An accelerated surface-mediated stress assay of antibody instability for developability studies

Agitation-Induced Aggregation of Lysine- And Interchain Cysteine-Linked Antibody-Drug Conjugates

Drug conjugation to an antibody can affect its stability, which depends on factors such as the conjugation technique used, drug-linker properties, and stress encountered. This study focused on the effects of agitation stress on the physical stability of two lysine (ADC-K) and two interchain cysteine (ADC-C) conjugates of an IgG1 monoclonal antibody (mAb) linked to either ∼4 MMAE or DM1 payloads. During agitation, all antibody-drug conjugates (ADCs) exhibited higher aggregation than the mAb, which was dependent on the conjugation technique (aggregation of ADC-Ks > ADC-Cs) and drug-linker (aggregation of ADCs with MMAE > ADCs with DM1). The aggregation propensities correlated well with higher self-interaction, hydrophobicity, and surface activity of ADCs relative to the mAb. The intermediate reduced mAb (mAb-SH) showed even higher aggregation than the final product ADC-Cs. However, blocking mAb-SH's free thiols with N-ethylmaleimide (NEM) strongly reduced its aggregation, suggesting that free thiols should be minimized in cysteine ADCs. Further, this study demonstrates that a low-volume surface tension method can be used for estimating agitation-induced aggregation of ADCs in early development phases. Identifying liabilities to agitation stress and their relationship to biophysical properties may help optimize ADC stability.

Emergent gauge symmetry in active Brownian matter

We investigate a two-dimensional system of interacting active Brownian particles. Using the Martin-Siggia-Rose-Janssen-de Dominicis formalism, we built up the generating functional for correlation functions. We study in detail the hydrodynamic regime with a constant density stationary state. Our findings reveal that, within a small density fluctuations regime, an emergent U(1) gauge symmetry arises, originated from the conservation of fluid vorticity. Consequently, the interaction between the orientational order parameter and density fluctuations can be cast into a gauge theory, where the concept of "electric charge density" aligns with the local vorticity of the original fluid. We study in detail the case of a microscopic local two-body interaction. We show that, upon integrating out the gauge fields, the stationary states of the rotational degrees of freedom satisfy a nonlocal Frank free energy for a nematic fluid. We give explicit expressions for the splay and bend elastic constants as a function of the Péclet number (Pe) and the diffusion interaction constant (k_{d}).

Combined Effect of Shaking Orbit and Vial Orientation on the Agitation-Induced Aggregation of Proteins

Orbital shaking in a glass vial is a commonly used forced degradation test to evaluate protein propensity for agitation-induced aggregation. Vial shaking in horizontal orientation has been widely recommended to maximize the air-liquid interface area while ensuring solution contact with the stopper. We evaluated the impact of shaking orbit diameter and frequency, and glass vial orientation (horizontal versus vertical) on the aggregation of three proteins prepared in surfactant-free formulation buffers. As soon as an orbit-specific frequency threshold was reached, an increase in turbidity was observed for the three proteins in vertical orientation only when using a 3 mm agitation orbit, and in horizontal orientation only when using a 30 mm agitation orbit. Orthogonal analyses confirmed turbidity was linked to protein aggregation. The most turbid samples had a visually more homogeneous appearance in vertical than in horizontal orientation, in line with the predicted dispersion of air and liquid phases obtained from computational fluid dynamics agitation simulations. Both shaking orbits were used to assess the performance of nonionic surfactants. We show that the propensity of a protein to aggregate in a vial agitated in horizontal or vertical orientation depends on the shaking orbit, and confirm that Brij® 58 and FM1000 prevent proteins from agitation-induced aggregation at lower concentrations than polysorbate 80.

