Assessment of net charge and protein-protein interactions of different monoclonal antibodies

Flow Activation Energy of High-Concentration Monoclonal Antibody Solutions and Protein-Protein Interactions Influenced by NaCl and Sucrose

The solution viscosity and protein-protein interactions (PPIs) as a function of temperature (4-40 °C) were measured at a series of protein concentrations for a monoclonal antibody (mAb) with different formulation conditions, which include NaCl and sucrose. The flow activation energy (Eη) was extracted from the temperature dependence of solution viscosity using the Arrhenius equation. PPIs were quantified via the protein diffusion interaction parameter (kD) measured by dynamic light scattering, together with the osmotic second virial coefficient and the structure factor obtained through small-angle X-ray scattering. Both viscosity and PPIs were found to vary with the formulation conditions. Adding NaCl introduces an attractive interaction but leads to a significant reduction in the viscosity. However, adding sucrose enhances an overall repulsive effect and leads to a slight decrease in viscosity. Thus, the averaged (attractive or repulsive) PPI information is not a good indicator of viscosity at high protein concentrations for the mAb studied here. Instead, a correlation based on the temperature dependence of viscosity (i.e., Eη) and the temperature sensitivity in PPIs was observed for this specific mAb. When kD is more sensitive to the temperature variation, it corresponds to a larger value of Eη and thus a higher viscosity in concentrated protein solutions. When kD is less sensitive to temperature change, it corresponds to a smaller value of Eη and thus a lower viscosity at high protein concentrations. Rather than the absolute value of PPIs at a given temperature, our results show that the temperature sensitivity of PPIs may be a more useful metric for predicting issues with high viscosity of concentrated solutions. In addition, we also demonstrate that caution is required in choosing a proper protein concentration range to extract kD. In some excipient conditions studied here, the appropriate protein concentration range needs to be less than 4 mg/mL, remarkably lower than the typical concentration range used in the literature.

"Negative" Impact: The Role of Payload Charge in the Physicochemical Stability of Auristatin Antibody-Drug Conjugates

Antibody-drug conjugates (ADCs) tend to be less stable than their parent antibodies, which is often attributed to the hydrophobic nature of their drug payloads. This study investigated how the payload charge affects ADC stability by comparing two interchain cysteine ADCs that had matched drug-to-antibody ratios and identical linkers but differently charged auristatin payloads, vcMMAE (neutral) and vcMMAF (negative). Both ADCs exhibited higher aggregation than their parent antibody under shaking stress and thermal stress conditions. However, conjugation with vcMMAF increased the aggregation rates to a greater extent than conjugation with uncharged but more hydrophobic vcMMAE. Consistent with the payload logD values, ADC-vcMMAE showed the greatest increase in hydrophobicity but minor changes in charge compared with the parent antibody, as indicated by hydrophobic interaction chromatography and capillary electrophoresis data. In contrast, ADC-vcMMAF showed a decrease in net charge and isoelectric point along with an increase in charge heterogeneity. This charge alteration likely contributed to a reduced electrostatic repulsion and increased surface activity in ADC-vcMMAF, thus affecting its aggregation propensity. These findings suggest that not only the hydrophobicity of the payload, but also its charge should be considered as a critical factor affecting the stability of ADCs.

Role of Charge Heterogeneity on Physical Stability of Monoclonal Antibody Biotherapeutic Products

PURPOSE

Chemical modifications in monoclonal antibodies can change hydrophobicity, charge heterogeneity as well as conformation, which eventually can impact their physical stability. In this study, the effect of the individual charge variants on physical stability and aggregation propensity in two different buffer conditions used during downstream purification was investigated.

METHODS

The charge variants were separated using semi-preparative cation exchange chromatography and buffer exchanged in the two buffers with pH 6.0 and 3.8. Subsequently each variant was analysed for size heterogeneity using size exclusion chromatography and dynamic light scattering, conformational stability, colloidal stability, and aggregation behaviour under accelerated stability conditions.

RESULTS

Size variants in each charge variant were similar in both pH conditions when analyzed without extended storage. However, conformational stability was lower at pH 3.8 than pH 6.0. All charge variants showed similar apparent melting temperature at pH 6.0. In contrast, at pH 3.8 variants A3, A5, B2, B3 and B4 display lower Tm, suggesting reduced conformational stability. Further, A2, A3 and A5 exhibit reduced colloidal stability at pH 3.8. In general, acidic variants are more prone to aggregation than basic variants.

CONCLUSION

Typical industry practice today is to examine in-process intermediate stability with acidic species and basic species taken as a single category each. We suggest that perhaps stability evaluation needs to be performed at specie level as different acidic or basic species have different stability and this knowledge can be used for clever designing of the downstream process to achieve a stable product.

