For argument’s sake, I will forward two 80:20 observations that apply to chromatography:

80% of published applications are for research and development (R&D) studies, and 20% are for routine applications

80% of all chromatographs sold are for routine work, and 20% go to the R&D labs.

While not surprising, it means that chromatographers often ignore issues that are critical in routine, industrial settings that should see more of our light. So, think about it: Most chromatographs are tasked on day one with a specific analysis and, 20 years later, their final analysis will be the same as the first.

Deploying a chromatograph in a quality control (QC) or process setting is critical to many complex streams in that it provides detailed information on the composition of a huge array of mixtures and provides the means of integrating compositional control strategies in the plant. Day-to-day and instrument-to-instrument variability will frustrate data analysis. Computer-enabled technology can be applied to mitigate the impact of aging instruments and instrument differences, leading to a more robust, lower-maintenance world for industrial chromatographs.

The key issue is to control retention time drift. Because peak retention on the column has some variability, this shifting increases the likelihood of misidentifying a peak and, ultimately, risks misreporting a component’s concentration. Chromatographic retention time drift from run-to-run is always present, but usually is not a significant source of variability. Over time, however, any retention drift amplifies the risk of an error in peak identification, which can lead, in turn, to mistakes in peak tables or in evaluating the overall distribution. Software control of retention time drift is a generic solution to this problem and addressing retention time variation simplifies ownership of a chromatograph by making the data consistent from one month to the next, even one instrument to the next.

In 1965, Kováts described how you can use peaks that are easily identified as markers to calculate relative retention times of neighboring peaks (1). In the late 1990s, groups worked to address the problem of retention time variability by borrowing a multivariate technology that had been applied to voice recognition; one example is correlation optimized warping (COW) described by Nielsen (2). Software, both commercial and freeware, has been available for these approaches since the early 2000s. My team has employed both techniques, separately and in combination, for two decades or so, and has used alignment technology to manage a variety of routine and complex applications, including clinical analysis for the Centers for Disease Control (CDC), systems for economic fraud investigations for the U.S. Food and Drug Administration (FDA), and process hydrocarbon evaluations in refineries and chemical plants.

The traditional way of handling this situation is to rerun the standard and accept new time positions for the peaks. This approach gives a very short-term context and, by forcing frequent recalibrations, lowers the number of samples that can be processed. Hands-on recalibration makes the system more unreliable online, where it is harder to attend to these changes. We often relegate this type of analysis to a supervised laboratory rather than placing it in a less-supervised position near the sampling point, where the feedback would be timely.

But what if we could rely on retention times not changing? This is an example of where chemometric alignment technology should be used. For software alignment to work, one chromatogram must be previously chosen to be the alignment standard; the algorithm then adjusts the peak positions in all the other traces to match that standard as closely as possible. COW-based alignment does not require the alignment standard to be run close to the analysis date, nor does it even need to be run on the same chromatograph. In practice, alignment keeps the peaks in place for a significantly longer time and reduces the work necessary to keep the system calibrated.

The idea that a small amount of software can be added to a chromatographic data system and have that addition open a true plug-and-play capability for the instrument and application is very powerful. Ostensibly, a company could keep a cold spare chromatograph in inventory. When a process or laboratory unit goes down for any reason, the storage unit would be placed online and have its data be completely comparable to all previous runs on its very first injection, possibly without ever performing a traditional calibration. Alignment can also apply this procedure to the historical chromatographic data assembly, resulting in a consistent database ready to be mined.

This conclusion also holds for situations where the column and the method conditions are similar. But if this is the case, the ability to perform more complex chromatographic evaluations in a fully automated manner is achieved.

(2) N-P. V. Nielsen, J.M. Carstensen, and J. Smedsgaard, 

Articles

Columns

Computer-enabled technology approaches can mitigate the impact of aging instruments and instrument differences—leading to more robust, lower-maintenance analysis in industrial settings.

Controlling Retention Time Drift in Industrial Chromatography Settings

This contribution is a continuation of Part IX of this series. In that article, the fundamentals of light scattering as applied to SEC was introduced, including the origin and significance of pertinent equations related to the light scattering of macromolecules. In the present contribution, a summary of commercially available light scattering instrumentation is given, with emphasis on new detector technology. Owing to the complexity of data analysis and the many equations involved with light scattering measurements, a glossary of principal symbols and a table of relevant relationships are presented.

This review is a continuation of Part IX (1), in which the theory of light scattering is given, including pertinent equations and data analysis. The following contribution is a summary of commercially available light scattering (LS) detection systems for size-exclusion chromatography (SEC). Information was obtained, for the most part, from current web sites and discussions with manufacturers as of May 2020. Please note that the author does not endorse any specific instrument.

In addition to detector sensitivity and noise specifications, selecting a light scattering instrument depends on many other factors, including software features and technical support. Furthermore, certain instruments now include dynamic light scattering capability for characterizing aggregates and particulates, which will be the subject of Part XI of this series.

Light scattering detectors for SEC are currently available from Agilent Technologies, Brookhaven Instruments, Malvern Panalytical, Postnova Analytics, Tosoh Bioscience, and Wyatt Technology Corporation. The low-angle capabilities of Malvern’s low angle light scattering/right angle light scattering (LALS/RALS) (7°/90°) and Agilent’s dual-angle detector (15°/90°) use collimated annulus optics for low-angle measurements and photodiodes for right-angle detection. Moreover, Agilent’s instrument utilizes fiber optics to transmit scattering signals to the sensor. Other multiangle instruments employ an array of photodiodes that surround the flow cell, placed at specified angles for detecting scattered light, with the exception of Brookhaven Instruments that employs a charge-coupled device (CCD) for detection.

The apparent trend among some companies is to maximize the number detection angles for improved accuracy and precision. For example, Wyatt Technology, Malvern Panalytical, and Postnova Analytics sell instruments that have 18, 20, and 21 angles of measurement, respectively.

For most instruments, the low-molecular-weight limit ranges from about 200 to 103 g/mol. By reason of equation 7c from Part IX, the lower limit can be adjusted by increasing injection concentration. It is important to note, that when measuring the low-molecular tail of a polydisperse sample, realistic molecular-weight detection limits greatly exceed the above range. The lower radius-of-gyration limit appears to be about 10 nm, except, for example, Tosoh Bioscience LenS3 (see following section) and Postnova multiple angle light scattering (MALS) detectors, whose lower limits are approximately 5 and 8 nm, respectively, using typical injection concentrations. Here the lower limit of angular dissymmetry depends primarily on the sensitivity and signal/noise of the instrument.

