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The pharmaceutical industry is rapidly advancing toward new drug modalities, necessitating the development of advanced analytical strategies for effective, meaningful, and reliable assays. Hydrophilic Interaction Chromatography (HILIC) is a powerful technique for the analysis of polar analytes. Despite being a well-established technique, HILIC method development can be laborious owing to the multiple factors that affect the separation mechanism, such as the selection of stationary phase chemistry, mobile phase eluents, and optimization of column equilibration time. Herein, we introduce a new automated multicolumn and multi-eluent screening workflow that streamlines the development of new HILIC assays, circumventing the existing tedious 'hit-or-miss' approach. A total of 12 complementary columns packed with sub-2 µm fully porous and 2.7 µm superficially porous particles operated on readily available ultra-high pressure liquid chromatography (UHPLC) instrumentation across a diverse set of commercially available polar stationary phases were investigated. Different mobile phases with pH ranging from pH 3 to 9 were evaluated using different organic modifiers. The gradient and column re-equilibration were judiciously set to ensure a reliable assay screening framework that indicates promising conditions for subsequent method optimization to achieve resolution of challenging mixtures. This UHPLC screening system is coupled with a diode array and charged aerosol detectors (DAD, CAD and mass spectrometry) to ensure versatile detection for a variety of compounds. This fast-screening platform lays the foundation for a convenient generic workflow, accelerating the pace of HILIC method development and transfer across both academic and industrial sectors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The predictive modeling of liquid chromatography methods can be an invaluable asset, potentially saving countless hours of labor while also reducing solvent consumption and waste. Tasks such as physicochemical screening and preliminary method screening systems where large amounts of chromatography data are collected from fast and routine operations are particularly well suited for both leveraging large datasets and benefiting from predictive models. Therefore, the generation of predictive models for retention time is an active area of development. However, for these predictive models to gain acceptance, researchers first must have confidence in model performance and the computational cost of building them should be minimal. In this study, a simple and cost-effective workflow for the development of machine learning models to predict retention time using only Molecular Operating Environment 2D descriptors as input for support vector regression is developed. Furthermore, we investigated the relative performance of models based on molecular descriptor space by utilizing uniform manifold approximation and projection and clustering with Gaussian mixture models to identify chemically distinct clusters. Results outlined herein demonstrate that local models trained on clusters in chemical space perform equivalently when compared to models trained on all data. Through 10-fold cross-validation on a comprehensive set containing 67,950 of our company's proprietary analytes, these models achieved coefficients of determination of 0.84 and 3 % error in terms of retention time. This promising statistical significance is found to translate from cross-validation to prospective prediction on an external test set of pharmaceutically relevant analytes. The observed equivalency of global and local modeling of large datasets is retained with METLIN's SMRT dataset, thereby confirming the wider applicability of the developed machine learning workflows for global models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

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 (R 2 =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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The emergence of complex biological modalities in the biopharmaceutical industry entails a significant expansion of the current analytical toolbox to address the need to deploy meaningful and reliable assays at an unprecedented pace. Size exclusion chromatography (SEC) is an industry standard technique for protein separation and analysis. Some constraints of traditional SEC stem from its restricted ability to resolve complex mixtures and notoriously long run times while also requiring multiple offline separation conditions on different pore size columns to cover a wider molecular size distribution. Two-dimensional liquid chromatography (2D-LC) is becoming an important tool not only to increase peak capacity but also to tune selectivity in a single online method. Herein, an online 2D-LC framework in which both dimensions utilize SEC columns with different pore sizes is introduced with a goal to increase throughput for biomolecule separation and characterization. In addition to improving the separation of closely related species, this online 2D SEC-SEC approach also facilitated the rapid analysis of protein-based mixtures of a wide molecular size range in a single online experimental run bypassing time-consuming deployment of different offline SEC methods. By coupling the second dimension with multiangle light scattering (MALS) and differential refractive index (dRI) detectors, absolute molecular weights of the separated species were obtained without the use of calibration curves. As illustrated in this report for protein mixtures and vaccine processes, this workflow can be used in scenarios where rapid development and deployment of SEC assays are warranted, enabling bioprocess monitoring, purity assessment, and characterization.

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to inappropriately influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

P(v) iminophosphorane compounds are accessed via electrochemical oxidation of commercially available P(iii) phosphines, including mono-, di- and tri-dentate phosphines, as well as chiral phosphines. The reaction uses inexpensive bis(trimethylsilyl)carbodiimide as an efficient and safe aminating reagent. DFT calculations, cyclic voltammetry, and NMR studies provide insight into the reaction mechanism. The proposed mechanism reveals a special case of sequential paired electrolysis. DFT calculations of the frontier orbitals of an iminophosphorane are compared with those of the analogous phosphines and phosphine oxides. X-ray crystallographic studies of the ligands as well as a Ni-coordination complex provide structural insight for these ligands. The utility of these iminophosphoranes as ligands is demonstrated in nickel-catalyzed cross-electrophile couplings including C(sp 2 )-C(sp 3 ) and C(sp 2 )-C(sp 2 ) couplings, an electrochemically driven C-N cross-coupling, and a photochemical arylative C(sp 3 )-H functionalization. In some cases, these new ligands provide improved performance over commonly used sp 2 - N -based ligands ( e.g. 4,4'-di- tert -butyl-2,2'-bipyridine)., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Fast-paced pharmaceutical process developments (e.g., high-throughput experimentation, directed evolution, and machine learning) involve the introduction of fast, sensitive, and accurate analytical assays using limited sample volumes. In recent years, acoustic droplet ejection (ADE) coupled with an open port interface has been invented as a sampling technology for mass spectrometry, providing high-throughput nanoliter analytical measurements directly from the standard microplates. Herein, we introduce an ADE-multiple reaction monitoring-mass spectrometry (ADE-MRM-MS) workflow to accelerate pharmaceutical process research and development (PR&D). This systematic workflow outlines the selection of MRM transitions and optimization of assay parameters in a data-driven manner using rapid measurements (1 sample/s). The synergy between ADE sampling and MRM analysis enables analytical assays with excellent sensitivity, selectivity, and speed for PR&D reaction screenings. This workflow was utilized to develop new ADE-MRM-MS assays guiding a variety of industrial processes, including (1) screening of Ni-based catalysts for C-N cross-coupling reaction at 1 Hz and (2) high-throughput regioisomer analysis-enabled enzyme library screening for peptide ligation reaction. ADE-MRM-MS assays were demonstrated to deliver accurate results that are comparable to conventional liquid chromatography (LC) experiments while providing >100-fold throughput enhancement.