Concentration-Dependent Diffusion of Monoclonal Antibodies: Underlying Mechanisms of Anomalous Diffusion

The development, storage, transport, and subcutaneous delivery of highly concentrated monoclonal antibody formulations pose significant challenges due to the high solution viscosity and low diffusion of the antibody molecules in crowded environments. These issues often stem from the self-associating behavior of the antibody molecules, potentially leading to aggregation. In this work, we used a dissipative particle dynamics-based coarse-grained model to investigate the diffusion behavior of IgG1 antibody molecules in aqueous solutions with 15 and 32 mM NaCl and antibody concentrations ranging from 10 to 400 mg/mL. We determined the coarse-grained interaction parameters by matching the calculated structure factor with the computational and experimental data from the literature. Our results indicate Fickian diffusion for antibody concentrations of 10 and 25 mg/mL and anomalous diffusion for concentrations exceeding 50 mg/mL. The anomalous diffusion was observed for ∼0.33 to 0.4 μs, followed by Fickian diffusion for all antibody concentrations. We observed a strong linear correlation between the diffusion behavior of the antibody molecules (diffusion coefficient D and anomalous diffusion exponent α) and the amount of aggregates present in the solution and between the amount of aggregates and the Coulomb interaction energy. The investigation of underlying mechanisms for anomalous diffusion revealed that in crowded environments at high antibody concentrations, the attractive interaction between electrostatically complementary regions of the antibody molecules could further bring the neighboring molecules closer to one another, ultimately resulting in aggregate formation. Further, the Coulomb attraction can continue to draw more molecules together, forming larger aggregates.

Exploring the Combined Action of Adding Pertuzumab to Branded Trastuzumab versus Trastuzumab Biosimilars for Treating HER2+ Breast Cancer

The binding activity of various trastuzumab biosimilars versus the branded trastuzumab towards the glycosylated extracellular domain of the human epidermal growth factor receptor 2 (HER2) target in the presence of pertuzumab was investigated. We employed size exclusion chromatography with tetra-detection methodology to simultaneously determine absolute molecular weight, concentration, molecular size, and intrinsic viscosity. All trastuzumab molecules in solution exhibit analogous behavior in their binary action towards HER2 regardless of the order of addition of trastuzumab/pertuzumab. This analogous behavior of all trastuzumab molecules, including biosimilars, highlights the robustness and consistency of their binding activity towards HER2. Furthermore, the addition of HER2 to a mixture of trastuzumab and pertuzumab leads to increased formation of high-order HER2 complexes, up to concentrations of one order of magnitude higher than in the case of sequential addition. The observed increase suggests a potential synergistic effect between these antibodies, which could enhance their therapeutic efficacy in HER2-positive cancers. These findings underscore the importance of understanding the complex interplay between therapeutic antibodies and their target antigens, providing valuable insights for the development of more effective treatment strategies.

Impact of Glycosylation on Protein-Protein Self-Interactions of Monoclonal Antibodies

Protein self-interactions measured via second osmotic virial coefficients (B22) and dynamic light scattering interaction parameter values (kD) are often used as metrics for assessing the favorability of protein candidates and different formulations during monoclonal antibody (MAb) product development. Model predictions of B22 or kD typically do not account for glycans, though glycosylation can potentially impact experimental MAb self-interactions. To the best of our knowledge, the impact of MAb glycosylation on the experimentally measured B22 and kD values has not yet been reported. B22 and kD values of two fully deglycosylated MAbs and their native (i.e., fully glycosylated) counterparts were measured by light scattering over a range of pH and ionic strength conditions. Significant differences between B22 and kD of the native and deglycosylated forms were observed at a range of low to high ionic strengths used to modulate the effect of electrostatic contributions. Differences were most pronounced at low ionic strength, indicating that electrostatic interactions are a contributing factor. Though B22 and kD values were statistically equivalent at high ionic strengths where electrostatics were fully screened, we observed protein-dependent qualitative differences, which indicate that steric interactions may also play a role in the observed B22 and kD differences. A domain-level coarse-grained molecular model accounting for charge differences was considered to potentially provide additional insight but was not fully predictive of the behavior across all of the solution conditions investigated. This highlights that both the level of modeling and lack of inclusion of glycans may limit existing models in making quantitatively accurate predictions of self-interactions.

Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations

Monoclonal antibodies (mAbs) are an important modality of protein therapeutics with broad applications for numerous diseases. However, colloidal instabilities occurring at high protein concentrations can limit the ability to develop stable, high-concentration liquid dosage forms that are required for patient-centric, device-mediated products. Therefore, it is advantageous to identify colloidally stable mAbs early in the discovery process to ensure that they are selected for development. Experimental screening for colloidal stability can be time- and resource-consuming and is most feasible at the later stages of drug development due to material requirements. Alternatively, computational approaches have emerging potential to provide efficient screening and focus developmental efforts on mAbs with the greatest developability potential, while providing mechanistic relationships for colloidal instability. In this work, coarse-grained, molecular-scale models were fine-tuned to screen for colloidal stability at amino-acid resolution. This model parameterization provides a framework to screen for mAb self-interactions and extrapolate to bulk solution behavior. This approach was applied to a wide array of mAbs under multiple buffer conditions, demonstrating the utility of the presented computational approach to augment early candidate screening and later formulation strategies for protein therapeutics.

Improved Diffusion Interaction Parameter Measurement to Predict the Viscosity of Concentrated mAb Solutions

During the developability assessment of therapeutic monoclonal antibody (mAb) candidates, utilization of robust high-throughput predictive assays enables rapid selection of top candidates with low risks for late-stage development. Predicting the viscosities of highly concentrated mAbs using limited materials is an important aspect of developability assessment because high viscosity can complicate manufacturability, stability, and administration. Here, we report a high-throughput assay measuring protein-protein interactions to predict mAb viscosity. The diffusion interaction parameter (kD) measures colloidal self-association in dilute solutions and has been reported to be predictive of the mAb viscosity at high concentrations. However, kD of Amgen early stage IgG1 mAb candidates measured in 10 mM acetate at pH 5.2 containing sucrose and polysorbate (denoted A52SuT) shows only weak correlation to their viscosities at 140 mg/mL in A52SuT. We hypothesize that kD measured in A52SuT reflects primarily long-range electrostatic repulsions because most of these mAb candidates carry strong net positive charges in this low ionic strength formulation with pH (5.2) well below pI values of mAb candidates. However, the viscosities of high concentration mAbs depend heavily on short-range molecular interactions. We propose an improved kD method in which salt is added to suppress charge repulsions and to allow for detection of key short-range interactions in dilute solutions. Salt types and salt concentrations were screened, and an optimal salt condition was identified. This optimized method was further validated using two test mAb sets. Overall, the method improves the Pearson R2 between kD and viscosity (6-230 cP) from 0.24 to 0.80 for a data set consisting of 37 mAbs.

Role of Domain-Domain Interactions on the Self-Association and Physical Stability of Monoclonal Antibodies: Effect of pH and Salt

Monoclonal antibodies (mAbs) make up a major class of biotherapeutics with a wide range of clinical applications. Their physical stability can be affected by various environmental factors. For instance, an acidic pH can be encountered during different stages of the mAb manufacturing process, including purification and storage. Therefore, understanding the behavior of flexible mAb molecules in acidic solution environments will benefit the development of stable mAb products. This study used small-angle X-ray scattering (SAXS) and complementary biophysical characterization techniques to investigate the conformational flexibility and protein-protein interactions (PPI) of a model mAb molecule under near-neutral and acidic conditions. The study also characterized the interactions between Fab and Fc fragments under the same buffer conditions to identify domain-domain interactions. The results suggest that solution pH significantly influences mAb flexibility and thus could help mAbs remain physically stable by maximizing local electrostatic repulsions when mAbs become crowded in solution. Under acidic buffer conditions, both Fab and Fc contribute to the repulsive PPI observed among the full mAb at a low ionic strength. However, as ionic strength increases, hydrophobic interactions lead to the self-association of Fc fragments and, subsequently, could affect the aggregation state of the mAb.

Experimental support for reclassification of the light scattering second virial coefficient from macromolecular solutions as a hydrodynamic parameter

This investigation examines the source of the disparity between experimental values of the light scattering second virial coefficient [Formula: see text] (mL.mol/g2) for proteins and those predicted on the statistical mechanical basis of excluded volume. A much better theoretical description of published results for lysozyme is obtained by considering the experimental parameters to monitor the difference between the thermodynamic excluded volume term and its hydrodynamic counterpart. This involves a combination of parameters quantifying concentration dependence of the translational diffusion coefficient obtained from dynamic light scattering measurements. That finding is shown to account for observations of a strong correlation between [Formula: see text] (mL/g), where M2 is the molar mass (molecular weight) of the macromolecule and the diffusion concentration parameter [Formula: see text] (mL/g). On the grounds that [Formula: see text] is regarded as a hydrodynamic parameter, the same status should be accorded the light scattering second virial coefficient rather than its current incorrect thermodynamic designation as [Formula: see text] (mL.mol/g2), or just B, the osmotic second virial coefficient for protein self-interaction.