It should be stressed that lower molecular-weight and radius-of-gyration limits depend, among other attributes, on instrument design, intensity and wavelength of the incident beam, scattering volume, and photocell sensitivity. Specifications are also based on such factors as the specific refractive index of the sample, injection amount, signal-to-noise ratio of the light scattering and concentration detectors, baseline drift, peak broadening from columns and detector cell volume, and other chromatographic conditions.

It is of interest to note that a radius-of-gyration limit of 10 nm corresponds to 105 g/mol for linear, random-chain polymers. For polymers that are smaller than 10 nm, viscometric detectors can be used, provided that universal calibration is valid, a topic that will be covered in Part XII of this series.

Tosoh Bioscience has recently introduced a multiangle instrument (LenS3 MALS) that is capable of measuring radii of gyration well below 10 nm and molecular weights less than 500 using typical injection concentrations. This newly designed instrument has a conically shaped flow cell (referred to as a chamber), composed of blackened poly(ether ketone) to absorb stray scattered light. It also is equipped with a green laser-diode (505 nm), rather than longer wavelength diodes (635 to 680 nm), typical in some other detectors, with the exception, for example, of Postnova Analytics’s 532-nm light source. Because of the 4th-power dependency on wavelength, the intensity of scattered light at 505 nm, as compared to 635–680 nm, is increased by a factor of 2.3–3.0, representing a significant increase in sensitivity.

The cell design and optical pathway of the LenS3 MALS instrument are illustrated in Figures 5 and 6, respectively. (Figure designations are continued from Part IX.) Eluent enters from the bottom of the flow chamber, splits into two pathways, which are then combined before exiting. For increased sensitivity, the unit is constructed such that nearly the entire cell volume or path length acts as the scattering volume. This is accomplished by passing the incident beam through the center of the cell, allowing forward scattering to be measured at 10

 (low-angle LS or LALS) and back scattering at 170

 (high-angle LS or HALS); these supplementary angles are close to the theoretical limits of 0

, contributing to greater radius-of-gyration sensitivity. In addition, scattered light intensity is also measured at 90

The high sensitivity and low baseline noise are demonstrated by the analysis of a mixture of styrene oligomers in tetrahydrofuran, ranging from dimer to nonamer. These data, given in Table I, show that the instrument is capable of measuring the molecular weight of styrene oligomers, as low as 260 g/mol for the dimer with an error of −2% when compared to the predicted value. Note that the same specific refractive index, 0.170 mL/g, was applied to all oligomers, which may have contributed to the progressively increasing error. The total mass of sample injected was only 0.43 mg of which approximately 30 μg was attributed to the dimer.

The LenS3 MALS instrument uses angular dissymmetry, rather than Zimm’s method, to calculate the radius of gyration. With this approach, the particle scattering function is represented as a ratio of scattering intensities,

° is the scattering intensity taken at 10°. Furthermore, an instrument normalization factor, 

, is employed that corrects for scattering volume, detector sensitivities, and distances from the scattering volume to the detector. Thus, for each elution volume increment, three particle scattering functions are generated:

With this procedure, the particle scattering function (equation 9) can be expressed as:

which is referred to as the Guinier relationship (15). Since 

 = 1, and the initial slope (at the intercept) is –

An example of this angular dissymmetry approach is given in Figure 7, in which a broad polystyrene standard (NIST SRM 706a) was analyzed by the LenS3 MALS detector, courtesy of Tosoh Bioscience. Owing to a slight amount of curvature, a quadratic equation (

 = 27 nm, in agreement with the literature value. Owing to the low noise level and high sensitivity of the instrument, only three angles are required for radius-of-gyration and molecular weight measurements.

Table II shows preliminary molecular weight and radius-of-gyration data of a series of nearly monodisperse polystyrene standards, adapted from data supplied by Tosoh Bioscience. Radii of gyration were in agreement with literature data obtained from small-angle 

-ray scattering, whose authors used similar lots of polystyrene standards dissolved in toluene (2). These initial results were well below the established limit of 10 nm. As previously noted, detection lim- its depend upon many factors that can contribute to the signal-to-noise ratio (S/N) of both the light scattering instrument and concentration detector, such as baseline noise and drift, column efficiency, injection amount, and specific refractive index of the sample.

Light scattering is the ideal detector for SEC, because it provides molecular weight and radius-of-gyration distributions in addition to corresponding statistical averages without column calibration. With this detector, the only information that is required is the specific refractive index of the polymer and the refractive index of the mobile phase.

By using low injection concentrations, the Rayleigh equation is reduced from three (

), greatly facilitating data analysis. Moreover, if low-angle measurements are used, molecular weight can be determined directly without resorting to graphical analysis, however, molecular size information is lost.

To increase the reliability of molecular weight and radius-of-gyration measurements, several instrument companies have opted to maximize the number of photodiodes that surround the flow cell; for example, Wyatt Technology, Malvern Panalytical, and Postnova Analytics have instruments of 18, 20, and 21 angles, respectively. Of late, Postnova Analytics and Tosoh Bioscience have instruments with green- rather than red-laser diodes, resulting in increased sensitivity. Furthermore, Tosoh Bioscience’s instrument consists of a newly designed flow cell and optical system that can mea- sure the radii of gyration as low as about 2 nm under ideal condition. With normal injection amounts, the radius-of-gyration limit is approximately 5 nm, and the molecular weight limit is below 500 g/mol for polystyrene.

For the reader’s benefit, a glossary of principal symbols and a summary of relevant equations and their significance are given, respectively, in Tables III and IV.

Parts XI and XII of "Chromatography Fundamentals" will be devoted to online dynamic light scattering and viscometric detectors, respectively.

The author gratefully acknowledges Cara Tomasek, David Gillespie, and Sébastien Rouzeau, all from Tosoh Bioscience, for their insightful discussions on light scattering and for providing figures and preliminary data on the LenS3 MALS instrument.

LenS is a registered trademark of Tosoh Bioscience LLC.

EcoSEC and TSKgel are registered trademarks of Tosoh Corporation.

(2) F. Abe, Y. Fumiaki, T. Yoshizaki, and H. Yamakawa, 

 is with Analytical Chemistry Consultants, Ltd., in Wilmington, Delaware. Direct correspondence to: 

Peer-Reviewed Article

This exploration into commercially available light scattering detection systems for size-exclusion chromatography (SEC) emphasizes new technologies and will help users understand the options.