Real-time monitoring of biopharmaceutical reactors is becoming increasingly important as the processes become more complex. During the continuous manufacturing of monoclonal antibodies (mAbs), the desired mAb product is continually created and collected over a 30 day process, where there can be changes in quality over that time. Liquid chromatography (LC) is the workhorse instrumentation capable of measuring mAb concentration as well as quality attributes such as aggregation, charge variants, oxidation, etc. However, traditional offline sampling is too infrequent to fully characterize bioprocesses, and the typical time from sample generation to data analysis and reporting can take weeks. To circumvent these limitations, an automated online sampling multidimensional workflow was developed to enable streamlined measurements of mAb concentration, aggregation, and charge variants. This analytical framework also facilitates automated data export for real-time analysis of up to six bioreactors, including feedback-controlling capability using readily available LC technology. This workflow increases the data points per bioreactor, improving the understanding of each experiment while also reducing the data turnaround time from weeks to hours. Examples of effective real-time analyses of mAb critical quality attributes are illustrated, showing substantial throughput improvements and accurate results while minimizing labor and manual intervention.

The solution-based gram-scale synthesis of complex and highly potent proprotein convertase subtilisin-like/kexin type 9 (PCSK9) inhibitor 1 is presented. Construction of Northern fragment 2 , followed by stepwise installation of Eastern 3 , Southern 4 , and Western 5 fragments, provided macrocyclic precursor 19 . This intermediate was cross-linked via an intramolecular azide-alkyne click reaction, which preceded macrolactamization to afford the core framework of compound 1 . Finally, coupling with poly(ethylene glycol) side-chain-based 6 gave the PCSK9 inhibitor 1 .

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.

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 CO 2 , 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)., (© 2022 Wiley-VCH GmbH.)

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., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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 (scCO 2 ) and deuterated modifiers (CD 3 OD) 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 (CH 3 OH) and its deuterated counterpart (CD 3 OD). 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.

The aim of this study was to evaluate the potential of ultra-high performance supercritical fluid chromatography (UHPSFC) for peptide analysis by comparing its analytical performance to several chromatographic approaches based on reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC) and mixed-mode liquid chromatography. First, the retention behavior of synthetic peptides with 3 to 30 amino acids and different isoelectric points (acid, neutral, and basic) was evaluated. For all the tested conditions (13 peptides in 8 conditions), only 4 results were not exploitable (not retained or not eluted), confirming that all the tested chromatographic conditions can be successfully applied when analyzing a wide range of diverse peptides. Average tailing factor were quite comparable across all chromatographic modes, while the best peak capacity values were obtained under mixed-mode LC conditions. Selectivity for each chromatographic mode was also evaluated for six closely related peptides having minor modifications on their structures. The LC-based chromatographic modes confirmed their superior selectivity over UHPSFC. By contrast, when analyzing short peptides (di- or tripetides), UHPSFC was the only technique allowing to simultaneously separate highly polar and less polar peptides within the same run confirming its unique versatility. In addition, the sensitivity of each chromatographic approach was accessed by for two representative peptides by both UV and MS detection. With UV detection, limit of detection (LOD) values were comparable among the different chromatographic modes, ranging from 0.5 to 2 µg mL -1 . However, major differences were found when employing MS detection (LOD values ranged from 0.05 to 5 µg mL -1 ). The best results were obtained under HILIC conditions, followed by SFC, and finally mixed-mode LC and RPLC modes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

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/CO 2 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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

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 H 2 O and D 2 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., (© 2022 Wiley-VCH GmbH.)

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 ( 1 D) conditions that are combined with MS-friendly RPLC conditions in the second dimension ( 2 D) for two-dimensional liquid chromatography experiments enabling purity analysis and identification of pharmaceutical targets., (© 2022. Merck & Co., Inc., Kenilworth, NJ, USA and its affiliates and Davy Guillarme under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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).

