Peak deconvolution to correctly assess the band broadening of chromatographic columns

Column-Only Band Broadening in a Porous Shell Radially Elongated Pillar Array Column

In the quest for better performing separation media for liquid chromatography, micropillar array columns have received great interest over the past years. While previous research was mainly focused around micropillar array columns (μPACs) filled with cylindrical pillars, this contribution discusses μPACs with rectangular pillars, which, for the first time, have been anodized and hence carry a mesoporous shell. We report on a series of on-chip measurements of the band broadening and flow permeability in a μPAC with very wide radially elongated pillars (3·75 μm) and with an interpillar distance (2 μm) between that of the first (2.5 μm) and second generation (1.25 μm) of cylindrical μPACs. Because of the extreme flow path tortuosity, this type of μPAC can produce very large plate numbers over a short distance. Despite the relatively large interpillar distance, we obtain Hmin = 0.26 μm for a nearly unretained component (phase retention factor, k' ≈ 0.24) and Hmin = 0.79 μm for a retained component with k' ≈ 3. The kinetic performance in terms of separation impedance (Ei = 19) is considerably improved compared to cylindrical pillar μPACs (Ei in range 40-50) and is in excellent agreement with the theoretical value for an open tubular channel with a rectangular cross-section (Ei = 18). This shows that rectangular μPACs can be represented as a parallel bundle of interconnected open-tubular channels.

Application of mechanistic modelling in membrane and fiber chromatography for purification of biotherapeutics - A review

Mechanistic modelling is a simulation tool which has been effectively applied in downstream bioprocessing to model resin chromatography. Membrane and fiber chromatography are newer approaches that offer higher rates of mass transfer and consequently higher flow rates and reduced processing times. This review describes the key considerations in the development of mechanistic models for these unit operations. Mass transfer is less complex than in resin columns, but internal housing volumes can make modelling difficult, particularly for laboratory-scale devices. Flow paths are often non-linear and the dead volume is often a larger fraction of the overall volume, which may require more complex hydrodynamic models to capture residence time distributions accurately. In this respect, the combination of computational fluid dynamics with appropriate protein binding models is emerging as an ideal approach.

On-Chip Comparison of the Performance of First- and Second-Generation Micropillar Array Columns

Because of its dimensions, the recently introduced micropillar array columns are most suited for high-efficiency liquid chromatography separations in proteomics. Unlike the packed bed columns and capillary-based column formats, the micropillar array concept still has significant room to progress in terms of the reduction of its characteristic size (i.e., pillar diameter and interpillar distance) to open the road to even higher-efficiency separations and their applications. We report here on the on-chip comparison between first-generation (Gen 1) and second-generation (Gen 2) micropillar array columns wherein the pillar and interpillar size have been halved. Because of the on-chip measurements, the observed plate heights H represent the fundamental band broadening, devoid of any extra-column band-broadening effects. The observed reduction of H with a factor of 2 around the uopt-velocity and with a factor of 4 in the C-term dominated regime of the van Deemter-curve is in full agreement with the theoretically expected gain. This shows the pillar and interpillar size reduction could be effectuated without affecting the theoretical separation potential of the micropillar arrays. Compared to Gen 1, Gen 2 offers a 4-fold reduction of the required analysis time around the optimal velocity and about a 16-fold reduction in the C-term-dominated range.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Measurement of the molecular diffusion coefficient and the effective longitudinal diffusion under supercritical fluid chromatography conditions in packed bed columns

The improvement of supercritical fluid chromatography (SFC) instrumentation enhanced its reliability and utility over the past decade. The further development of high speed and high resolution separations is however obstructed by the lack of accurate models for axial dispersion in SFC. This work is a first step to tackle this by developing more reliable methods to measure molecular (D_mol) and longitudinal diffusion (D_eff) in SFC, as these affect all aspects of separation efficiency. In the present contribution, we report on an improved method, to enable more flexible, reliable and accurate measurements of D_mol in SFC using commercial instrumentation. A two-column variant of the stopped-flow experiment is proposed as an adapted set-up for measuring the effective longitudinal diffusion coefficient D_eff in SFC-conditions. Using the set-ups for a number of test-compounds, it has been found that D_eff, and the coefficients describing its constituent sub-processes (cf. particle diffusion D_part and surface diffusion γ_sD_s), all vary in a linearly proportional way with the bulk diffusion coefficient D_mol within a high degree of accuracy. It has also been found that D_eff decreases much more sharply with increasing retention factor compared to LC. By applying the effective medium theory, it was found that the relative surface diffusion coefficient γ_sD_s/D_mol decreases strongly with retention factor for the investigated solutes and column, in contrary to what is typically observed in reversed phase liquid chromatography. Results indicate that this might be related to a change in retention behavior of the analytes. Obviously, more analytes and conditions need to be explored to complete this picture and the extend range of applicability of these observations.