Chromatography Fundamentals, Part X: Light Scattering Detection Systems for Size-Exclusion Chromatography

Biologically derived therapeutics, such as monoclonal antibodies (mAbs), are playing an increasingly important role in revolutionizing modern medicine for treating cancer and many autoimmune disorders. They have significantly improved health care outcomes for patients because of their superior target specificity. Because the function of the drug is impacted via multiple pathways and perturbations at various levels of the protein architecture, a detailed study of functional assessment by using orthogonal tools has become a necessary part of their characterization. In the case of biosimilars, demonstration of biological comparability to the originator is an essential component of the comparability package that the manufacturer submits to the regulatory authorities. In this article, we present many of the various tools that are routinely used for performing such functional characterization of biotherapeutic products. Traditional cell-based approaches include measurement of the antibody-dependant cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP). More recently, approaches based on ligand binding, including fluorescence-activated cell sorting (FACS), surface plasmon resonance (SPR), and biolayer interferometry (BLI) are commonly used as well. Current understanding of the role these approaches can play in a functional assessment has been elucidated.

Therapeutic biologics are becoming a critical and significant component of drug discovery pipelines in the pharmaceutical industry. The utility of biologic drugs for treating unmet medical needs is being expanded beyond oncology and immunology into other therapeutic areas, including cardiovascular and metabolic diseases (1). Drug disposition of biotherapeutics is vastly different from small molecules (2) and therefore, assessment of their safety and efficacy is critical for clinical development. Determining the safety of biotherapeutics often involves evaluating multiple factors, including those related to the product, patient, and treatment (3,4). Another trend is the rise of biosimilars, driven by the societal needs of affordable and accessible biotherapeutics. This has further necessitated the need for a meticulous and rigorous risk–benefit analysis of the biologics, involving establishing comparability of biosimilars. There are instances where process and formulation changes have been introduced to ensure similar quality, safety, and efficacy in line with the expectations, and a slew of guidelines have been issued by the regulatory authorities in this regard (2,5).

Several researchers have reported on development of platform methods or approaches for demonstrating analytical comparability with the reference product. Characterization of therapeutic monoclonal antibodies (mAbs) involves using a wide range of analytical techniques, along with ligand-binding and cell-based potency assays (6). Because publications on analytical comparability are commonplace, those on functional comparability are limited to determining either binding affinity to the receptors or the potency (depending on the mechanism of action) of the biosimilar on the relevant cell lines. Thus, considering the complexity of the therapeutic drug and the significant possibility that the function of the drug might be impacted via multiple pathways at various levels of the protein architecture, assessment of functional comparability is as important as analytical comparability.

Each functional assay has its pros and cons and hence just like in the case of analytical comparability, a platform of complementary assays is utilized. Table I summarizes the advantages and disadvantages of the most commonly used functional assays.

Design of bioassays for mAbs is driven by a physiological mechanism of action (MOA). Bioassays are always unique for each therapeutic, unlike other analytical techniques, and a well-designed functional assessment can precisely capture the biological activity of the mAb.

Ligand-Binding Assays (In Vitro Potency Assay) 

Protein–protein interactions play a major role in the formation of protein complexes, which is the basis of various biological processes. The quantification of ligand binding to specific receptors is the key for drug development research, specifically for determining biological potency. The important aspects of ligand–receptor binding interactions include binding affinity and kinetics, thermodynamics, and ligand efficiency (7). Every step of ligand–target interactions can be studied by multiple binding assays.

Fluorescence-activated cell sorting (FACS) is the adopted method used to obtain a high purity sample of the product of interest. It allows purification of individual cells based on size, granularity, and fluorescence. It gives the percentage, actual number of cells, and mean fluorescence intensity (MFI) of the cell population, and can measure multiple parameters simultaneously on hundreds of individual cells per second; it is a powerful technology with a wide variety of applications in biopharmaceutics (8,9). Appropriate fluorochromes, dyes, conjugates, incubation temperatures, and periods are the essentials for cell surface protein estimation to get well-defined data from the samples.

Two prime tools that have gained prominence for establishment of functional comparability are surface plasmon resonance (SPR) and biolayer interferometry (BLI). Both techniques are optic-based label-free techniques that are used for estimating the biomolecular interaction profiles of biosimilar drugs. These two techniques are superior to traditional fluorescence or luminescence techniques, that are aided by labeling, because labeling is cumbersome and can occupy principal binding sites of the interacting molecule, thereby leading to conformational changes in the molecule and increase non-specificity in the analytical result (10,11).

SPR allows real-time, label-free detection of the interactions between biomolecules. Surface plasmon resonance is a phenomenon that occurs when polarized light strikes an electrically conducting surface at the interface of two media. This interaction generates plasmons, which are electron charge density waves, reducing the intensity of reflected light at a specific angle, referred to as the resonance angle. SPR is a powerful technique for measuring the binding of any pair of interacting molecules, including proteins, antibodies, and antigens. Interactions are measured in real-time, which enable the determination of kinetic parameters. The characterization of antibody–antigen interactions is essential for the successful development of biotherapeutics (9). For about two decades, SPR biosensors have been used to characterize antibody–antigen interactions with applications ranging from the low-resolution affinity screening of antibodies to the high-resolution kinetic constant determinations of the antibodies, and the classification of antibody binding epitopes via epitope-binding studies (12).

BLI works on the principle of superimposition of electromagnetic waves of similar or different phases (13,14). BLI platforms comprise two interfaces, one between the glass fiber and the proprietary biomolecule, and the other between the surface chemistry and the solution. In addition, the BLI platform includes a disposable dip and an optical biosensor. Immobilization of a biomolecule on the surface tip of the glass fiber increases the pathlength of the reflection at the interface between surface chemistry and the solution that changes the interference patterns of all the wavelengths. When the interferometric profiles of the wavelengths are plotted, that results in a new profile that exhibits a shift to the right compared to the original profile. Therefore, if the immobilized molecule interacts with another molecule, there will be a further shift in the interferometric profile. This provides real-time kinetics and quantitation data of biomolecular interactions without the use of labeling (13,14).

Although the ligand-binding assay can be performed readily with great precision and accuracy, the MOA typically involves post-ligand-binding and thus, the binding activity alone is an incomplete measure of potency. Evaluation of potency at the cellular level is required based on the understanding of the MOA for different targets. The biotherapeutic can typically either induce an early response (signaling pathway) or a late response (proliferation, cytokines).