The introduction of molecular complexity in an atom- and step-efficient manner remains an outstanding goal in modern synthetic chemistry. Artificial biosynthetic pathways are uniquely able to address this challenge by using enzymes to carry out multiple synthetic steps simultaneously or in a one-pot sequence 1-3 . Conducting biosynthesis ex vivo further broadens its applicability by avoiding cross-talk with cellular metabolism and enabling the redesign of key biosynthetic pathways through the use of non-natural cofactors and synthetic reagents 4,5 . Here we describe the discovery and construction of an enzymatic cascade to MK-1454, a highly potent stimulator of interferon genes (STING) activator under study as an immuno-oncology therapeutic 6,7 (ClinicalTrials.gov study NCT04220866 ). From two non-natural nucleotide monothiophosphates, MK-1454 is assembled diastereoselectively in a one-pot cascade, in which two thiotriphosphate nucleotides are simultaneously generated biocatalytically, followed by coupling and cyclization catalysed by an engineered animal cyclic guanosine-adenosine synthase (cGAS). For the thiotriphosphate synthesis, three kinase enzymes were engineered to develop a non-natural cofactor recycling system in which one thiotriphosphate serves as a cofactor in its own synthesis. This study demonstrates the substantial capacity that currently exists to use biosynthetic approaches to discover and manufacture complex, non-natural molecules., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

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 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.

Inhibitor cystine knot peptides, derived from venom, have evolved to block ion channel function but are often toxic when dosed at pharmacologically relevant levels in vivo . The article describes the design of analogues of ProTx-II that safely display systemic in vivo blocking of Na v 1.7, resulting in a latency of response to thermal stimuli in rodents. The new designs achieve a better in vivo profile by improving ion channel selectivity and limiting the ability of the peptides to cause mast cell degranulation. The design rationale, structural modeling, in vitro profiles, and rat tail flick outcomes are disclosed and discussed.

The (4 + 3) cycloaddition of 2-trialkylsilyl-4-alkylbutadienes with an N -methyloxidopyridinium ion affords cycloadducts with high regioselectivity and excellent endo selectivity.

Modern supercritical fluid chromatography (SFC) is now a well-established technique, especially in the field of pharmaceutical analysis. We recently demonstrated the transferability and the reproducibility of a SFC-UV method for pharmaceutical impurities by means of an inter-laboratory study. However, as this study involved only one brand of SFC instrumentation (Waters®), the present study extends the purpose to multi-instrumentation evaluation. Specifically, three instrument types, namely Agilent®, Shimadzu®, and Waters®, were included through 21 laboratories (n = 7 for each instrument). First, method transfer was performed to assess the separation quality and to set up the specific instrument parameters of Agilent® and Shimadzu® instruments. Second, the inter-laboratory study was performed following a protocol defined by the sending lab. Analytical results were examined regarding consistencies within- and between-laboratories criteria. Afterwards, the method reproducibility was estimated taking into account variances in replicates, between-days and between-laboratories. Reproducibility variance was larger than that observed during the first study involving only one single type of instrumentation. Indeed, we clearly observed an 'instrument type' effect. Moreover, the reproducibility variance was larger when considering all instruments than each type separately which can be attributed to the variability induced by the instrument configuration. Nevertheless, repeatability and reproducibility variances were found to be similar than those described for LC methods; i.e. reproducibility as %RSD was around 15 %. These results highlighted the robustness and the power of modern analytical SFC technologies to deliver accurate results for pharmaceutical quality control analysis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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 ( 2 D) 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 2 D 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 ( 1 D) separation using a single combination of 2 D stationary phase and elution conditions. The multifactorial retention models were found to be very accurate for both the 1 D and 2 D 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.

The aim of this work was to expand the applicability range of UHPSFC to series of synthetic and commercialized peptides. Initially, a screening of different column chemistries available for UHPSFC analysis was performed, in combination with additives of either basic or acidic nature. The combination of an acidic additive (13 mM TFA) with a basic stationary phase (Torus DEA and 2-PIC) was found to be the best for a series of six synthetic peptides possessing either acidic, neutral or basic isoelectric points. Secondly, methanesulfonic acid (MSA) was evaluated as a potential replacement for TFA. Due to its stronger acidity, MSA gave better performance than TFA at the same concentration level. Furthermore, the use of reduced percentages of MSA, such as 8 mM, yielded similar results to those observed with 15 mM of MSA. The optimized UHPSFC method was, then, used to compare the performance of UHPSFC against RP-UHPLC for peptides with different pI and with increasing peptide chain length. UHPSFC was found to give a slightly better separation of the peptides according to their pI values, in few cases orthogonal to that observed in UHPLC. On the other hand, UHPSFC produced a much better separation of peptides with an increased amino acidic chain compared to UHPLC. Subsequently, UHPSFC-MS was systematically compared to UHPLC-MS using a set of linear and cyclic peptides commercially available. The optimized UHPSFC method was able to generate at least similar, and in some cases even better performance to UHPLC with the advantage of providing complementary information to that given by UHPLC analysis. Finally, the analytical UHPSFC method was transferred to a semipreparative scale using a proprietary cyclic peptide, demonstrating excellent purity and high yield in less than 15 min., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors have no conflict of interests to declare. No funding to declare., (Copyright © 2021. Published by Elsevier B.V.)

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., (Copyright © 2021. Published by Elsevier B.V.)

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 ( 1 D ) and second ( 2 D ) dimensions using LC Simulator (ACD/Labs) software. Retention models for 1 D and 2 D 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 1 D and 2 D 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.