Microchromatography integrated with impedance sensor for bioprocess optimization: Experimental and numerical study of column efficiency for evaluation of scalability

In the last decade, there has been a growing interest in developing microfluidic systems as new scale-down models for accelerated and cost-effective biopharmaceutical process development. Nonetheless, the research in this field is still in its infancy and requires further investigation to simplify and accelerate the microfabrication process. In addition, integration of different label-free sensors into the microcolumn systems has utmost importance to minimize result discrepancies during the scale-up process. In this study, we developed a simple, low-cost integrated microcolumn (26 µl). Micromilling technology was employed to define the geometry and shape of microfluidic structures using poly(methylmethacrylate) (PMMA). The design of PMMA microstructure was transferred to polydimethylsiloxane (PDMS), and interdigitated planar microelectrodes (IDE) were integrated into the system. To evaluate the scalability of the developed microcolumn column, column performance was assessed and compared with a conventional 1-ml prepacked column. Computational Fluid Dynamics (CFD) studies were performed for both columns to understand the differences between theoretical and experimental results regarding retention time and peak broadening. Despite obtaining an acceptable asymmetric factor for the microcolumn (1.03 ± 0.02), the reduced plate height value was still higher than the recommended range with the value of 4.14 ± 0.18. Nevertheless, the consistency and significant improvement of microcolumn efficiency compared to previous studies provide the possibility of developing robust simulation tools for transferring acquired experimental data for larger-scale units.

Detailed numerical analysis of the effect of radial column heterogeneities on peak parking experiments with slowly diffusing analytes

The origin of the peak skewness that can be observed when applying the deconvolution method to isolate the diffusion process from the flow processes for peak parking experiments conducted under conditions of slow radial equilibration and strong trans-column velocity gradients was investigated. Numerical simulations were carried out for a variety of trans-column velocity profiles and a broad range of experimental conditions and system parameters were investigated. Results show that, under the aforementioned conditions, the traditionally employed variance subtraction method displays a consistent error which follows the dynamics of the diffusive relaxation during both the peak parking and the flow steps. It is also found that, under the same conditions, the peak deconvolution method is bound to produce deconvoluted "parking-only" peaks that are strongly asymmetric, despite the perfectly symmetric nature of the pure diffusion process marking this parking step. It is shown that this asymmetry is acquired during the flow step following the parking stop. During this step, parked and non-parked peaks are deformed in different ways, despite being subjected to the same trans-column velocity profile. This different deformation cannot be filtered away with the deconvolution or the variance subtraction method, hence introducing an error. Solutions to alleviate the peak skewness and the variance error consist of parking the peak close to the inlet or the outlet or exiting the parked peak through the column inlet (flow reversal method). Under the considered conditions, these approaches could reduce the error on the measured effective diffusion coefficient up to 87%. Carrying out the variance subtraction or the deconvolution process with a peak that has also been parked for a substantially long parking time instead of using a "no-parking" peak as is customary done, is another option to counter the effect.

Fundamental Properties of Packing Materials for Liquid Chromatography

The high performance of chemically-modified silica gel packing materials is based on the utilization of pure silica gels. Earlier silica gels used to be made from inorganic silica; however, nowadays, silica gels are made from organic silanes. The surface smoothness and lack of trace metals of new silica gels permits easy surface modifications (chemical reactions) and improves the reproducibility and stability. Sharpening peak symmetry is based on developing better surface modification methods (silylation). Typical examples can be found in the chromatography of amitriptyline for silanol testing and that of quinizarin for trace metal testing. These test compounds were selected and demonstrated sensitive results in the measurement of trace amounts of either silanol or trace metals. Here, we demonstrate the three-dimensional model chemical structures of bonded-phase silica gels with surface electron density for easy understanding of the molecular interaction sites with analytes. Furthermore, a quantitative explanation of hydrophilic and hydrophobic liquid chromatographies was provided. The synthesis methods of superficially porous silica gels and their modified products were introduced.

Separations at the Speed of Sensors

The virtue of chemical sensors is speed and analyte specificity. The response time to generate an analytical signal typically varies from ∼1 to 20 s, and they are generally limited to a single analyte. Chemical sensors are significantly affected by multiple interferents, matrix effects, temperature, and can vary widely in sensitivity depending on the sensor format. Separation-based analyses remove matrix effects and interferents and are compatible with multiple analytes. However, the speed of such analyses has not been commensurate with traditional sensors until now. Beds of very small size with optimal geometry, containing core-shell particles of judicious immobilized selectors, can be used in an ultrahigh-flow regime, thereby providing subsecond separations of up to 10 analytes. Short polyether ether ketone lined stainless steel columns of various geometries were evaluated to determine the optimal bed geometry for subsecond analysis. Coupling these approaches provides subsecond-based detection and quantitation of multiple chiral and achiral species, including nucleotides, plant hormones, acids, amino acid derivatives, and sedatives among a variety of other compounds. The subsecond separations were reproducible with 0.9% RSD on retention times and showed consistent performance with 0.9% RSD on reduced plate height in van Deemter curves. A new powerful signal processing algorithm is proposed that can further enhance separation outputs and optical spectra without altering band areas on more complex separations such as 10 peaks under a second.