MAbs target soluble receptors or cytokines on the cell surface and evaluation of this interaction can be achieved from cytotoxic assays including apoptosis to cell proliferation and metabolic assays. The antigen-biding fragment (Fab) fragment of the mAb is mainly associated with binding specificity, while the antibody fragment crystallizable (Fc) portion is for the function of immunoglobulin G (IgG) at the cell level (15). There is significant discrepancy between the potency of mAb therapeutics measured in vitro and in vivo in regards to the required doses. Apart from complement activation, other effector functions are also important for MOA of mAbs.

As molecular-targeted biotherapeutics, antibodies that bind to specific cell-surface antigens on target cells can induce cytotoxicity via the effector functions of antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP) through the constant region of the Fc, and apoptosis of target cells (15,16). Establishment of an ADCC or CDC assay should be performed according to the characteristics of the mAbs because the assessment of effector functions is important for the development of the original mAbs candidates. Both in vitro assays are common tools for immunotherapeutic drug discovery and biosimilar development.

ADCC is a lytic mechanism that can be mediated by autoreactive IgG where monoclonal antibodies are able to elicit killing of antibody-coated target cells. The autoreactive IgG recruits effector cells to the target cells with the Fab portion of the IgG binding to the target cell and the Fc region associating with Fc receptors (FcR) on effector cells such as natural killer (NK) cells, monocytes, macrophages, neutrophils, eosinophils, and dendritic cells. Then, the Fc–FcR cross-linking results in the formation of an immune synapse leading to direct tumor cell lysis through the release of cytotoxic molecules (17).

CDC is a cytolytic cascade mediated by a series of complement proteins generously present in the serum. It is triggered by binding of complement component 1q (C1q) to the constant region of cell-bound antibody molecules (17,19). The first step of the complement cascade is binding of the C1q component to the Fc region, which affects the intensity of the following complement activations. A few approaches have succeeded in enhancing the CDC by facilitating the binding of the antibody constant region to the C1q component. As a result of the engineered amino acid mutations that have been inserted into either Fc or the hinge region, an improvement in C1q binding is observed (20).

The ADCP assay is based on using peripheral blood mononuclear cell (PBMC)-derived macrophages as effector cells. Monocytes are isolated from PBMCs and differentiated to macrophages in culture. The workflow is more sophisticated than ADCC and usually takes more than a week to retrieve macrophages. A dose-dependent curve is generated to assess the ADCP potency and phagocytosis is analyzed using flow cytometry. The ADCP assay is a powerful tool for the assessment of biocompatibility as well as early phage confirmation of in vivo (21–23).

Because of the complexity and intrinsic heterogeneity of mAbs, extensive physicochemical and biological characterization must be carefully conducted. In this article, we present the major tools that are used for functional characterization of mAb therapeutics, assessment methods and technologies that are used to characterize mAb-based candidate during preclinical and clinical studies. An important step in the successful development of a biosimilar is to establish robust analytical and functional comparability with the innovator (24). These are necessary for the biosimilar manufacturer to take advantage of the significant reduction in clinical data required for achieving regulatory approval (25). Functional tools have played an important role and have gradually emerged as a major resource for characterization of biosimilars, thereby playing a prime role in the biosimilar development. A comprehensive set of bioanalytical methods is typically used to analyze functional integrity and comparability (26, 27).

Establishment of cell-based potency assays is more useful than developing a ligand-binding assay because cell-based assays enable better detection of chemical modifications, such as deamidation in the complementarity-determining region or the Fc region of the molecule on its potency (28). Therefore, cell-based assays should be primarily chosen for product characterization, even for lot release, during the clinical development of mAb-based drug and post-licensure life-cycle management (29,30). However, cell-based methods are rather time-consuming and laborious and offer limited automation possibilities. Moreover, the detection format usually requires a label and a complex labelling protocol (9). The development of ligand-binding assays, used orthogonally, may prove to be a powerful and complementary tool in basic research, drug discovery and development, and downstream bioprocessing.

No potential conflicts of interest were disclosed.

(2) M. Hassanein, M.A. Partridge, W. Shao, and A. Torri, 

(3) A.M. Goetze, M.R. Schenauer, and G.C. Flynn, 

(4) A. Eon-Duval, H. Broly, and R. Gleixner, 

(5) S.K. Singh, G. Narula, and A.S. Rathore, 

(6) A.S. Rathore, I.S. Krull, and S. Joshi, 

(7) T. Aung, B. Chapuy, D. Vogel, D. Wenzel, M. Oppermann, M. Lahmann, T. Weinhage, K. Menck, T. Hupfeld, R. Koch, L. Trumper, and G.G. Wulf, 

(8) I. Jilani, S. O’Brien, T. Manshuri, D.A. Thomas, V.A. Thomazy, M. Imam, S. Naeem, S. Verstovsek, H. Kantarjian, F. Giles, M. Keating, and M. Albitar, Blood 102(10), 3514–3520 (2003).

(9) M. Cedeño-Arias, J. Sanchez-Ramirez, R. Blanco-Santana, and E. Rengifo-Calzado, 

(11) A.S. Rathore, I. Krull, J. Batra, and D. Kumar, 

(13) X.R. Jiang, A. Song, S. Bergelson, T. Arroll, B. Parekh, K. May, S. Chung, R. Strouse, A. Mire-Sluis, and M. Schenerman. 

 (Academic Press, Massachusetts, 2007), pp. 3–5.

(16) X. Wang, Z. An, W. Luo, N. Xia, and Q. Zhao, 

(17) M. Tada, A Ishii-Watabe, T. Suzuki, and N. Kawasaki, 

(18) N. Nupur, N. Chhabra, R. Dash, and A.S. Rathore, 

(19) S. Lida, R. Kuni-Kamochi, K. Mori, H. Misaka, M. Inoue, A. Okazaki, K. Shitara, and M. Satoh, 

(20) S. Lida, H. Misaka, M. Inoue, M. Shibata, R. Nakano, N. Yamane-Ohnuki, M. Wakitani, K. Yano, K. Shitara, and M. Satoh, 

(21) A.W. Pawluczkowycz, F.J. Beurskens, P.V. Beum, M.A. Lindorfer, J.G.J van de Winkel, P.W.H.I. Parren, and R.P. Taylor, 

(23) L. Kamen, S. Myneni, C. Langsdorf, E. Kho, B. Ordonia, T. Thakurta, K. Zheng, A. Song, and S. Chung, 

(25) E.R. Kabir, S.S. Moreino, and M.K.S. Siam, 

(26) A.S. Tsiftsoglou, S. Ruiz, and C.K. Schneider, 

Biomarker Discovery in the Developing World: Dissecting the Pipeline for Meeting the Challenges

(29) T.T. Hansel, H. Kropshofer, T. Singer, J.A. Mitchell, and A.J.T. George, 

(30) R. Bansal, R. Dash, and A.S. Rathore, 

We present the main analytical techniques for performing functional characterization of biotherapeutic products. Such assessments are particularly critical for biosimilars, where analytical testing must ensure functional comparability with the innovator product.