At the forefront of synthetic endeavors in the pharmaceutical industry, including drug discovery and high-throughput screening, timelines are tight and large quantities of pure chemical targets are rarely available. In this regard, the development of novel and increasingly challenging chemistries requires a commensurate level of innovation to develop reliable analytical assays and purification workflows with rapid turnaround that enables accelerated pharmacological evaluation. A small-scale automation platform enabling high-throughput analysis and purification to streamline the selection of candidate leads would be a transformative advance. Herein, we introduce an automation-friendly solid-phase extraction-matrix-assisted laser desorption/ionization (SPE-MALDI) platform applied to the high-throughput purification and analysis of peptide libraries. This advance enabled us to purify peptides from microgram levels in less than a day with results comparable to traditional high-performance liquid chromatography-diode array detection-mass spectrometry (HPLC-DAD-MS)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Seven new arylpyrrole alkaloids ( 1 - 7 ), along with four known compounds, were isolated from an extract of a Dactylia sp. nov. marine sponge, and their structures were elucidated by interpretation of NMR and MS spectroscopic data. Denigrins D-G ( 1 - 4 ) have highly substituted pyrrole or pyrrolone rings in their core structures, while dactylpyrroles A-C ( 5 - 7 ) have tricyclic phenanthrene cores. Due to the proton-deficient nature of these scaffolds, key heteronuclear correlations from 1 H- 15 N HMBC and LR-HSQMBC NMR experiments were used in the structure assignment of denigrin D ( 1 ). Dictyodendrin F ( 8 ), a previously described co-metabolite, inhibited transcription driven by the oncogenic PAX3-FOXO1 fusion gene with an IC 50 value of 13 μM.

Modern pharmaceutical processes can often lead to multicomponent mixtures of closely related species that are difficult to resolve under chromatographic conditions, and even worse in preparative scale settings. Despite recent improvements in column technology and instrumentation, there remains an urgent need for creating innovative approaches that address challenging coelutions of critical pair and poor chromatographic productivity of purification methods. Herein, we overcome these challenges by introducing a simple and practical technique named multifactorial peak crossover (MPC) via computer-assisted chromatographic modeling. The approach outlined here focuses on mapping the separation landscape of pharmaceutical mixtures to quickly identify spaces of peak coelution crossings which enables one to conveniently switch the elution order of target analytes. Diverse examples of MPC diagrams as a function of column temperature, mobile phase gradient or a multifactorial combination in reversed phase and ion exchange chromatography (RPLC and IEC) modes are generated using ACD Laboratories/LC Simulator software and corroborated with experimental data match (overall retention time differences of less than 1%). This powerful MPC technique allows us to gain massive productivity increases (shorter cycle time and higher sample loading) for purification of pharmaceuticals by selectively switching the elution order of target components away from undesired tailing peaks and coelution spaces. MPC chromatography dramatically reduces the time spent developing productive analytical and preparative scale separations. In addition, we illustrate how this new MPC concept can be used to gain substantial improvements of the signal-to-noise ratio, enabling straightforward ppb detection of low-level target components with direct impact in the quantitation of metabolites and potential genotoxic impurities (PGIs). These innovations are of paramount importance in order to facilitate efficient isolation, characterization, and quantitation of drug substances in the development of new medicines.

Baseline separation and analysis of multicomponent mixtures of closely related pharmaceuticals using single column selectivity can often be challenging, requiring the combination of orthogonal stationary and mobile phase methods to monitor all the species and optimize reaction outcomes. In recent years, two-dimensional liquid chromatography (2D-LC) has become a valuable tool for improving peak capacity and selectivity. Though powerful, standard 2D-LC instrumentation and software can often lead to tedious method development and has a requirement for very specific expertise that is poorly suited for a fast-paced industrial environment. In this regard, the introduction of an automated online 2D-LC setup that could screen multiple columns in both dimensions without manual intervention will undeniably serve to streamline column/mobile phase selection and secure the viability of 2D-LC as a mainstay instrument for industrial applications. Herein, we introduce and investigate a multicolumn online 2D-LC approach that simplifies column screening and method development dramatically. This setup incorporates 6-position column selection valve technology whose functionality enables us to combine multiple columns in the first and second dimensions. This strategy in conjunction with diode array detection (DAD) in both dimensions and mass spectrometry (MS) acquisition in the second dimension serves to explore different columns and mobile phases as a framework for screening targeted compounds in multicomponent mixtures without having to perform chromatographic purification. Multiple online heart cutting achiral RPLC - achiral RPLC and achiral RPLC - chiral RPLC coupled to DAD and ESI-MS methods combining several stationary phase selectivity in an automated fashion are successfully applied to the separation and analysis of complex mixtures of drug substances, where in many instances, traditional 1D-ultra-high performance liquid chromatography (UHPLC) fails or delivers sub-optimal results. This automated online multicolumn 2D-LC workflow enables rapid and efficient identification of column/eluent combinations, as well as sample analysis across multiple columns in both dimensions overnight with a single click., Competing Interests: Declaration of competing interest None., (Copyright © 2020. Published by Elsevier B.V.)

