CIUSuite 3: Next-Generation CCS Calibration and Automated Data Analysis Tools for Gas-Phase Protein Unfolding Data.

Ion mobility-mass spectrometry (IM-MS) has become a technology deployed across a wide range of structural biology applications despite the challenges in characterizing closely related protein structures. Collision-induced unfolding (CIU) has emerged as a valuable technique for distinguishing closely related, iso-cross-sectional protein and protein complex ions through their distinct unfolding pathways in the gas phase. With the speed and sensitivity of CIU analyses, there has been a rapid growth of CIU-based assays, especially regarding biomolecular targets that remain challenging to assess and characterize with other structural biology tools.

Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis.

Introduction: The pharmaceutical industry continues to expand its search for innovative biotherapeutics. The comprehensive characterization of such therapeutics requires many analytical techniques to fully evaluate critical quality attributes, making analysis a bottleneck in discovery and development timelines. While thorough characterization is crucial for ensuring the safety and efficacy of biotherapeutics, there is a need to further streamline analytical characterization and expedite the overall timeline from discovery to market.

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.

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers.

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker.

High-Throughput Capillary Liquid Chromatography Using a Droplet Injection and Application to Reaction Screening.

The cycle time of a standard liquid chromatography (LC) system is the sum of the time for the chromatographic run and the autosampler injection sequence. Although LC separation times in the 1-10 s range have been demonstrated, injection sequences are commonly >15 s, limiting throughput possible with LC separations. Further, such separations are performed on relatively large bore columns requiring flow rates of ≥5 mL/min, thus generating large volumes of mobile phase waste when used for large scale screening and increasing the difficulty in interfacing to mass spectrometry.

High-Throughput Liquid Chromatographic Analysis Using a Segmented Flow Injector with a 1 s Cycle Time.

High-throughput screening (HTS) workflows are revolutionizing many fields, including drug discovery, reaction discovery and optimization, diagnostics, sensing, and enzyme engineering. Liquid chromatography (LC) is commonly deployed during HTS to reduce matrix effects, distinguish isomers, and preconcentrate prior to detection, but LC separation time often limits throughput. Although subsecond LC separations have been demonstrated, they are rarely utilized during HTS due to limitations associated with the speed of common autosamplers.

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

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.

Measurement and modelling of the intra-particle diffusion and b-term in reversed-phase liquid chromatography.

In an ongoing effort to better understand the underlying mechanisms of band broadening in particle-packed reversed-phase liquid chromatography columns, new models for intra-particle diffusion, representing an adsorption- and partition-type retention behavior, are proposed. These models assume the mesoporous zone inside the particles is subdivided in four distinct regions: a fraction f filled with bulk mobile phase, a fraction f enriched in pure organic modifier extending outside the stationary phase layer, a fraction f comprising the liquid surrounding the alkyl chains and a fraction f consisting of the stationary phase alkyl chains. Intra-particle diffusion is calculated as a residence time weighted average of the diffusion in these different regions.

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.

Experimental investigation of the retention factor dependency of eddy dispersion in packed bed columns and relation to knox's empirical model parameters.

We report on a systematic and comprehensive (0.7 ≤ k'' ≤ 122) experimental study of the effect of the zone retention factor k'' on eddy dispersion (h) in packed bed columns for liquid chromatography. The values for h are obtained by subtracting rigorously estimated contributions to the total plate height from longitudinal diffusion (h) and the mobile (h) and stationary zone (h) mass transfer resistances.