Tools for Functional Assessment of Biotherapeutics

This article is the first of four on the bioanalysis of small-molecule drugs and metabolites by liquid chromatography–mass spectrometry (LC–MS). In this article, we provide an overview of the fundamentals, workflow, regulations, and modern trends on these quantitative assays.

 is the term used to describe the quantitative assessment of drugs and their metabolites in biological fluids (such as blood, plasma, and urine) and tissue homogenates. Bioanalysis plays a pivotal role in the research, discovery, development, and commercialization of new drug therapeutics, and also offers many career opportunities for analytical chemists. Initially, bioanalysis was first used to detect illicit drugs in biological fluids to investigate overdosing in forensic cases. The field then grew from there with the development of pharmacokinetic science (1).

The four white papers for this planned series are:

Part 1: An overview of the fundamentals and regulations.

Part 2: Sample preparation for different sample types.

Part 3: Method development–optimization and best practices.

Part 4: Method validation for regulated bioanalysis.

Part 1 focuses on the bioanalysis of new chemical entities (NCE) in physiological fluids by liquid chromatography–mass spectrometry (LC–MS) in nonclinical and clinical samples. It strives to be a primer for the novice and a guide to the fundamentals of methodologies and regulations for the laboratory scientist. Bioanalysis of large-molecule biotherapeutics is not covered in this part. LC– MS applications and methodologies in biochemical research, drug metabolism, biomarker analysis, and clinical diagnostics are briefly mentioned.

Table I lists the common acronyms and brief definitions. Some terms are further described in the text or cited in references. For comprehensive explanations, the reader is referred to books and articles on drug development, pharmacology, pharmacokinetics (PK), drug metabolism (DM), bioanalysis (BA), LC, and MS (2–11).

The Role of Bioanalysis in Drug Discovery and Development

The development of new drugs is a complex, expensive, and multidisciplinary process. The modern drug development process often uses a molecular approach, which starts with an understanding of the biology and pathophysiology of the disease, the identification of the molecular target (a receptor or enzyme) responsible for the specific body malfunction, and the synthesis or discovery of a molecule (a small organic molecule or antibody) that binds to a physiological target, thereby mitigating a particular disease state (2). Because the drug must first be bound to the target to be effective, its distribution to the patient’s systemic circulatory system is mandatory unless the drug can be delivered directly to the affected organ or target (3–6). Therefore, it is paramount to have accurate assessments of the drug concentrations in the patient’s physiological fluids after administering the drug to the patient. For small-molecule drug products, oral dosage forms like tablets or capsules are generally preferred because of the ease in administering them: The patient ingests oral drug products to release the active pharmaceutical ingredient (API), which is then absorbed from the digestive system into the bloodstream to reach the intended target.

Bioanalysis is conducted during all new drug development phases—including initial research, drug discovery, preclinical, nonclinical, clinical development, and post-approval studies. Data from bioanalytical studies are collected to support various investigations, as can be seen in Table II. Readers seeking an in-depth understanding of these topics are encouraged to peruse the relevant references (4–6).

Fundamentals of High Performance Liquid Chromatography (HPLC) and MS in Bioanalysis

LC–MS is the primary analytical technique for the quantitative bioanalysis of small-molecule drugs in physiological fluids. This section describes LC–MS fundamentals and the rationales for selecting reversed-phase liquid chromatography (RPLC) with tandem mass spectrometry (MS/MS) detection as the predominant technique.

The reader is referred to textbooks and review articles for details on HPLC (including RPLC (7,8), MS, and LC–MS (9–11). Table III lists the terminologies of HPLC and MS in bioanalysis and the advantages and limitations of RPLC with MS/MS detection.

RPLC is the predominant LC mode used in bioanalysis. The primary retention mechanism of RPLC is the hydrophobic interaction of the analytes with a bonded hydrophobic ligand (C18) to silica supports packed inside a column. Because the hydrophobic interaction force is weak, there is a reasonable assurance that all analytes in the sample will be eluted from the column with ~100% mass balance. RPLC is amenable to separating analytes with a wide polarity range under gradient conditions (7). Because most small-molecule drugs are basic (<80%), an acidic, aqueous mobile phase is generally used to keep the drug molecule in an ionized state which also suppresses the silanophilic activity of the bonded phases.

The key limitation of RPLC is the lack of retention for hydrophilic analytes that are better separated using a specialized RPLC bonded phase without end-capping or with a hydrophilic end-capping. A newer LC mode called hydrophilic interaction liquid chromatography (HILIC) has also been used successfully (7). In HILIC, one uses a hydrophilic stationary phase (such as silica) and a mobile phase similar to RPLC (acetonitrile and aqueous buffers). The analytes are eluted in an order that is opposite to that of RPLC, and the technique is less robust than RPLC. HILIC using MS-compatible mobile phases is particularly useful for analyzing secondary metabolites. Other HPLC modes, such as ion-exchange chromatography (IEC) and size-exclusion chromatography (SEC), are rarely used in bioanalysis because their mobile phases are generally not MS-compatible.

Triple-quadrupole mass spectrometry (TQMS) or MS/MS with electrospray ionization (ESI) and multiple or selected reaction monitoring (MRM or SRM) is the primary technique used in bioanalysis because of its excellent reproducibility, sensitivity, specifically nanomolar (nM) or picomolar (pM) levels, and specificity (7,11). The impressive linear dynamic range (typically up to three or four orders of magnitude) allows the simultaneous quantitation of the API and lower-level metabolites in the same assay. A drawback of MS detection mode is the requirement of an internal standard for each analyte to compensate for loss during sample preparation, nebulization efficiency in the LC–MS interface, and the ion suppression and enhancement matrix effects (9–11). The internal standard used is preferably a stable isotopically labeled form of the analyte, which must be synthesized or purchased from a commercial vendor and added to the sample early during sample preparation.