The analysis of complex mixtures of closely related species is quickly becoming a bottleneck in the development of new drug substances, reflecting the ever-increasing complexity of both fundamental biology and the therapeutics used to treat disease. Two-dimensional liquid chromatography (2D-LC) is emerging as a powerful tool to achieve substantial improvements in peak capacity and selectivity. However, 2D-LC suffers from several limitations, including the lack of automated multicolumn setups capable of combining multiple columns in both dimensions. Herein, we report an investigation into the development and implementation of a customized online comprehensive multicolumn 2D-LC-DAD-MS setup for screening and method development purposes, as well as analysis of multicomponent biopharmaceutical mixtures. In this study, excellent chromatographic performance in terms of selectivity, peak shape, and reproducibility were achieved by combining reversed-phase (RP), strong cation exchange (SCX), strong anion exchange (SAX), and size exclusion chromatography (SEC) using sub-2-μm columns in the first dimension in conjunction with several 3.0 mm × 50 mm RP columns packed with sub-3-μm fully porous particles in the second dimension. Multiple combinations of separation modes coupled to UV and MS detection are applied to the LC × LC analysis of a protein standard mixture, intended to be representative of protein drug substances. The results reported in this study demonstrate that our automated online multicolumn 2D-LC-DAD-MS workflow can be a powerful tool for comprehensive chromatographic column screening that enables the semi-automated development of 2D-LC methods, offering the ability to streamline full visualization of sample composition for an unknown complex mixture while maximizing chromatographic orthogonality. Graphical Abstract.

The pharmaceutical industry's focus has expanded to include peptide and protein-based therapeutics; however, some analytical challenges have arisen along the way, including the urgent need for fast and robust measurement of the membrane permeability of peptides and small proteins. In this study, a simple and efficient approach that utilizes MALDI-TOF-MS to study peptide and protein permeability through an artificial liposome membrane in conjunction with a differential hydrogen-deuterium exchange (HDX) methodology is described. A non-aqueous (aprotic) matrix was evaluated for use with MALDI sample preparation in order to eliminate undesirable hydrogen-deuterium back-exchange. Peptides and proteins were incubated with liposomes and their penetration into the liposome membrane over time was measured by MALDI-MS. A differential HDX approach was used to distinguish the peptides outside of the liposome from those inside. In this regard, the peptides on the outside of the liposomes were labeled using short exposure to deuterium oxide, while the peptides inside of the liposomes were protected from labeling. Subsequently, the unlabeled versus labeled peak area ratios for peptide and protein samples were compared using MALDI-TOF-MS. In this proof-of-concept study, we developed the Liposome Artificial Membrane Permeability Assay (LAMPA) workflow to study three well-known membrane-active model peptides (melittin, alamethicin, and gramicidin) and two model proteins (aprotinin and ubiquitin). The permeability results obtained from this were corroborated by previously reported data for studied peptides and proteins. The proposed LAMPA by MALDI-HDX-MS can be applied in an ultra-high-throughput manner for studying and rank-ordering membrane permeability of peptides and small proteins., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Accessing hindered amines, particularly primary amines α to a fully substituted carbon center, is synthetically challenging. We report an electrochemical method to access such hindered amines starting from benchtop-stable iminium salts and cyanoheteroarenes. A wide variety of substituted heterocycles (pyridine, pyrimidine, pyrazine, purine, azaindole) can be utilized in the cross-coupling reaction, including those substituted with a halide, trifluoromethyl, ester, amide, or ether group, a heterocycle, or an unprotected alcohol or alkyne. Mechanistic insight based on DFT data, as well as cyclic voltammetry and NMR spectroscopy, suggests that a proton-coupled electron-transfer mechanism is operational as part of a hetero-biradical cross-coupling of α-amino radicals and radicals derived from cyanoheteroarenes.

Chromatographic separation, analysis and characterization of complex highly polar analyte mixtures can often be very challenging using conventional separation approaches. Analysis and purification of hydrophilic compounds have been dominated by liquid chromatography (LC) and ion-exchange chromatography (IC), with sub/supercritical fluid chromatography (SFC) moving toward these new applications beyond traditional chiral separations. However, the low polarity of supercritical carbon dioxide (CO 2 ) has limited the use of SFC for separation and purification in the bioanalytical space, especially at the preparative scale. Reaction mixtures of highly polar species are strongly retained even using polar additives in alcohol modifier/CO 2 based eluents. Herein, we overcome these problems by introducing chaotropic effects in SFC separations using a nontraditional mobile phase mixture consisting of ammonium hydroxide combined with high water concentration in the alcohol modifier and carbon dioxide. The separation mechanism was here elucidated based on extensive IC-CD (IC couple to conductivity detection) analysis of cyclic peptides subjected to the SFC conditions, indicating the in situ formation of a bicarbonate counterion (HCO 3 - ). In contrast to other salts, HCO 3 - was found to play a crucial role acting as a chaotropic agent that disrupts undesired H-bonding interactions, which was demonstrated by size-exclusion chromatography coupled with differential hydrogen-deuterium exchange-mass spectrometry experiments (SEC-HDX-MS). In addition, the use of NH 4 OH in water-rich MeOH modifiers was compared to other commonly used basic additives (diethylamine, triethylamine, and isobutylamine) showing unmatched chromatographic and MS detection performance in terms of peak shape, retention, selectivity, and ionization as well as a completely different selectivity and retention behavior. Moreover, relative to ammonium formate and ammonium acetate in water-rich methanol modifier, the ammonium hydroxide in water additive showed better chromatographic performance with enhanced sensitivity. Further optimization of NH 4 OH and H 2 O levels in conjunction with MeOH/CO 2 served to furnish a generic modifier (0.2% NH 4 OH, 5% H 2 O in MeOH) that enables the widespread transition of SFC to domains that were previously considered out of its scope. This approach is extensively applied to the separation, analysis, and purification of multicomponent reaction mixtures of closely related polar pharmaceuticals using readily available SFC instrumentation. The examples described here cover a broad spectrum of bioanalytical and pharmaceutical applications including analytical and preparative chromatography of organohalogenated species, nucleobases, nucleosides, nucleotides, sulfonamides, and cyclic peptides among other highly polar species.