Comparison of the Protective Effect of Polysorbates, Poloxamer and Brij on Antibody Stability Against Different Interfaces

Therapeutic proteins and antibodies are exposed to a variety of interfaces during their lifecycle, which can compromise their stability. Formulations, including surfactants, must be carefully optimized to improve interfacial stability against all types of surfaces. Here we apply a nanoparticle-based approach to evaluate the instability of four antibody drugs against different solid-liquid interfaces characterized by different degrees of hydrophobicity. We considered a model hydrophobic material as well as cycloolefin-copolymer (COC) and cellulose, which represent some of the common solid-liquid interfaces encountered during drug production, storage, and delivery. We assess the protective effect of polysorbate 20, polysorbate 80, Poloxamer 188 and Brij 35 in our assay and in a traditional agitation study. While all nonionic surfactants stabilize antibodies against the air-water interface, none of them can protect against hydrophilic charged cellulose. Polysorbates and Brij increase antibody stability in the presence of COC and the model hydrophobic interface, although to a lesser extent compared to the air-water interface, while Poloxamer 188 has a negligible stabilizing effect against these interfaces. These results highlight the challenge of fully protecting antibodies against all types of solid-liquid interfaces with traditional surfactants. In this context, our high-throughput nanoparticle-based approach can complement traditional shaking assays and assist in formulation design to ensure protein stability not only at air-water interfaces, but also at relevant solid-liquid interfaces encountered during the product lifecycle.

Interfacial Adsorption Controls Particle Formation in Antibody Formulations Subjected to Extensional Flows and Hydrodynamic Shear

During their manufacturing and delivery to patients, therapeutic proteins are commonly exposed to various interfaces and to hydrodynamic shear forces. Although adsorption of proteins to solid-liquid interfaces is known to foster formation of protein aggregates and particles, the impact of shear remains controversial, in part because of experimental challenges in separating the effects of shear from those caused by simultaneous exposure to interfaces. Extensional flows (occurring when solutions flow through sudden contractions) exert localized elongational forces that have been suspected to be damaging to proteins. In this work, we measured aggregation and particle formation in formulations of polyclonal and monoclonal antibodies subjected to extensional flow, high shear (105 s-1) and exposure to stainless-steel/water interfaces. Modification of the surface charge at the stainless steel/water interface changed protein adsorption characteristics without altering shear profiles, enabling shear and interfacial interactions to be separated. Even under conditions where antibodies were subjected to high hydrodynamic shear and extensional flow, production of subvisible particles could be inhibited by modifying the stainless-steel surface charge to minimize antibody adsorption. Digital images of particles recorded by flow imaging microscopy (FIM) and analyzed with machine learning algorithms were consistent with a particle formation mechanism by which antibodies adsorb and aggregate at the stainless-steel/water interface and subsequently form particles when shear displaces the interfacial aggregates, transporting them into the bulk solution. Topographical differences measured using atomic force microscopy (AFM) supported the proposed mechanism by showing reduced levels of protein adsorption on surface-charge-modified stainless-steel.

How can we discover developable antibody-based biotherapeutics?

Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.

Surface patches induce nonspecific binding and phase separation of antibodies

Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.

Multidimensional Protein Solubility Optimization with an Ultrahigh-Throughput Microfluidic Platform

Protein-based biologics are highly suitable for drug development as they exhibit low toxicity and high specificity for their targets. However, for therapeutic applications, biologics must often be formulated to elevated concentrations, making insufficient solubility a critical bottleneck in the drug development pipeline. Here, we report an ultrahigh-throughput microfluidic platform for protein solubility screening. In comparison with previous methods, this microfluidic platform can make, incubate, and measure samples in a few minutes, uses just 20 μg of protein (>10-fold improvement), and yields 10,000 data points (1000-fold improvement). This allows quantitative comparison of formulation excipients, such as sodium chloride, polysorbate, histidine, arginine, and sucrose. Additionally, we can measure how solubility is affected by the combinatorial effect of multiple additives, find a suitable pH for the formulation, and measure the impact of mutations on solubility, thus enabling the screening of large libraries. By reducing material and time costs, this approach makes detailed multidimensional solubility optimization experiments possible, streamlining drug development and increasing our understanding of biotherapeutic solubility and the effects of excipients.