Another limitation of MS is its inability to differentiate isobaric compounds. However, many diastereomers from multichiral NCEs can be separated by a well-developed HPLC method, and most enantiomer pairs can also be resolved using a chiral LC column (7). Ion mobility MS (IMS) is increasingly used to separate isomers based on differences in collisional cross-section. High resolution MS (HRMS) such as time-of-flight (TOF) and orbital trap MS, often available as hybrid (quadrupole time of flight, QTOF) instruments or “tribrid” (quadrupole–orbital ion trap) instruments, is a powerful tool for high-throughput screening applications or structure elucidation of metabolites (11,12). HRMS is invaluable in research to support particular investigations because it has a higher discrimination power to eliminate or reduce interferences from matrix components without MRM. Although they were not typically used in routine quantitative testing in the past, there has been an increasing trend recently in HRMS-based quantitation using new generations of HRMS instruments.

Workflow in Non-Regulated and Clinical Bioanalysis

On the laboratory side, the bioanalytical workflow is similar to most analytical testing procedures used in the quality assessment of drug substances and products (7). A key difference is the complex biological sample matrices, which require more sample cleanup, followed by a sensitive and selective quantitation of the API and its specified metabolites. Most bioanalytical studies are project-based, such as PK evaluation for initial NCE screening, good laboratory practice (GLP) toxicology studies, or testing patient samples under good clinical practice (GCP) regulations. The general workflow includes documented procedures such as sampling and sample preparation, method development (calibration, LC–MS parameter optimization), method validation, sample analysis, and data processing and reporting (7,11). The final deliverables can include reports for initial PK studies, phase 1 dose-ranging for safety evaluation, or phase 4 bioequivalence studies to support new formulations. Reported data yield insights on drug absorption into the systemic circulation for bioavailability, the peak exposure of the drug (

), time taken for the maximum peak exposure (

) for clearance of the drug in plasma, or the investigation of excretion and metabolic profiles, by measuring drug concentrations in plasma, urine, and feces for mass balance studies.

The development of regulations and guidelines is crucial to ensure ethical, controlled approaches to managing clinical trials and safeguarding the subjects. Efforts to provide regulatory guidance in bioanalysis started in 1990 with a global workshop in Crystal City, Virginia, which marked the beginning of a series of workshops known as “The Crystal City Bioanalytical Workshops” (13). These efforts led to the issuing of much useful regulatory guidance by the US FDA (14). However, it should be noted that this document provides “guidance,” and is not a law or rule. Laboratory personnel should use their best judgment on a case-by-case basis as to the exact methodology for a given method and validation protocol.

Laboratories conducting bioanalytical studies generally operate under GLP guidelines, or Title 21 

 Part 58 for nonclinical laboratory studies (15). In contrast, most manufacturing facilities operate under good manufacturing practice (GMP) regulations (16). Title 21 

 Part 58 describes regulatory requirements for GLP facilities, equipment, testing operation, test and control articles, protocols, records, and reports. Other important guidance documents include the Organization for Economic Cooperation and Development (OECD) principles of GLP and consensus document (17), and the regulations on electronic records and signatures as described in 21 

International Council for Harmonization (ICH) Guidelines

In an attempt to introduce international regulatory harmonization, a scientific consortium of regulators and pharmaceutical companies from Europe, Japan, and the United States created the ICH for Technical Requirements for Pharmaceuticals for Human Use. The focus of ICH is to improve the efficiency of new drug development, prevent duplication of clinical trials in humans, and minimize animal use while maintaining safeguards on quality, safety, efficacy, and regulatory obligations to protect public health. More information on ICH guidelines is available from www.ich.org. The ICH guideline for the validation of analytical procedure is particularly relevant to bioanalytical method validation (19).

At present, the pharmaceutical industry has proactively established a QMS in bioanalysis similar to that described in ICH guideline Q10 (20) for manufacturing, which is focused on strategies and principles to ensure high-quality and consistent data. Some of the key components of the QMS supporting the regulated bioanalysis are listed here:

 This includes the designated staff and facilities for the conduct of the study in a compliant manner.

: These are a set of instructions approved by management to ensure the quality and integrity of the data generated in bioanalysis.

: Test facilities have an independent quality assurance (QA) program to ensure data integrity and compliance with regulations for all programs.

: Test facilities use validated equipment to generate, store, and retrieve the data. Likewise, the chemicals used in the study are documented with their respective identity, concentration, storage recommendations, stability, and expiration dating.

: Samples are labeled to avoid any ambiguity in identification and stored in recommended conditions to ensure stability. A robust tracking system is in place to provide a chain of custody of all critical samples from receipt to disposal processes.

Laboratory information management system (LIMS)

: Most laboratories supporting regulated bioanalysis use validated commercial or in-house developed software to oversee information regarding sample management, study protocols, assay development and validation, and analytical workflow to ensure data accuracy and integrity.

: Patient safety, informed consent, and protecting the integrity of the study by installing proper measures to protect critical identification information in studies are the clinical study components that the bioanalytical testing site must also follow.

Finally, we share our views on modern trends in bioanalysis relating to separation science technologies, sample collection and preparation, data analysis, and outsourcing and automation strategies adopted by many progressive pharmaceutical companies and contract research organizations (CROs).

HPLC trends in bioanalysis are similar to other HPLC applications with the recent adoption of ultrahigh-pressure LC (UHPLC) and sub-2-μm columns to increase throughput and separation efficiency. Superficially porous particles (SPPs) are used to enhance column efficiencies (7) and HILIC for separating primary and secondary metabolites if RPLC does not retain them. Chiral LC is needed to separate enantiomers, although achiral RPLC methods are adequate for separating diastereomers for multichiral API. Faster autosamplers capable of injecting several samples per minute are used for high-throughput screening applications. Many LC–MS systems are multiplexed with parallel pumps and multi-samplers to increase sample throughput (7).

MS/MS using TQMS with MRM or SRM detection remains the dominant preclinical and clinical testing technique. A wide linear dynamic range allows for simultaneous quantitation of the API and its metabolites. Modern TQMS instruments are becoming more compact and stackable with reduced footprints and improved ion optics and ion transfer technology for increased sensitivity, dynamic, and mass range. Many modern chromatography data systems (CDS) are updated to perform data handling and MS control for the same manufacturers’ TQMS systems (7).