In recent years, charged aerosol detection (CAD) has become a valuable tool for fast and efficient quantitative chromatographic analysis of drug substances with weak UV absorption. In analytical method development using CAD, the power function settings available in the instrument software are key for linearization of the signal response with respect to analyte concentration. However, the relatively poor understanding of the power function algorithm has limited a more widespread use of CAD for quantitative assays, especially in the late stage of method validation and GMP laboratories. Herein, we present an approach to understand the inner workings of the power function value (PFV), the PFV optimization algorithm, as well as a method to determine the optimum PFV based on the signals acquired at PFV = 1 (default CAD settings). The exponent and the constant in the PFV equation used for modeling follow a trend as a function of PFV. The CAD signal at any PFV was modeled based on the signal acquired at PFV = 1, the modelling was successful for two analytes at different concentration levels on two different CAD detectors of the same model. This method reveals the functionality of the PFV which substantially simplifies the workflow needed to optimize the detector signal. The accuracy between the experimental and theoretical results showed high correlation and always resulted in the same optimum PFV determined by both ways. The approach described in this investigation simplifies the selection of the optimum PFV at which the signal is more linear, the signal-to-noise is higher, and the area reproducibility is better. The power function algorithm elucidated herein enables determination of optimum PFV from minimal experimental output and excellent overall accuracy. This paper provides an approach that includes no data transformation outside the vendor software, a very important requirement to easily validate and report results in a GMP environment., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Manufacturing process development of new drug substances in the pharmaceutical industry combines numerous chemical challenges beyond the efficient synthesis of complex molecules. Optimization of a synthetic route involves the screening of multiple reaction variables with a desired outcome that not only depends on an increased product yield but is also highly influenced by the removal efficacy of residual chemicals and reaction byproducts during the subsequent synthetic route. Consequently, organic chemists must survey a wide array of synthetic variables to develop a highly productive, green, and cost-effective manufacturing process. The time constraints of developing robust quantitative methods prior to each processing step can easily lead to sample analysis becoming a bottleneck in synthetic route development. In this regard, conventional "on demand" analytical method development and optimization approaches, traditionally used for guiding synthetic chemistry efforts, become unsustainable. This Account introduces recent efforts to address the aforementioned challenges through the development and implementation of generic or more universal chromatographic methods that can cover a broad spectrum of targeted compound classes. Such generic methods require significant resolving power to enable baseline resolution of multicomponent mixtures in a single experimental run without additional method customization but must be simple enough to allow for routine use by chemists, chemical engineers and other researchers with little experience in chromatographic method development. These powerful analytical methodologies are often employed to minimize the time spent developing new analytical assays, while also facilitating method transfer to manufacturing facilities and application in regulatory settings. Diverse examples of universal and fit-for-purpose analytical procedures are presented herein, illustrating the power of modern readily available analytical technology for streamlining the development of new drug substances in organic chemistry laboratories across both academic and industrial sectors. With recent advances in analytical instrumentation and column technologies, universal chromatographic methods are quickly becoming a proactive and effective strategy to accelerate the discovery and implementation of new synthetic methodologies, especially but not limited to laboratories where the synthetic process route is undergoing rapid change and optimization. Targets of these generic methods include analysis of organic solvents, acid and basic additives, nucleotide species, palladium scavengers, impurity mapping, enantiopurity, synthetic intermediates, active pharmaceutical ingredients and their counterions, dehalogenation byproducts, and mixtures of organohalogenated pharmaceuticals, among other chemicals used or formed in process chemistry reactions.

The evolution of supercritical fluid chromatography (SFC) instrumentation, improved detection capability, and expanded modifier range has led to extending the reach of SFC to the analysis of a broader spectrum of analytes beyond enantioselective separations. However, preparative SFC has yet to see the same technological revitalization, especially in regards to the purification of highly polar analytes. Enhanced fluidity liquid chromatography (EFLC) has been demonstrated as one of the ways to extend the applicable range of SFC instrumentation to highly polar analytes such as proteins, carbohydrates, and nucleotides. Despite recent applications of EFLC for challenging mixtures of hydrophilic metabolites and analogs, its viability in preparative purification, which is of great importance to the pharmaceutical industry, remains unknown. Herein, multiple chromatographic parameters that are critical to achieve feasible EFLC purification methods were investigated, including system pressure as a function of modifier composition (for several MeOH:H 2 O ratios), effect of diluent injection conditions on peak shape, and optimization of mass load with diluent composition. The usage of 50% acetonitrile or methanol diluents provided the most volumetric loading capacity. In the case of sucrose, leveraging higher analyte solubility in water proved to be more favorable than the volumetric loading capacity of diluents with higher organic content. In fact, an 80 mg injection of sucrose was possible on a 2 cm preparative HILIC column with minimal peak shape degradation. The combined information led to the successful demonstration of EFLC for the preparative separation of sugars using readily available MS-directed SFC instrumentation., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Modern process research and development can often be hampered by the tedious method development required to chromatographically resolve mixtures of chemical species with very similar physical properties. Herein, we describe a simple approach for the development and implementation of an efficient ultra-high performance liquid chromatography (UHPLC) assay that is extensively applied to the separation and analysis of multicomponent reaction mixtures of closely related pharmaceutical intermediates and impurities. Methods are optimized using multi-column and multi-solvent UHPLC screening in conjunction with chromatography simulation software (ACD Labs/LC Simulator). This approach is implemented to enable the separation, identification, mapping and control of impurities formed within the process chemistry optimization of the dimeric catalyst used in the synthesis of new drug substances. The final method utilized a sub-2 μm C18 stationary phase (2.1 mm I.D. × 50 mm length, 1.7 μm particle size ACQUITY UPLC BEH C18) with a non-conventional chaotropic mobile phase buffer (35 mM potassium hexafluorophosphate in 0.1% phosphoric acid/acetonitrile) in order to achieve baseline separation of all reaction components. The chromatographic simulation and modeling strategy served to generate 3D resolution maps with robust separation conditions that match the outcome of subsequent experimental data (overall ΔtR < 0.35%). Our multi-column UHPLC screening with computer-assisted chromatographic modeling is a great addition to the toolbox of synthetic chemists and can be a powerful tool for streamlining process chemistry optimization in organic chemistry laboratories across both academic and industrial sectors.

