNA of representative organisms from all kinds of species. As reversible epigenetic modifications, m5C modifications of RNA affect the fate of the modified RNA molecules and play important roles in various biological processes including RNA stability control, protein synthesis, and transcriptional regulation. Furthermore, accumulative evidence also implicates the role of RNA m5C in tumorigenesis. Here, we review the latest progresses in the biological roles of m5C modifications and how it is regulated by corresponding "writers", "readers" and "erasers" proteins, as well as the potential molecular mechanism in tumorigenesis and cancer immunotherapy.

Perspectives on the Use of Retention Modeling to Streamline 2D-LC Method Development: Current State and Future Prospects

The history of multidimensional liquid chromatography (MDLC) has been dominated by methods that have been developed using highly empirical, experience-driven, trial-and-error approaches. These approaches have been sufficient in progressing the field forward scientifically, primarily in academic research laboratories. However, more widespread usage of multidimensional separations will require more systematic approaches to method development that rely less on user experience and lower the barriers to development and use of methods by a wider community of users. In this mini-review, we discuss recent research aimed at developing such systematic, model-driven approaches to streamline method development and speculate about likely advances in the same direction in the near future. It seems likely that such model-driven approaches would be particularly helpful for methods developed for analyzing biopharmaceutical molecules, which tend to be very sensitive to slight changes in method conditions (for example, mobile phase composition).

Comprehensive profiling of Sanguisorba officinalis using off-line two-dimensional mixed-mode liquid chromatography × reversed-phase liquid chromatography, tandem high-resolution mass spectrometry, and molecular network

The profiling of natural products is important in modern biological sciences and new drug development. However, the separation and characterization of complex herbal extracts are significantly challenging for researchers in the biochemical field. Herein, an off-line two-dimensional mixed-mode LC × reversed-phase LC system is developed. Our system exhibits high orthogonality and is composed of a newly prepared stationary phase in the first dimension and a traditional C₁₈ phase in the second dimension, and is operated in combination with high-resolution MS and molecular network. Sanguisorba officinalis L. is studied using the proposed method owing to its bioactivity. With the aid of orthogonal separation, the ionization of the individual components is improved. The number of detected compounds and separated peaks are significantly increased when one-dimensional-LC is upgraded to two-dimensional-LC. In addition, 270 compounds (127 of which are tentatively characterized as new compounds, and further confirmation is needed) are successfully characterized based on their fragmentation patterns under the guidance of molecular network, while only 95 compounds are characterized using one-dimensional-LC and high-resolution MS. The results indicate that the developed off-line two-dimensional mixed-mode LC × reversed-phase LC, tandem high-resolution MS, and molecular network method is effective for profiling complex samples. This article is protected by copyright. All rights reserved.

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).

Structure identification and analysis of the suspected chemical precursor of 2-fluorodeschloroketamine and its decomposition products

In this work, 1-[(2"-fluorophenyl)(methylimino) methyl]cyclopentan-1-ol (2-fluorodeschlorohydroxylimine) was identified as a suspected chemical precursor of 2-fluorodeschloroketamine (2-FDCK) using GC-MS and GC-Q/TOF-MS and comparing the data with those of ketamine and its chemical precursor, hydroxylimine. Furthermore, the entire fragmentation pathway of 2-fluorodeschlorohydroxylimine was theorized from the GC-MS spectrum recorded using an electron ionization (EI) source, and the mechanisms and decomposition pathways of 2-fluorodeschlorohydroxylimine were elucidated. In protic solvents, the nitrogen atom in the C=N group of 2-fluorodeschlorohydroxylimine underwent a protonation reaction. Thereafter, the traces of water present in protic solvents promoted the hydrolysis of the protonated imine, and a carbon cation was obtained following the loss of methylamine. The carbon cation could follow the classical decomposition mechanism of imines and yield an α-hydroxyl ketone, which was the major decomposition product, (2'-fluorophenyl)(1"-hydroxycyclopentyl) methanone. The cation could also undergo a loop expansion rearrangement and yield another α-hydroxyl ketone, 2-(2'-fluorophenyl)-2-hydroxycyclohexan-1-one. The structures of the two aforementioned decomposition products were elucidated using several techniques including theoretical calculation, GC-MS, NMR, the prediction and assistance elucidation functions of ACDLabs-Structure Elucidator Suite, and the virtual separation technology of diffusion-ordered spectroscopy. The aforementioned study revealed important information about the chemical precursor of 2-FDCK and its decomposition. Furthermore, a set of methods for the qualitative analysis of 2-fluorodeschlorohydroxylimine was established, which facilitated accurate analysis of 2-fluorodeschlorohydroxylimine samples following decomposition or destruction.

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.

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.

Downstream Processing of Therapeutic Peptides by Means of Preparative Liquid Chromatography

The market of biomolecules with therapeutic scopes, including peptides, is continuously expanding. The interest towards this class of pharmaceuticals is stimulated by the broad range of bioactivities that peptides can trigger in the human body. The main production methods to obtain peptides are enzymatic hydrolysis, microbial fermentation, recombinant approach and, especially, chemical synthesis. None of these methods, however, produce exclusively the target product. Other species represent impurities that, for safety and pharmaceutical quality reasons, must be removed. The remarkable production volumes of peptide mixtures have generated a strong interest towards the purification procedures, particularly due to their relevant impact on the manufacturing costs. The purification method of choice is mainly preparative liquid chromatography, because of its flexibility, which allows one to choose case-by-case the experimental conditions that most suitably fit that particular purification problem. Different modes of chromatography that can cover almost every separation case are reviewed in this article. Additionally, an outlook to a very recent continuous chromatographic process (namely Multicolumn Countercurrent Solvent Gradient Purification, MCSGP) and future perspectives regarding purification strategies will be considered at the end of this review.

Advances in ultra-high-pressure and multi-dimensional liquid chromatography instrumentation and workflows

The present contribution discusses recent advances in ultra-high-pressure liquid chromatography (UHPLC) and multi-dimensional liquid chromatography (MDLC) technology. First, new developments in UHPLC column technology and system design are highlighted. The latter includes a description of a novel injector concept enabling method speed-up, emerging detectors, and instrument diagnostics approaches. Next, online MDLC workflows are reviewed and advances in modulation technology are highlighted. Finally, key applications published in 2020 are reviewed.