Publications by authors named "Imad A Haidar Ahmad"

Background: The need for stationary phases with unique selectivity in reversed-phase liquid chromatography has been of utmost importance to chromatographers for advancing the analysis of complex samples. Macrocyclic glycopeptide based stationary phases have been widely used for chiral separations with different chromatographic modes such as normal phase, reversed phase, and supercritical fluid chromatography. Given the multimodal retention mechanisms namely π-π complex interaction, hydrogen bonding, dipole-dipole interaction, and strong Coulombic interactions by which analytes are separated using the macrocyclic glycopeptides, these stationary phases are expected to provide novel selectivity when used under the reversed phase for achiral separations.

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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.

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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.

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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.

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The development of liquid chromatography UV and mass spectrometry (LC-UV-MS) assays in pharmaceutical analysis is pivotal to improve quality control by providing critical information about drug purity, stability, and presence and identity of byproducts and impurities. Analytical method development of these assays is time-consuming, which often causes it to become a bottle neck in drug development and poses a challenge for process chemists to quickly improve the chemistry. In this study, a systematic and efficient workflow was designed to develop purity assay and purification methods for a wide range of compounds including peptides, proteins, and small molecules with MS-compatible mobile phases (MP) by using automated LC screening instrumentation and in silico modeling tools.

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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.

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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 , 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.

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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) and deuterated modifiers (CDOD) in sub/supercritical fluid chromatography (SFC) is herein introduced.

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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 based eluents enabling rapid identification of suitable enantioseparation conditions for accelerated purification of pharmaceutical targets.

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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.

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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.

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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 ( D-UV); 2) automated peak trapping-enrichment and buffer removal achieved through a sequence of H O and D O washes using an independent pump setup; and 3) a second dimension separation ( 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.

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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.

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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 (D) separations involving variables including gradient time, temperature, organic modifier blending, and buffer concentration using LC simulator (ACD/Labs) software.

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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.

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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.

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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.

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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.

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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.

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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.

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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) has limited the use of SFC for separation and purification in the bioanalytical space, especially at the preparative scale.

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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.

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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.

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Article Synopsis
  • Modern process research faces challenges due to complex method development required for chromatographic separation of closely related chemical mixtures.
  • A new approach utilizing ultra-high performance liquid chromatography (UHPLC) is introduced for efficiently separating and analyzing multicomponent pharmaceutical reaction mixtures.
  • The method incorporates multi-column screening and chromatography simulation software, resulting in effective strategies for identifying and controlling impurities in drug synthesis processes.
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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.

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