Supercritical fluid chromatography (SFC) has become the fastest growing analytical tool for chiral and achiral small-molecule pharmaceutical separations. The benefits from savings in cost (as a result of lower solvent and energy consumption), and time have made SFC a proven effective tool for solving many analytical problems for small-molecules over the years. There is, however, a gap in the application of SFC for larger biomolecules, proteins and peptides. There has been a notable increase of protein- and peptide-based drug therapies that contain a higher-order structure important to their efficacy. These studies leverage the use of size exclusion chromatography coupled with hydrogen-deuterium exchange (SEC-HDX) methodology and circular dichroism (CD) spectroscopy to probe global conformational structures of model peptides and proteins following purification by preparative SFC. It was demonstrated that bradykinin and insulin can be used in SFC purification, and moreover, insulin was able to recover its original higher-order structure when compared to pre-purification insulin by three orthogonal techniques: 1) calculated percent alpha-helicity based on CD spectra, 2) alpha-helix - temperature hysteresis analysis by CD and 3) SEC-HDX-MS at different temperatures. However, it was shown that the higher order structures of the other three model proteins used in the study (ubiquitin, cytochrome C, and apomyoglobin) were significantly modified during SFC purification and were unable to re-fold to their original conformations. The present workflow was applied successfully to several peptide therapeutic programs at our comp any and in addition can be applied for small proteins., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Nucleotides are among the most frequently used chemical building blocks in the research, development and manufacture of drug substances. They are composed of three highly polar subunit molecules (a nucleobase, a sugar, and at least one phosphate group), which makes their separation and analysis very challenging by conventional liquid chromatography techniques. Herein, we describe a simple, efficient, and cost-effective ion-exchange chromatography (IEC) method for the separation and purification of over 20 nucleotides. This method combines the use of a Tosoh TSKgel SuperQ-5P W resin in conjunction with a fully aqueous eluent profile (ammonium bicarbonate-based) that allows for a straightforward scale-up transition and convenient drying process with minimal environmental impact. This generic method was optimized using chromatography simulation software (ACD Labs/LC Simulator) and successfully applied to the preparative purification of multicomponent nucleotide mixtures using readily available Fast Protein Liquid Chromatography (FPLC) instrumentation. These IEC method conditions can be effectively applied as the starting point for method development and isolation of other highly polar nucleotide species beyond those investigated in this study., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Within the pharmaceutical industry, the determination of residual solvents by Gas Chromatography Flame Ionization Detection (GC-FID) is a highly utilized analytical test that often employs helium (He) as the carrier gas. However, many do not realize that helium is a non-renewable resource that will eventually become progressively more difficult to source. In recent years, analytical chemists are increasingly adopting hydrogen (H 2 ) in place of helium for routine GC analysis. In this study, a simple and efficient generic/universal GC-FID method using H 2 as the carrier gas has been developed with the capability of baseline resolution of over 30 of the most commonly used solvents in development and manufacturing with a method run time of less than eight minutes. The use of this method for the separation and analysis of solvents within a pharmaceutical manufacturing process is demonstrated with additional method validation data presented using five different diluents as a means to increase flexibility for the chromatographer. Furthermore, it is the recommendation of the authors that the current compendia for residual solvent analysis be updated to allow for hydrogen as a carrier gas. The similarity between He and H 2 observed within this study supports the use of hydrogen as a suitable replacement for helium, and an update of the EU and USP compendia for residual solvent analysis should be made to reflect this., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Supercritical Fluid Chromatography (SFC) has known a strong regain of interest for the last 10 years, especially in the field of pharmaceutical analysis. Besides the development and validation of the SFC method in one individual laboratory, it is also important to demonstrate its applicability and transferability to various laboratories around the world. Therefore, an inter-laboratory study was conducted and published for the first time in SFC, to assess method reproducibility, and evaluate whether this chromatographic technique could become a reference method for quality control (QC) laboratories. This study involved 19 participating laboratories from 4 continents and 9 different countries. It included 5 academic groups, 3 demonstration laboratories at analytical instrument companies, 10 pharmaceutical companies and 1 food company. In the initial analysis of the study results, consistencies within- and between-laboratories were deeply examined. In the subsequent analysis, the method reproducibility was estimated taking into account variances in replicates, between-days and between-laboratories. The results obtained were compared with the literature values for liquid chromatography (LC) in the context of impurities determination. Repeatability and reproducibility variances were found to be similar or better than those described for LC methods, and highlighted the adequacy of the SFC method for QC analyses. The results demonstrated the excellent and robust quantitative performance of SFC. Consequently, this complementary technique is recognized on equal merit to other chromatographic techniques., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Column