Predictive Nature of High-Throughput Assays in ADC Formulation Screening

Utilization of high-throughput biophysical screening techniques during early screening studies is warranted due to the limited amount of material and large number of samples. But the predictability of the data to longer-term storage stability is critical as the high-throughput methods assist in defining the design space for the longer-term studies. In this study, the biophysical properties of two ADCs in 16 formulation conditions were evaluated using high-throughput techniques. Conformational stability and colloidal stability were evaluated by determining Tm values, kD, B22, and Tagg. In addition, the samples were placed on stability and the extent of aggregate formation over the 8-week interval was determined. The rank order of the 16 different formulations in the high-throughput assays was compared to the rank order observed during the stability studies to assess the predictive capabilities of the screening methods. It was demonstrated that similar rank orders can be expected between high-throughput physical stability indicating assays such as Tagg and B22 and traditional aggregation by SEC data, whereas conformational stability read-outs (Tm) are less predictive. In addition, the high-throughput assays appropriately identified the poor performing formulation conditions, which is ultimately what is desired of screening assays.

Blueprint for antibody biologics developability

Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Technology development to evaluate the effectiveness of viscosity reducing excipients

Addition of pharmaceutical excipients is a commonly used approach to decrease the viscosity of highly concentrated protein formulations, which otherwise could not be subcutaneously injected or processed. The variety of protein-protein interactions, which are responsible for increased viscosities, makes a portfolio approach necessary. Screening of several excipients to develop such a portfolio is time and money consuming in industrial settings. Responsible protein-protein interactions were investigated using the interaction parameter k_D obtained from dynamic light scattering measurements in the studies presented herein. Together with in-silico calculated excipient parameter, k_D could be used as a screening tool accelerating screening and formulation development as k_D is suitable to high-throughput formats using small quantities of protein and low concentrations. A qualitative correlation between k_D and high-concentration viscosity behavior could be shown in our case.

Biosimilar monoclonal antibodies: Challenges and approaches towards formulation

Many biologic drug products, particularly monoclonal antibodies (mAbs), were off-patented between 2015 and 2020, and this process is continuing as the number of biologics approvals has increased. However, the availability of affordable biosimilars is delayed by secondary patents related to the formulation and manufacturing process. Therefore, an alternative formulation development is required to avoid infringement of formulation related patents. Several variables must be considered while developing alternative non-infringement formulations, including the time gap between the expiration of the molecule patent and the formulation patent, the ability not to infringe other secondary patents (process-related), and project timelines. As a part of life cycle management, innovator companies are adopting multiple strategies to delay biosimilar competition. Biosimilar companies could use the innovator formulation knowledge space to develop alternative formulations at the expense of time and cost. The present review discusses the key approaches in biosimilar formulation development, and further summarizes the use of innovator formulation knowledge space for biosimilar mAbs product development.

Use of Debye-Hückel-Henry charge measurements in early antibody development elucidates effects of non-specific association

The diffusion interaction parameter (kD) has been demonstrated to be a high-throughput technique for characterizing interactions between proteins in solution. kD reflects both attractive and repulsive interactions, including long-ranged electrostatic repulsions. Here, we plot the mutual diffusion coefficient (Dm) as a function of the experimentally determined Debye-Hückel-Henry surface charge (ZDHH) for seven human monoclonal antibodies (mAbs) in 15 mM histidine, pH 6. We find that graphs of Dm versus ZDHH intersect at ZDHH, ~ 2.6, independent of protein concentration. The same data plotted as kD vs. ZDHH shows a transition from net attractive to net repulsive interactions in the same region of the ZDHH intersection point. These data suggest that there is a minimum surface charge necessary on these mAbs needed to overcome attractive interactions.

Antibody-Incorporated Nanomedicines for Cancer Therapy

Antibody-based cancer therapy, one of the most significant therapeutic strategies, has achieved considerable success and progress over the past decades. Nevertheless, obstacles including limited tumor penetration, short circulation half-lives, undesired immunogenicity, and off-target side effects remain to be overcome for the antibody-based cancer treatment. Owing to the rapid development of nanotechnology, antibody-containing nanomedicines that have been extensively explored to overcome these obstacles have already demonstrated enhanced anticancer efficacy and clinical translation potential. This review intends to offer an overview of the advancements of antibody-incorporated nanoparticulate systems in cancer treatment, together with the nontrivial challenges faced by these next-generation nanomedicines. Diverse strategies of antibody immobilization, formats of antibodies, types of cancer-associated antigens, and anticancer mechanisms of antibody-containing nanomedicines are provided and discussed in this review, with an emphasis on the latest applications. The current limitations and future research directions on antibody-containing nanomedicines are also discussed from different perspectives to provide new insights into the construction of anticancer nanomedicines.