Single-Molecule Sizing through Nanocavity Confinement

An approach relying on nanocavity confinement is developed in this paper for the sizing of nanoscale particles and single biomolecules in solution. The approach, termed nanocavity diffusional sizing (NDS), measures particle residence times within nanofluidic cavities to determine their hydrodynamic radii. Using theoretical modeling and simulations, we show that the residence time of particles within nanocavities above a critical time scale depends on the diffusion coefficient of the particle, which allows the estimation of the particle's size. We demonstrate this approach experimentally through the measurement of particle residence times within nanofluidic cavities using single-molecule confocal microscopy. Our data show that the residence times scale linearly with the sizes of nanoscale colloids, protein aggregates, and single DNA oligonucleotides. NDS thus constitutes a new single molecule optofluidic approach that allows rapid and quantitative sizing of nanoscale particles for potential applications in nanobiotechnology, biophysics, and clinical diagnostics.

Surface-Induced Protein Aggregation and Particle Formation in Biologics: Current Understanding of Mechanisms, Detection and Mitigation Strategies

Protein stability against aggregation is a major quality concern for the production of safe and effective biopharmaceuticals. Amongst the different drivers of protein aggregation, increasing evidence indicates that interactions between proteins and interfaces represent a major risk factor for the formation of protein aggregates in aqueous solutions. Potentially harmful surfaces relevant to biologics manufacturing and storage include air-water and silicone oil-water interfaces as well as materials from different processing units, storage containers, and delivery devices. The impact of some of these surfaces, for instance originating from impurities, can be difficult to predict and control. Moreover, aggregate formation may additionally be complicated by the simultaneous presence of interfacial, hydrodynamic and mechanical stresses, whose contributions may be difficult to deconvolute. As a consequence, it remains difficult to identify the key chemical and physical determinants and define appropriate analytical methods to monitor and predict protein instability at these interfaces. In this review, we first discuss the main mechanisms of surface-induced protein aggregation. We then review the types of contact materials identified as potentially harmful or detected as potential triggers of proteinaceous particle formation in formulations and discuss proposed mitigation strategies. Finally, we present current methods to probe surface-induced instabilities, which represent a starting point towards assays that can be implemented in early-stage screening and formulation development of biologics.

Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties

Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Amyloidogenesis: What Do We Know So Far?

The study of protein aggregation, and amyloidosis in particular, has gained considerable interest in recent times. Several neurodegenerative diseases, such as Alzheimer's (AD) and Parkinson's (PD) show a characteristic buildup of proteinaceous aggregates in several organs, especially the brain. Despite the enormous upsurge in research articles in this arena, it would not be incorrect to say that we still lack a crystal-clear idea surrounding these notorious aggregates. In this review, we attempt to present a holistic picture on protein aggregation and amyloids in particular. Using a chronological order of discoveries, we present the case of amyloids right from the onset of their discovery, various biophysical techniques, including analysis of the structure, the mechanisms and kinetics of the formation of amyloids. We have discussed important questions on whether aggregation and amyloidosis are restricted to a subset of specific proteins or more broadly influenced by the biophysiochemical and cellular environment. The therapeutic strategies and the significant failure rate of drugs in clinical trials pertaining to these neurodegenerative diseases have been also discussed at length. At a time when the COVID-19 pandemic has hit the globe hard, the review also discusses the plausibility of the far-reaching consequences posed by the virus, such as triggering early onset of amyloidosis. Finally, the application(s) of amyloids as useful biomaterials has also been discussed briefly in this review.

Developability Assessments of Monoclonal Antibody Candidates to Minimize Aggregation During Large-Scale Ultrafiltration and Diafiltration (UF-DF) Processing

Therapeutic proteins are subjected to a variety of stresses during manufacturing, storage or administration, that often lead to undesired protein aggregation and particle formation. Ultrafiltration-diafiltration (UF-DF) processing of monoclonal antibodies (mAbs) is one such manufacturing step that has been shown to result in such physical degradation. In this work, we explore the use of different analytical techniques and lab-scale setups as methodologies to predict and rank-order the aggregation potential of four different mAbs during large-scale UF-DF processing. In the first part of the study, a suite of biophysical techniques was applied to assess differences in their inherent bulk protein properties including conformational and colloidal stability in a PBS buffer. Additionally, the inherent interfacial properties of these mAbs in PBS were measured using a Langmuir trough technique. In the next part of the study, several different scale-down lab models were evaluated including a lab bench-scale UF-DF setup, mechanical stress (shaking/stirring) studies in vials, and application of interfacial dilatational stress using a Langmuir trough to assess protein particle formation in different UF-DF processing buffers. Taken together, our results demonstrate the ability of a Langmuir-trough methodology to accurately predict the mAb instability profile observed during large scale UF-DF processing.