temperature control is a fundamental component of liquid chromatography experiments. However, it is typically monitored indirectly by tracking the temperature of an adjacent heating element that exchanges heat with the column in a controlled environment. The practice of not directly measuring the column temperature means that uncontrolled contributions of heat, such as frictional heating inside the column, can be overlooked. The present work describes the use of a high-resolution infrared thermal imaging camera to directly measure the column heat map during mobile phase flow. The approach was used to measure the longitudinal temperature gradient formed with three common mobile phases: water, methanol, and acetonitrile, in two 50 mm reversed-phase columns, a 1.7 μm particle-packed column and a polystyrene divinylbenzene monolith. In a close approximation to an adiabatic environment, the temperature gradients (ΔT) observed with the 1.7 μm particle column at a linear velocity of 5.8 mm/s were up to +16.6 and + 12.8 °C above an ambient temperature of 23 °C for water and acetonitrile, respectively. In the case of water, the measured temperature gradient values (ΔT) were within 1% difference of theoretically-calculated values and on average within 10% for acetonitrile. By contrast, the ΔT observed in the monolith was negligible. The elevated temperatures that are generated through friction in sub-2 μm particle columns may be particularly important to consider for the design of experiments that measure structural features of temperature-sensitive analytes, such as biomolecules. While frictional heating is one important application of the thermal imaging approach described, the technique can be used to provide a data-rich profile of heat exchange in numerous experimental configurations, chromatographic or otherwise., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Impurity fate and purge studies are critical in order to establish an effective impurity control strategy for approval of the commercial filing application of new medicines. Reversed phase liquid chromatography-diode array-mass spectrometry (RPLC-DAD-MS) has traditionally been the preferred tool for impurity fate mapping. However, separation of some reaction mixtures by LC can be very problematic requiring combination LC-UV for area % analysis and a different LC-MS method for peak identification. In addition, some synthetic intermediates might be chemically susceptible to the aqueous conditions used in RPLC separations. In this study, the use of supercritical fluid chromatography-photodiode array-electrospray ionization mass spectrometry (SFC-PDA-ESIMS) for fate and purge of two specified impurities in the 1-uridine starting material from the synthesis of a bis-piv 2'keto-uridine, an intermediate in the synthesis of uprifosbuvir, a treatment under investigation for chronic hepatitis C infection. Readily available SFC instrumentation with a Chiralpak IC column (4.6 × 150 mm, 3 μm) and ethanol: carbon dioxide based mobile phase eluent enabled the separation of closely related components from complex reaction mixtures where RLPC failed to deliver optimal chromatographic performance. These results illustrate how SFC combined with PDA and ESI-MS detection can become a powerful tool for direct impurity fate mapping across multiple reaction steps., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Verubecestat is an inhibitor of β-site amyloid precursor protein cleaving enzyme 1 (BACE1) being evaluated in clinical trials for the treatment of Alzheimer's disease. Synthetic route development involves diastereoselective transformations with a need for enantiomeric excess (ee) determination of each intermediate and final active pharmaceutical ingredient (API). The analytical technical package of validated methods relies on enantioselective SFC and RPLC separations using multiple 3 and 5 μm coated polysaccharide-based chiral stationary phases (CSPs) and mobile phases combinations. Evaluation of recently developed chiral columns revealed a single chiral selector (Teicoplanin) bonded to 2.7 μm core-shell particles using H 3 PO 4 in H 2 O/ACN and triethylammonium acetate: methanol based eluents at different isocratic compositions allowed good enatioseparation of all verubecestat intermediates. EE determination of verubecestat is easily performed on NicoShell, another macrocyclic glycopeptide chiral selector bonded to 2.7 μm superficially porous particles. This approach enables fast and reliable enantiopurity analysis of the entire verubecestat synthetic route using only two chiral columns and mobile phases on a conventional HPLC system, simplifying technical package preparation, method validation and transfer to manufacturing facilities., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Volatile amines are among the most frequently used chemicals in organic and pharmaceutical chemistry. Synthetic route optimization often involves the evaluation of several different amines requiring the development and validation of analytical methods for quantitation of residual amine levels. Herein, a simple and fast generic GC-FID method on an Agilent J&W CP-Volamine capillary column (using either He or H 2 as the carrier gas) capable of separating over 25 volatile amines and other basic polar species commonly used in pharmaceutical chemistry workflows is described. This 16min method is successfully applied to the analysis and quantitation of volatile amines in a variety of pharmaceutically-related drugs and synthetic intermediates. Method validation experiments showed excellent analytical performance in linearity, recovery, repeatability, and limit of quantitation and detection. In addition, diverse examples for the application of this method to the simultaneous determination of other amine-related chemicals in reaction mixtures are illustrated, thereby indicating that these GC-FID method conditions can be effectively used as starting point during method development for the analysis of other basic polar species beyond the validated list of amines described in this study., (Copyright © 2017 Elsevier B.V. All rights reserved.)