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High-throughput drug discovery on the microgram scale is now common, making analyte quantitation without molecule-specific calibration imperative. The charged aerosol detector (CAD) was invented to be a next-generation universal liquid chromatography (LC) detector with excellent response universality for nonvolatile analytes as well as sensitivity for nonchromophoric compounds. Although the CAD is a mass flow-sensitive detector, its response to mass is inherently nonlinear, which challenges traditional quantitation. In CAD software, there is a "power function value" ( p ) setting that can be used to linearize the signal through digital signal processing. The exact workings of this power function value algorithm remain unknown; however, its optimization is a crucial aspect of analytical method development for LC-CAD. Herein, we developed a theoretical relationship that can be used to predict the chromatogram (plus peak area, width, and height) at any p if the data are collected at p = 1. This model was validated using a diverse dataset comprising 1440 measurements including peak heights, areas, and widths. Predicted areas had an average error of less than 2% showing excellent agreement between calculated and experimental results. An open-access automated code is tested and provided, which predicts the power function value that produces the most linear response. It is vital to note that optimizing the power function value affects peaks of different heights disproportionately. Low-level impurities were shown to be minimized and eventually eliminated by increasing the power function value. This model provides an easy-to-implement tool (MATLAB or Excel) that assists in choosing the optimal p for each LC-CAD method, increasing the speed of method development and improving the accuracy of quantitative workflows.

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.

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.

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).

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.

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.

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.

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.

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.

Previously, we described a novel method for cladding elemental carbon onto the surface of catalytically activated silica by a chemical vapor deposition (CVD) method using hexane as the carbon source and its use as a substitute for carbon-clad zirconia.1,2 In that method, we showed that very close to exactly one uniform monolayer of Al (III) was deposited on the silica by a process analogous to precipitation from homogeneous solution in order to preclude pore blockage. The purpose of the Al(III) monolayer is to activate the surface for subsequent CVD of carbon. In this work, we present an improved procedure for preparing the carbon-clad silica (denoted CCSi) phases along with a new column packing process. The new method yields CCSi phases having better efficiency, peak symmetry, and higher retentivity compared to carbon-clad zirconia. The enhancements were achieved by modifying the original procedure in three ways: First, the kinetics of the deposition of Al(III) were more stringently controlled. Second, the CVD chamber was flushed with a mixture of hydrogen and nitrogen gas during the carbon cladding process to minimize generation of polar sites by oxygen incorporation. Third, the fine particles generated during the CVD process were exhaustively removed by flotation in an appropriate solvent.