Machine Learning Analysis Provides Insight into Mechanisms of Protein Particle Formation Inside Containers During Mechanical Agitation

Container choice can influence particle generation within protein formulations. Incompatibility between proteins and containers can manifest as increased particle concentrations, shifts in particle size distributions and changes in particle morphology distributions. In this study, flow imaging microscopy (FIM) combined with machine learning-based goodness-of-fit hypothesis testing algorithms were used in accelerated stability studies to investigate the impact of containers on particle formation. Containers in four major container categories subdivided into eleven container types were filled with monoclonal antibody formulations and agitated with and without headspace, producing subvisible particles. Digital images of the particles were recorded using flow imaging microscopy and analyzed with machine learning algorithms. Particle morphology distributions depended on container category and type, revealing differences that would not have been obvious by analysis of particle concentrations or container surface characteristics alone. Additionally, the algorithm was used to compare morphologies of particles generated in containers against those generated using isolated stresses at air-liquid and container-air-liquid interfaces. These comparisons showed that the morphology distributions of particles formed during agitation most closely resemble distributions that result from exposure of proteins to moving triple interface lines at points where container-air-liquid interfaces intersect. The approach described here can be used to identify dominant causes of particle generation due to protein-container interactions.

Aggregation of Lactoferrin Caused by Droplet Atomization Process via a Two-Fluid Nozzle: The Detrimental Effect of Air-Water Interfaces

Biological macromolecules, especially therapeutic proteins, are delicate and highly sensitive to denaturation from stresses encountered during the manufacture of dosage forms. Thin-film freeze-drying (TFFD) and spray freeze-drying (SFD) are two processes used to convert liquid forms of protein into dry powders. In the production of inhalable dry powders that contain proteins, these potential stressors fall into three categories based on their occurrence during the primary steps of the process: (1) droplet formation (e.g., the mechanism of droplet formation, including spray atomization), (2) freezing, and (3) frozen water removal (e.g., sublimation). This study compares the droplet formation mechanism used in TFFD and SFD by investigating the effects of spraying on the stability of proteins, using lactoferrin as a model. This study considers various perspectives on the denaturation (e.g., conformation) of lactoferrin after subjecting the protein solution to the atomization process using a pneumatic two-fluid nozzle (employed in SFD) or a low-shear drop application through the nozzle. The surface activity of lactoferrin was examined to explore the interfacial adsorption tendency, diffusion, and denaturation process. Subsequently, this study also investigates the secondary and tertiary structure of lactoferrin and the quantification of monomers, oligomers, and, ultimately, aggregates. The spraying process affected the tertiary structure more negatively than the tightly woven secondary structure, resulting in the peak position corresponding to the tryptophan (Trp) residues red-shifting by 1.5 nm. This conformational change can either (a) be reversed at low concentrations via relaxation or (b) proceed to form irreversible aggregates at higher concentrations. Interestingly, when the sample was allowed to progress into micrometer-sized aggregates, such a dramatic change was not detected using methods such as size-exclusion chromatography, polyacrylamide gel electrophoresis, and dynamic light scattering at 173°. A more complete understanding of the heterogeneous protein sample was achieved only through a combination of 173 and 13° backward and forward scattering, a combination of derived count rate measurements, and microflow imaging (MFI). After studying the impact of droplet formation mechanisms on aggregation tendency of lactoferrin, we further investigated two additional model proteins with different surface activity: bovine IgG (serving as a non surface-active negative reference), and β-galactosidase (another surface-active protein). The results corroborated the lactoferrin findings that spray-atomization-related stress-induced protein aggregation was much more pronounced for proteins that are surface active (lactoferrin and β-galactosidase), but it was minimal for non-surface-active protein (bovine IgG). Finally, compared to the low-shear dripping used in the TFFD process, lactoferrin underwent a relatively fast conformational change upon exposure to the high air-water interface of the two-fluid atomization nozzle used in the SFD process as compared to the low shear dripping used in the TFFD process. The interfacial-induced denaturation that occurred during spraying was governed primarily by the size of the atomized droplets, regardless of the duration of exposure to air. The percentage of denatured protein population and associated activity loss, in the case of β-galactosidase, was determined to range from 2 to 10% depending on the air-flow rate of the spraying process.