Process- and Product-Related Foulants in Virus Filtration

Regulatory authorities place stringent guidelines on the removal of contaminants during the manufacture of biopharmaceutical products. Monoclonal antibodies, Fc-fusion proteins, and other mammalian cell-derived biotherapeutics are heterogeneous molecules that are validated based on the production process and not on molecular homogeneity. Validation of clearance of potential contamination by viruses is a major challenge during the downstream purification of these therapeutics. Virus filtration is a single-use, size-based separation process in which the contaminating virus particles are retained while the therapeutic molecules pass through the membrane pores. Virus filtration is routinely used as part of the overall virus clearance strategy. Compromised performance of virus filters due to membrane fouling, low throughput and reduced viral clearance, is of considerable industrial significance and is frequently a major challenge. This review shows how components generated during cell culture, contaminants, and product variants can affect virus filtration of mammalian cell-derived biologics. Cell culture-derived foulants include host cell proteins, proteases, and endotoxins. We also provide mitigation measures for each potential foulant.

Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties

The widespread interest in antibody therapeutics has led to much focus on identifying antibody candidates with favorable developability properties. In particular, there is broad interest in identifying antibody candidates with highly repulsive self-interactions in standard formulations (e.g., low ionic strength buffers at pH 5-6) for high solubility and low viscosity. Likewise, there is also broad interest in identifying antibody candidates with low levels of non-specific interactions in physiological solution conditions (PBS, pH 7.4) to promote favorable pharmacokinetic properties. To what extent antibodies that possess both highly repulsive self-interactions in standard formulations and weak non-specific interactions in physiological solution conditions can be systematically identified remains unclear and is a potential impediment to successful therapeutic drug development. Here, we evaluate these two properties for 42 IgG1 variants based on the variable fragments (Fvs) from four clinical-stage antibodies and complementarity-determining regions from 10 clinical-stage antibodies. Interestingly, we find that antibodies with the strongest repulsive self-interactions in a standard formulation (pH 6 and 10 mM histidine) display the strongest non-specific interactions in physiological solution conditions. Conversely, antibodies with the weakest non-specific interactions under physiological conditions display the least repulsive self-interactions in standard formulations. This behavior can be largely explained by the antibody isoelectric point, as highly basic antibodies that are highly positively charged under standard formulation conditions (pH 5-6) promote repulsive self-interactions that mediate high colloidal stability but also mediate strong non-specific interactions with negatively charged biomolecules at physiological pH and vice versa for antibodies with negatively charged Fv regions. Therefore, IgG1s with weakly basic isoelectric points between 8 and 8.5 and Fv isoelectric points between 7.5 and 9 typically display the best combinations of strong repulsive self-interactions and weak non-specific interactions. We expect that these findings will improve the identification and engineering of antibody candidates with drug-like biophysical properties.

Utility of High Resolution 2D NMR Fingerprinting in Assessing Viscosity of Therapeutic Monoclonal Antibodies

Purpose

The viscosity of highly concentrated therapeutic monoclonal antibody (mAb) formulations at concentrations ≥ 100 mg/mL can significantly affect the stability, processing, and drug product development for subcutaneous delivery. An early identification of a viscosity prone mAb during candidate selection stages are often beneficial for downstream processes. Higher order structure of mAbs may often dictate their viscosity behavior at high concentration. Thus it is beneficial to gauge or rank-order their viscosity behavior using noninvasive structural fingerprinting methods and to potentially screen for suitable viscosity lowering excipients.

Methods

In this study, Dynamic Light Scattering (DLS) and 2D NMR based methyl fingerprinting were used to correlate viscosity behavior of a set of Pfizer mAbs. The viscosities of mAbs were determined. Respective Fab and Fc domains were generated for studies.

Result

Methyl fingerprinting of intact mAbs allows for differentiation of viscosity prone mAbs from well behaved ones even at 30–40 mg/ml, where bulk viscosity of the solutions are near identical. For viscosity prone mAbs, peak broadening and or distinct chemical shift changes were noted in intact and fragment fingerprints, unlike the well-behaved mAbs, indicative of protein protein interactions (PPI).

Conclusion

Fab-Fab or Fab-Fc interactions may lead to formation of protein networks at high concentration. The early transients to these network formation may be manifested through peak broadening or peak shift in the 2D NMR spectrum of mAb/mAb fragments. Such insights go beyond rank ordering mAbs based on viscosity behavior, which can be obtained by other methods as well..

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03200-6.