HRMS using TOF, orbital trap MS, and hybrid MS are commonly used for metabolite identification and structure elucidation (7,12). HRMS is gaining popularity because it can generate more accurate quantitative data in preclinical screening studies to avoid severe interferences from endogenous components in the matrix.

IMS can separate molecules with the exact 

 ratios based on differences in shape or collisional cross-section. IMS is increasingly used to offer an additional dimension for the resolution of isobaric compounds without extensive HPLC method development effort for isomer separations (21).

More Convenient and Efficient Sampling and Sample Preparation

The collection and transportation procedures for plasma or serum sample remains a labor-intensive and expensive process. The development of dried blood spot testing received much attention a decade ago for nonregulated and regulated bioanalysis (22,23). However, this testing has several bioanalytical challenges that need to be comprehensively addressed.

PCS is a hot topic in the bioanalytical field. PCS constitutes new sample collection methods and technologies used in clinical trials where patients can follow instructions to self-collect samples and ship them to the testing facilities (24). Currently, there are multiple commercial vendors offering support in this direction.

Solid-Phase Extraction (SPE) Microplates and Automation Devices

SPE microplates have improved the automated sample preparation platforms for bioanalysis in complex matrices (25). Innovations in new bonded phase and supports have reduced matrix interferences and allowed more sensitive and accurate assays for many problematic samples. New chemistries in SPE phases will be addressed in the next installment of this article series. Advances in automation devices that include liquid handling, aliquoting, filtration, and shaking using robotic arms or other platforms have significantly increased productivity in routine testing.

Data Analysis and Artificial Intelligence

Data analysis in bioanalysis is another workflow bottleneck that would benefit from more intelligent data systems and data integration platforms. Artificial intelligence (AI) in big data analysis has been shown to extract valuable clinical data with genetic testing in personalized medicine (26). These concepts and applications may soon expedite the correlation of pharmacological results with bioavailability, PK, drug–drug interaction, and other factors.

Bioanalytical outsourcing will continue to be a significant part of the regulated bioanalysis strategy of pharmaceutical companies globally. Sponsors are increasingly looking to outsource suitable development workloads to contract research organizations (CROs) for workforce bandwidth to manage additional drug development programs.

Bioanalysis of drugs in biological samples is a common LC–MS application performed by thousands of laboratories to support new drug development. It is challenging to generate accurate data of trace analytes in complex matrices in a stringent regulatory environment. In this article, we have strived to provide an overview of bioanalysis to the practicing scientist on LC–MS fundamentals, best practices, regulations, and modern trends of this challenging and rapidly evolving analytical methodology.

The author thanks the following colleagues for providing timely reviews and comments to improve the final manuscript’s accuracy and clarity: Perry Wang and Jinhui Zhang at the US FDA; Naidong Weng at Janssen, J&J; Jack Henion, professor emeritus of Cornell University; Peng Yu at EpiQMax; and Eric Thomas, Stephanie Cape, and Mark Arnold at Covance.

, 3–7 (2009). https://doi.org/10.4155/bio.09.3.

Drug Discovery and Development: Technology in Transition

 (Churchill Livingston, Edinburgh, Scotland, 2nd ed., 2012).

Lippincott Illustrated Reviews: Pharmacology 

(Wolters Kluwer, New York, New York, 7th ed., 2018).

Drug Metabolism, Pharmacokinetics and Bioanalysis

(5) S.H. Hansen and S. Pedersen-Bjergaard (Ed.), 

Bioanalysis of Pharmaceuticals: Sample Preparation, Separation Techniques and Mass Spectrometry

 (John Wiley & Sons, Hoboken, New Jersey, 2015).

Regulated Bioanalysis: Fundamentals and Practice

 (John Wiley & Sons, Hoboken, New Jersey, 2nd ed., 2019).

Mass Spectrometry - Principles and Applications

 (Wiley Interscience, Hoboken, New Jersey, 3rd ed., 2007).

Mass Spectrometry for Drug Discovery and Drug Development

 (John Wiley & Sons, Hoboken, New Jersey, 2012).

, e4533 (2020). https://doi.org/10.1002/jms.4533.

(8), 823–827 (2011). https://doi.org/10.4155/bio.11.45.

Bioanalytical Method Validation, Guidance for Industry

, Title 21, Parts 58 (U.S. Government Printing Office, Washington, D.C., 2011).

, Title 21, Part 211.194(a) (U.S. Government Printing Office, Washington, D.C., 2019).

Principles of Good Laboratory Practice, Environment Directorate

 (Organization for Economic Cooperation and Development, Paris, France, 1998).

, Title 21, Parts 11 (U.S. Government Publishing Office, Washington, D.C., 2003).

(19) International Conference for Harmonization, 

ICH Q2 (R1), Validation of Analytical Procedures: Methodology

 (ICH, Geneva, Switzerland, November 1996, updated 2005).

(20) International Conference for Harmonization, 

(23) L. He, R. Gajee, R. Mangaraj, M. P. Waldron, and K.S. Brown, 

, 393–407 (2020). https://doi.org/10.4155/bio-2019-0180.

(24) D. Sentellas, J. Saurina, and O. Nunez, in 

(Elsevier, Amsterdam, The Netherlands, 2020), pp. 673–698.

, 971–976 (2020). https://doi.org/10.4155/bio- 2020-0075.

CISION PR Newswire, Lab Automation in Bioanalysis Markets, 2024 - Rising Demand for Personalized Medicines

. https:// www.prnewswire.com/news-releases/ lab-automation-in-bioanalysis-markets-2024-rising-demand-for-personalized-medicines--technological-innovations-resulting-in-improved-solutions-300872661.html.

This is the first article in a four-part series exploring the quantitative assessment of drugs and their metabolites in biological fluids (such as blood, plasma, and urine) and tissue homogenates using liquid chromatography–mass spectrometry (LC–MS).

Bioanalysis of Small-Molecule Drugs and Metabolites in Physiological Samples by LC–MS, Part 1: An Overview

The best option for the gas chromatographic (GC) analysis of highly volatile analytes without cryogenic cooling is to use solid adsorbents. Open tubular GC columns with a deposited layer of solid adsorbent on the inside are known as porous layer open tubular (PLOT) columns. Adsorbents like molecular sieves, alumina, porous polymers, and even carbon materials are essential when analyzing light gases. Most gas samples contain water; although we are not interested in the amount of moisture that is present in the sample, water is injected onto the column unless a drying step of the sample is utilized. This article reviews the effects of water on retention and selectivity in gas–solid chromatography of various adsorbent PLOT columns.