Improving antibody drug development using bionanotechnology

Monoclonal antibodies are being used to treat a remarkable breadth of human disorders. Nevertheless, there are several key challenges at the earliest stages of antibody drug development that need to be addressed using simple and widely accessible methods, especially related to generating antibodies against membrane proteins and identifying antibody candidates with drug-like biophysical properties (high solubility and low viscosity). Here we highlight key bionanotechnologies for preparing functional and stable membrane proteins in diverse types of lipoparticles that are being used to improve antibody discovery and engineering efforts. We also highlight key bionanotechnologies for high-throughput and ultra-dilute screening of antibody biophysical properties during antibody discovery and optimization that are being used for identifying antibodies with superior combinations of in vitro (formulation) and in vivo (half-life) properties.

Emerging Challenges and Innovations in Surfactant-mediated Stabilization of Biologic Formulations

Biologics may be subjected to various destabilizing conditions during manufacturing, transportation, storage, and use. Therefore, biologics must be appropriately formulated to meet their desired quality target product profiles. In the formulations of protein-based biologics, one critical component is surfactant. Polysorbate 80 and Polysorbate 20 remain the most commonly used surfactants. Surfactants can stabilize proteins through different mechanisms and help the proteins withstand destabilization stresses. However, the challenges associated with surfactants, for instance, impurities, degradation, and potential triggering of adverse immune responses, have been encountered. Therefore, there are continued efforts to develop novel surfactants to overcome these challenges associated with traditional surfactants. Meanwhile, surfactants have also found their use in formulations of newer and novel modalities, namely, antibody-drug conjugates, bispecific antibodies, and adeno-associated viruses (AAV). This review provides an updated in-depth discussion of surfactants in the above-mentioned areas, namely mechanism of action of surfactants, a critical review of challenges with surfactants and current mitigation approaches, and emerging technologies to develop novel surfactants. In addition, gaps, current mitigations, and future directions have been presented to trigger further discussion and research to facilitate the use and development of novel surfactants.

Design of Biopharmaceutical Formulations Accelerated by Machine Learning

In addition to activity, successful biological drugs must exhibit a series of suitable developability properties, which depend on both protein sequence and buffer composition. In the context of this high-dimensional optimization problem, advanced algorithms from the domain of machine learning are highly beneficial in complementing analytical screening and rational design. Here, we propose a Bayesian optimization algorithm to accelerate the design of biopharmaceutical formulations. We demonstrate the power of this approach by identifying the formulation that optimizes the thermal stability of three tandem single-chain Fv variants within 25 experiments, a number which is less than one-third of the experiments that would be required by a classical DoE method and several orders of magnitude smaller compared to detailed experimental analysis of full combinatorial space. We further show the advantage of this method over conventional approaches to efficiently transfer historical information as prior knowledge for the development of new biologics or when new buffer agents are available. Moreover, we highlight the benefit of our technique in engineering multiple biophysical properties by simultaneously optimizing both thermal and interface stabilities. This optimization minimizes the amount of surfactant in the formulation, which is important to decrease the risks associated with corresponding degradation processes. Overall, this method can provide high speed of converging to optimal conditions, the ability to transfer prior knowledge, and the identification of new nonlinear combinations of excipients. We envision that these features can lead to a considerable acceleration in formulation design and to parallelization of operations during drug development.