Proteins on the rack: Mechanistic studies on protein particle formation during peristaltic pumping

Peristaltic pumping can cause protein particle formation. The expected causes were unfolding by heat in the pump head, oxidative stress by cavitation generated during roller movement, interfacial adsorption to the tubing wall and mechanical stress by stretching of the tubing itself. The pump head reached 28°C during experiments stayed well below the onset of the melting point of the proteins. Thus, heat may only be a relevant root cause for proteins containing domains with very low unfolding temperature. Analysis by terephthalic acid dosimetry and protein oxidation via RP-HPLC ruled out major induction of reactive hydroxyl radicals by pumping, indicating that cavitation does not play a significant role in particle generation. Addition of surfactants suppresses protein adsorption to the tubing wall and drastically reduced protein particle formation. This indicates that interfacial protein adsorption is a key element. Repeated stretching of tubing filled with protein solution led to the formation of protein particles, demonstrating that expansion and compression of the protein film on the tubing surface is the second key component for particle formation. Thus, protein particle generation during peristaltic pumping originates from the formation of a protein film on the tubing surface which gets stretched and compressed, leading to film fragments entering the bulk solution. This interplay of protein film formation and its rupture has been also observed at liquid/liquid or liquid/air interfaces.

Dipolar Interactions and Protein Hydration in Highly Concentrated Antibody Formulations

Molecular interaction mechanisms in high-concentrated protein systems are of fundamental importance for the rational development of biopharmaceuticals such as monoclonal antibody (mAb) formulations. In such high-concentrated protein systems, the intermolecular distances between mAb molecules are reduced to the size of the protein diameter (approx. 10 nm). Thus, protein-protein interactions are more pronounced at high concentrations; so a direct extrapolation of physicochemical properties obtained from measurements at a low protein concentration of the corresponding properties at a high protein concentration is highly questionable. Besides the charge-charge interaction, the effects of molecular crowding, dipolar interaction, changes in protein hydration, and self-assembling tendency become more relevant. Here, protein hydration, protein dipole moment, and protein-protein interactions were studied in protein concentrations up to 200 mg/mL (= 1.3 mM) in different formulations for selected mAbs using dielectric relaxation spectroscopy (DRS). These data are correlated with the second virial coefficient, A₂, the diffusion interaction parameter, k_D, the elastic shear modulus, G', and the dynamic viscosity, η. When large contributions of dipolar protein-protein interactions were observed, the tendency of self-assembling and an increase in solution viscosity were detected. These effects were examined using specific buffer conditions. Furthermore, different types of protein-water interactions were identified via DRS, whereby the effect of high protein concentration on protein hydration was investigated for different high-concentrated liquid formulations (HCLFs).

Measuring Self-Association of Antibody Lead Candidates with Dynamic Light Scattering

In this method chapter, we provide a brief overview of the key methods available to measure self-association of monoclonal antibodies (mAbs) and explain for which experimental throughputs they are usually applied. We then focus on dynamic light scattering (DLS) and describe experimental details on how to measure the diffusion interaction parameter (k_D) which is occasionally referred to as the gold standard for measuring self-association of proteins. The k_D is a well-established parameter to predict solution viscosity, which is one of the most critical developability parameters of mAbs. Finally, we present a pH and excipient screen that is designed to measure self-association with DLS under conditions that are relevant for bioprocessing and formulation of mAbs. The presented light scattering methods are well suited for lead candidate selections where it is essential to select mAbs with high developability potential for progression toward first human dose.

Probing interactions of therapeutic antibodies with serum via second virial coefficient measurements

Antibody-based therapeutics are the fastest-growing drug class on the market, used to treat aggressive forms of cancer, chronic autoimmune conditions, and numerous other disease states. Although the specificity, affinity, and versatility of therapeutic antibodies can provide an advantage over traditional small-molecule drugs, their development and optimization can be much more challenging and time-consuming. This is, in part, because the ideal formulation buffer systems used for in vitro characterization inadequately reflect the crowded biological environments (serum, endosomal lumen, etc.) that these drugs experience once administered to a patient. Such environments can perturb the binding of antibodies to their antigens and receptors, as well as homo- and hetero-aggregation, thereby altering therapeutic effect and disposition in ways that are incompletely understood. Although excluded volume effects are classically thought to favor binding, weak interactions with co-solutes in crowded conditions can inhibit binding. The second virial coefficient (B₂) parameter quantifies such weak interactions and can be determined by a variety of techniques in dilute solution, but analogous methods in complex biological fluids are not well established. Here, we demonstrate that fluorescence correlation spectroscopy is able to measure diffusive B₂-values directly in undiluted serum. Apparent second virial coefficient (B_2,app) measurements of antibodies in serum reveal that changes in the balance between attractive and repulsive interactions can dramatically impact global nonideality. Furthermore, our findings suggest that the approach of isolating specific components and completing independent cross-term virial coefficient measurements may not be an effective approach to characterizing nonideality in serum. The approach presented here could enrich our understanding of the effects of biological environments on proteins in general and advance the development of therapeutic antibodies and other protein-based therapeutics.

