Electrosynthesis of iminophosphoranes and applications in nickel catalysis

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(sp2)-C(sp3) and C(sp2)-C(sp2) couplings, an electrochemically driven C-N cross-coupling, and a photochemical arylative C(sp3)-H functionalization. In some cases, these new ligands provide improved performance over commonly used sp2-N-based ligands (e.g. 4,4'-di-tert-butyl-2,2'-bipyridine).

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.

Two-Dimensional SEC-SEC-UV-MALS-dRI Workflow for Streamlined Analysis and Characterization of Biopharmaceuticals

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.

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.

Accelerating Pharmaceutical Process Development with an Acoustic Droplet Ejection-Multiple Reaction Monitoring-Mass Spectrometry Workflow

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.

Automated Online-Sampling Multidimensional Liquid Chromatography with Feedback-Control Capability as a Framework for Real-Time Monitoring of mAb Critical Quality Attributes in Multiple Bioreactors

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.

Synthesis of a Complex and Highly Potent PCSK9 Inhibitor

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.

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.

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

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

Nonlinear Predictive Modelling Enables In Silico Optimization of Chromatographic Methods for Complex Stationary Phase‑Analyte Interactions

The development of robust analytical assays for separation and analysis of complex multicomponent mixtures can often be challenging, reflecting the increased complexity of new medicine and vaccine processes. In silico liquid chromatography (LC) method development strategies for small molecules have reached a mature stage across the pharmaceutical industry. However, a straightforward approach for large molecules remains elusive because of conformational changes that can often influence chromatographic retention. Nonetheless, an excellent correlation between experimental and predicted retention time is possible by deploying the correct regression retention models in terms of ln k vs. %B and ln k vs. 1/T (ΔtR < 0.1%). Excellent outcomes generated through in silico chromatographic method development of large molecules using different chaotropic and denaturing mobile phases are illustrated. Linear and nonlinear (polynomial regression) retention models using readily available software were deployed as a function of several chromatographic parameters (gradient slope and column temperature) for a variety of proteins (12–670 kDa) and peptides.

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

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

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.

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).

Development of ProTx-II Analogues as Highly Selective Peptide Blockers of Nav1.7 for the Treatment of Pain

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_v1.7, 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.

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.

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

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

Endo Selectivity in the (4 + 3) Cycloaddition of Oxidopyridinium Ions

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

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.

Interlaboratory study of a supercritical fluid chromatography method for the determination of pharmaceutical impurities: Evaluation of multi-systems reproducibility

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.

Expanding the range of sub/supercritical fluid chromatography: Advantageous use of methanesulfonic acid in water-rich modifiers for peptide analysis

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.

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

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

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

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

Ultra-high-throughput SPE-MALDI workflow: Blueprint for efficient purification and screening of peptide libraries

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).

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

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

Denigrins and Dactylpyrroles, Arylpyrrole Alkaloids from a Dactylia sp. Marine Sponge

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 ¹H-¹⁵N 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 IC₅₀ value of 13 μM.

Introducing Multifactorial Peak Crossover in Analytical and Preparative Chromatography via Computer-Assisted Modeling

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.

Liposome Artificial Membrane Permeability Assay by MALDI-hydrogen-deuterium exchange mass spectrometry for peptides and small proteins

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.

Electrochemical Synthesis of Hindered Primary and Secondary Amines via Proton-Coupled Electron Transfer

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.

Chaotropic Effects in Sub/Supercritical Fluid Chromatography via Ammonium Hydroxide in Water-Rich Modifiers: Enabling Separation of Peptides and Highly Polar Pharmaceuticals at the Preparative Scale

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 (CO₂) 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/CO₂ 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 (HCO₃^-). In contrast to other salts, HCO₃^- 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 NH₄OH 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 NH₄OH and H₂O levels in conjunction with MeOH/CO₂ served to furnish a generic modifier (0.2% NH₄OH, 5% H₂O 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.

The Emergence of Universal Chromatographic Methods in the Research and Development of New Drug Substances

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.

Revealing the inner workings of the power function algorithm in Charged Aerosol Detection: A simple and effective approach to optimizing power function value for quantitative analysis

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.

Enhanced fluidity liquid chromatography: A guide to scaling up from analytical to preparative separations

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:H₂O 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.

Multi-column ultra-high performance liquid chromatography screening with chaotropic agents and computer-assisted separation modeling enables process development of new drug substances

Streamlined workflow for method development and optimization.

Generic anion-exchange chromatography method for analytical and preparative separation of nucleotides in the development and manufacture of drug substances

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.