Miniaturized Forced Degradation of Therapeutic Proteins and ADCs by Agitation-Induced Aggregation Using Orbital Shaking of Microplates

Microplate-based formulation screening is a powerful approach to identify stabilizing excipients for therapeutic proteins while reducing material requirements. However, this approach is sometimes not representative of studies conducted in relevant container closures. The present study aimed to identify critical parameters for a microplate-based orbital shaking method to screen biotherapeutic formulations by agitation-induced aggregation. For this purpose, an in-depth methodological study was conducted using different shakers, microplates, and plate seals. Aggregation was monitored by size exclusion chromatography, turbidity, and backgrounded membrane imaging. Both shaker quality and liquid-seal contact had substantial impacts on aggregation during shaking and resulted in non-uniform sample treatment when parameters were not suitably selected. The well volume to fill volume ratio (V_well/V_fill) was identified as an useful parameter for achieving comparable aggregation levels between different microplate formats. An optimized method (2400 rpm [a_c 95 m/s²], V_fill 60-100 µL [V_well/V_fill 6-3.6], 24 h, RT, heat-sealed) allowed for uniform sample treatment independent of surface tension and good agreement with vial shaking results. This study provides valuable guidance for miniaturization of shaking stress studies in biopharmaceutical drug development, facilitating method transfer and comparability between laboratories.

Plate Reader-Based Analytical Method for the Size Distribution of Submicron-Sized Protein Aggregates Using Three-Dimensional Homodyne Light Detection

The assessment of aggregates is essential in biopharmaceutical development. Although submicron-sized aggregates are considered to have a potential immunogenicity risk, analytical techniques are limited. In this study, we present a new analytical technique using three-dimensional homodyne light detection (3D-HLD). In this system, submicron-sized particles are quantified by combining the reflected light detection of each particle by high-speed 3D scan and then enhancing the amplitude of the reflected light using HLD. The particle concentrations and size distributions of human tetanus immune globulin (TIG) aggregates generated by stirring were measured using 3D-HLD. Both concentrations and distributions were comparable to those obtained via resonant mass measurement (RMM), a technique commonly used for submicron-sized particle measurement. Aiming at feasibility assessment of 3D-HLD for the high-through-put formulation development, 30 formulations of TIG and rituximab under agitation stress were analyzed by 3D-HLD. The results showed that 3D-HLD can automatically and simultaneously assess the aggregate concentrations and size distributions of at least 90 samples. This study demonstrates that 3D-HLD can be used for submicron-sized aggregate analysis as an orthogonal method to RMM and also as a screening tool during formulation development.

Screening for protein-protein interactions with asymmetrical flow field-flow fractionation

We describe a new method for screening protein-protein interaction of biopharmaceutical molecules at dilute concentrations to predict development issues at high concentration. The method is based on Asymmetrical Flow Field-Flow Fractionation (AF4) measurements using well known effects of protein-protein attraction on the fractionation profile due to elevated protein concentrations occurring close to the membrane. We explore the effect for 4 different monoclonal antibodies and show that the profiles obtained are quite different. Interestingly, we find that the recovery in AF4 correlates with the diffusion interaction parameter, which is a standard method for the analysis of protein-protein attraction. The results are insensitive to the protein concentration and buffer composition of the sample solution and only depend on the absolute amount of protein loaded and on the running buffer. This makes the method highly suitable for developability assessment in a compound discovery workflow.

The role of surfaces on amyloid formation

Interfaces can strongly accelerate or inhibit protein aggregation, destabilizing proteins that are stable in solution or, conversely, stabilizing proteins that are aggregation-prone. Although this behaviour is well-known, our understanding of the molecular mechanisms underlying surface-induced protein aggregation is still largely incomplete. A major challenge is represented by the high number of physico-chemical parameters involved, which are highly specific to the considered combination of protein, surface properties, and solution conditions. The key aspect determining the role of interfaces is the relative propensity of the protein to aggregate at the surface with respect to bulk. In this review, we discuss the multiple molecular determinants that regulate this balance. We summarize current experimental techniques aimed at characterizing protein aggregation at interfaces, and highlight the need to complement experimental analysis with theoretical modelling. In particular, we illustrate how chemical kinetic analysis can be combined with experimental methods to provide insights into the molecular mechanisms underlying surface-induced protein aggregation, under both stagnant and agitation conditions. We summarize recent progress in the study of important amyloids systems, focusing on selected relevant interfaces.