Toward a Suite of Coarse-Grained Models for Molecular Simulation of Monoclonal Antibodies and Therapeutic Proteins

A series of coarse-grained models for molecular simulation of proteins are considered, with emphasis on the application of predicting protein-protein self-interactions for monoclonal antibodies (MAbs). As an illustrative example and for quantitative comparison, the models are used to predict osmotic virial coefficients over a broad range of attractive and repulsive self-interactions and solution conditions for a series of MAbs where the second osmotic virial coefficient has been experimentally determined in prior work. The models are compared based on how well they can predict experimental behavior, their computational burdens, and scalability. An intermediate-resolution model is also introduced that can capture specific electrostatic interactions with improved efficiency and similar or improved accuracy when compared to the previously published models. Guidance is included for the selection of coarse-grained models more generally for capturing a balance of electrostatic, steric, and short-ranged nonelectrostatic interactions for proteins from low to high concentrations.

High-Throughput Screening for Colloidal Stability of Peptide Formulations Using Dynamic and Static Light Scattering

Selection of an appropriate formulation to stabilize therapeutic proteins against aggregation is one of the most challenging tasks in early-stage drug product development. The amount of aggregates is more difficult to quantify in the case of peptides due to their small molecular size. Here, we investigated the suitability of diffusion self-interaction parameters (k_D) and osmotic second virial coefficients (B₂₂) for high-throughput (HT) screening of peptide formulations regarding their aggregation risk. These parameters were compared to the effect of thermal stress on colloidal stability. The formulation matrix comprised six buffering systems at two selected pH values, four tonicity agents, and a common preservative. The results revealed that electrostatic interactions are the main driver to control colloidal stability. Preferred formulations consisted of acetate and succinate buffer at pH 4.5 combined with glycerol or mannitol and optional m-cresol. k_D proved to be a suitable surrogate for B₂₂ as an indicator of high colloidal stability in the case of peptides as was previously described for globular proteins and antibodies. Formulation assessment solely based on k_D obtained by HT methods offers important insights into the optimization of colloidal stability during the early development of peptide-based liquid formulations and can be performed with a limited amount of peptide (∼360 mg).

Application of Affinity-Capture Self-Interaction Nanoparticle Spectroscopy in Predicting Protein Stability, Especially for Co-Formulated Antibodies

PURPOSE

From traditional monoclonal antibodies to more and more complex mAb-based formulations, biopharmaceutical faces one challenge after another. To avoid these issues, identification of therapeutic proteins in the initial discovery process that has high stability and low self-interaction would simplify the development of safe and effective antibody therapeutics.

METHOD

Affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) is a new prediction method capable of identifying mAbs with different self-association propensity. In this study, 10 formulated monoclonal antibody (mAb) therapeutics include different mAb isotypes and co-formulated antibodies were measured by AC-SINS and some biophysical methods to predict protein stability. The prediction results of all 10 mAbs were compared to their stability data (Δ%monomer and Δ%HMWs) at accelerated (25°C and 40°C) and long-term storage conditions (4°C) as measured by size exclusion chromatography.

RESULT

AC-SINS method has a good predictive correlation with each mAbs and co-formulated antibodies. There were no physicochemical, intermolecular, or biological interactions that occurred between the two components of co-formulated antibodies which confirmed by Analytical ultracentrifugation (AUC).

CONCLUSION

Here we discuss the correlation between each method and protein stability, and also use AC-SINS assay to predict the stability of co-formulated antibodies for the first time. This may be an effective way to predict the stability of these complex mAb-based formulations such as co-formulated mAbs.

Global multi-method analysis of interaction parameters for reversibly self-associating macromolecules at high concentrations

Weak macromolecular interactions assume a dominant role in the behavior of highly concentrated solutions, and are at the center of a variety of fields ranging from colloidal chemistry to cell biology, neurodegenerative diseases, and manufacturing of protein drugs. They are frequently measured in different biophysical techniques in the form of second virial coefficients, and nonideality coefficients of sedimentation and diffusion, which may be related mechanistically to macromolecular distance distributions in solution and interparticle potentials. A problem arises for proteins where reversible self-association often complicates the concentration-dependent behavior, such that grossly inconsistent coefficients are measured in experiments based on different techniques, confounding quantitative conclusions. Here we present a global multi-method analysis that synergistically bridges gaps in resolution and sensitivity of orthogonal techniques. We demonstrate the method with a panel of monoclonal antibodies exhibiting different degrees of self-association. We show how their concentration-dependent behavior, examined by static and dynamic light scattering and sedimentation velocity, can be jointly described in a self-consistent framework that separates nonideality coefficients from self-association properties, and thereby extends the quantitative interpretation of nonideality coefficients to probe dynamics in highly concentrated protein solutions.