Activated alumina has been studied as a chromatographic material for over 70 years. The high surface area of this porous material showed promise in separating C1–C5 hydrocarbons. Because of the extreme activity, tailing, and inconsistent responses of alumina, the material was at first considered almost unusable. In the mid-1950s, alumina oxides were deactivated with water vapor. This new approach drastically improved peak shape and provided consistent compound responses. However, water-deactivated alumina columns could be used only under isothermal conditions. The next significant improvement for porous alumina columns occurred in the 1970s when more stable deactivations with inorganic salts, such as potassium chloride (KCl), sodium sulfate (Na

), and various proprietary salts, were implemented (1–3).

Even though the industry moved away from alumina-packed columns in favor of alumina-based porous layer open tubular (PLOT) columns, alumina columns remained a reliable choice for analyzing C1–C5 hydrocarbons. One thing has not changed since the 1950s—we still have problems with chromatography in the presence of moisture. To better understand the problematic effects of water on alumina columns, we studied the chromatographic behavior of C1–C5 hydrocarbons. Various selectivities of alumina deactivated PLOT columns were tested under the same isothermal chromatographic conditions. The analysis was performed again after injecting 0.1 μL of water onto the column, and the procedure was repeated five times.

Regardless of the column deactivation, the introduction of water onto the alumina PLOT column changes the retention time by accelerating the elution of the analytes. Water will act as a deactivating agent, meaning that the adsorption sites where water molecules are adsorbed will not be available for hydrocarbon retention. This process results in a decrease in retention time. Figures 1 and 2 show examples of the analysis of those two analytes, alumina MAPD (Figure 1) and alumina potassium chloride (Figure 2), as well as the analysis of the columns after exposing them to 0.5 μL of water in increments of 0.1 μL. Not only do we notice shifting retention times, but we also see changes in resolution, indicating that the polarity of the column has changed.

Regardless of whether the column was deactivated with proprietary deactivation, MAPD, or potassium chloride, exposure to water decreases retention time and impacts the resolution of the compounds. The introduction of any moisture to the column would further deactivate aluminum oxide, making the column less polar, which changes the column selectivity. The plotted deviation of retention indices of the analytes, which is based on the retention of adjacent 

-hydrocarbons, confirms our observation. The analytes most affected by the moisture treatment over time are polar analytes—acetylene, propadiene, and methyl acetylene—that show more significant shifts in retention than the butanes and butenes (Figure 3). Similarly, the impact of moisture is more dramatic on a polar column, such as a sodium sulfate alumina column. Figure 4 illustrates changes in relative retention of acetylene on different types of deactivated alumina columns. The polarity of a sodium sulfate-deactivated alumina column declines considerably faster than a potassium chloride-deactivated alumina column. The potassium chloride-deactivated alumina has the lowest polarity, and it is the least sensitive to water.

Water will not damage the alumina column. The column can always be regenerated by conditioning it at the maximum temperature of the column.

Molecular sieves 5A (MSieve 5A) are zeolites, which are part of the family of aluminosilicate minerals. They are strong adsorbents with an unique, tunnel-like crystalline structure and a well-defined pore size. These strong adsorption properties make them ideal for analyzing permanent gases. The analytes separate on molecular sieves based on two mechanisms: First, how well the molecules fit into the material’s pores, a separation based on the size of the molecules; and second, the physical interactions between the molecules and the MSieve 5A crystal, which is a separation that takes place based on the polarity. For example, nitrogen and oxygen are both small enough to fit in the pores of the 5A mineral, but oxygen, a smaller molecule than nitrogen, will navigate through the “tunnels” faster because it has less interactions with the pore surface and elutes from the column before nitrogen. In the case of carbon monoxide, dipole interactions play a more important role, and the MSieve 5A strongly retains these molecules. A bigger molecule, like sulfur hexafluoride (SF6), will not be able to enter the pores of the zeolite. It will only be retained by the outside, free-accessible surface area. The same phenomena is observed with isoalkanes. Isobutane, for example, would be eluted around nitrogen at 40 °C, while 

-butane (which can fit in the pores because of the linear structure), needs a very high temperature to be eluted (4,5).

Adsorption on molecular sieves is reversible, and the adsorption–desorption process is easily regulated with temperature. Molecular sieves are generally used as drying agents, and we know that we cannot analyze water using the MSieve 5A columns because of the high temperature required to desorb water from the molecular sieve pores. Our study on the effects of water on molecular sieves showed that the MSieve 5A has a relatively high tolerance to moisture in comparison to salt-deactivated alumina columns. A MSieve 5A PLOT column, with the dimensions of 30 m x 0.53 mm x 50 μm, was tested using a mixture of permanent gases at 40 °C. Afterward, water was injected onto the column at 100 °C isothermal. Column behavior was monitored by repeating the analysis of permanent gases at 40 °C. Figure 5 demonstrates a chromatogram of the initial analysis of permanent gases, black overlay, and blue overlay is a chromatogram after exposing the molecular sieves to water. The column had to be treated with 1 μL of water to see a notable shift in the retention time of the polar compound, which in this case is carbon monoxide.

Although 1 μL of water may seem like a small amount, the quantity is more significant when we look at it from a different angle. For example, if the gas sample has 50% relative humidity, with every 1 mL injection of gas, we are injecting ~0.01 μL of water onto the column. To see a slight shift of the carbon monoxide peak, we would need to make hundreds of injections.

Solid adsorbent gas chromatography (GC) columns, such as porous layer open tubular (PLOT) columns, are the best option for GC analysis of C1–C5 hydrocarbons, but water can affect retention and selectivity. We review the effects of water for different types of PLOT columns, and explain how to prevent or remediate the problem.

June 2021 | LCGC North America

Controlling Retention Time Drift in Industrial Chromatography Settings

Chromatography Fundamentals, Part X: Light Scattering Detection Systems for Size-Exclusion Chromatography

Tools for Functional Assessment of Biotherapeutics

Bioanalysis of Small-Molecule Drugs and Metabolites in Physiological Samples by LC–MS, Part 1: An Overview

Effects of Water on Adsorbents in Porous Layer Open Tubular (PLOT) Column Gas Chromatography (GC)

Where Has My Efficiency Gone? Impacts of Extracolumn Peak Broadening on Performance, Part III: Tubing and Detectors