Characterization and Modeling of Reversible Antibody Self-Association Provide Insights into Behavior, Prediction, and Correction

Reversible antibody self-association, while having major developability and therapeutic implications, is not fully understood or readily predictable and correctable. For a strongly self-associating humanized mAb variant, resulting in unacceptable viscosity, the monovalent affinity of self-interaction was measured in the low μM range, typical of many specific and biologically relevant protein-protein interactions. A face-to-face interaction model extending across both the heavy-chain (HC) and light-chain (LC) Complementary Determining Regions (CDRs) was apparent from biochemical and mutagenesis approaches as well as computational modeling. Light scattering experiments involving individual mAb, Fc, Fab, and Fab'2 domains revealed that Fabs self-interact to form dimers, while bivalent mAb/Fab'2 forms lead to significant oligomerization. Site-directed mutagenesis of aromatic residues identified by homology model patch analysis and self-docking dramatically affected self-association, demonstrating the utility of these predictive approaches, while revealing a highly specific and tunable nature of self-binding modulated by single point mutations. Mutagenesis at these same key HC/LC CDR positions that affect self-interaction also typically abolished target binding with notable exceptions, clearly demonstrating the difficulties yet possibility of correcting self-association through engineering. Clear correlations were also observed between different methods used to assess self-interaction, such as Dynamic Light Scattering (DLS) and Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS). Our findings advance our understanding of therapeutic protein and antibody self-association and offer insights into its prediction, evaluation and corrective mitigation to aid therapeutic development.

Identification of monoclonal antibody variants involved in aggregate formation - Part 2: Hydrophobicity variants

Monoclonal antibodies (mAbs) are valuable tools both in therapy and in diagnostic. Their tendency to aggregate is a serious concern. Since a mAb drug substance (DS) is composed of different variants, it is important for manufacturers to know the behavior and stability not only of the mAb as a whole, but also of the variants contained in the product. We present a method to separate hydrophobicity variants of a mAb and subsequently analyzed these variants for stability and aggregation propensity. We identified a potentially aggregation prone hydrophilic variant which is interrelated with another previously identified aggregation prone acidic charge variant. Additionally, we assessed the risk posed by the aggregation prone variant to the DS by spiking hydrophobicity variants into DS and did not observe an enhanced aggregation propensity. Thus we present an approach to separate, characterize and analyze the criticality of aggregation prone variants in protein DS which is a step forward to further assure drug safety.

Washing with alkaline solutions in protein A purification improves physicochemical properties of monoclonal antibodies

Protein A affinity chromatography has been widely used for both laboratory scale purification and commercial manufacturing of monoclonal antibodies and Fc-fusion proteins. Protein A purification is specific and efficient. However, there still remain several issues to be addressed, such as incomplete clearance of impurities including host cell proteins, DNA, aggregates, etc. In addition, the effects of wash buffers in protein A purification on the physicochemical characteristics of antibodies have yet to be fully understood. Here we found a new purification protocol for monoclonal antibodies that can improve physicochemical properties of monoclonal antibodies simply by inserting an additional wash step with a basic buffer after the capture step to the conventional protein A purification. The effects of the alkaline wash on monoclonal antibodies were investigated in terms of physicochemical characteristics, yields, and impurity clearance. The simple insertion of an alkaline wash step resulted in protection of antibodies from irreversible aggregation, reduction in free thiols and impurities, an improvement in colloidal and storage stability, and enhanced yields. This new procedure is widely applicable to protein A affinity chromatography of monoclonal antibodies.

Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods

There is intense and widespread interest in developing monoclonal antibodies as therapeutic agents to treat diverse human disorders. During early-stage antibody discovery, hundreds to thousands of lead candidates are identified, and those that lack optimal physical and chemical properties must be deselected as early as possible to avoid problems later in drug development. It is particularly challenging to characterize such properties for large numbers of candidates with the low antibody quantities, concentrations, and purities that are available at the discovery stage, and to predict concentrated antibody properties (e.g., solubility, viscosity) required for efficient formulation, delivery, and efficacy. Here we review key recent advances in developing and implementing high-throughput methods for identifying antibodies with desirable in vitro and in vivo properties, including favorable antibody stability, specificity, solubility, pharmacokinetics, and immunogenicity profiles, that together encompass overall drug developability. In particular, we highlight impressive recent progress in developing computational methods for improving rational antibody design and prediction of drug-like behaviors that hold great promise for reducing the amount of required experimentation. We also discuss outstanding challenges that will need to be addressed in the future to fully realize the great potential of using such analysis for minimizing development times and improving the success rate of antibody candidates in the clinic.

Temperature Dependence of Protein Solution Viscosity and Protein-Protein Interactions: Insights into the Origins of High-Viscosity Protein Solutions

Protein solution viscosity (η) as a function of temperature was measured at a series of protein concentrations under a range of formulation conditions for two monoclonal antibodies (MAbs) and a globular protein (aCgn). Based on theoretical arguments, a strong temperature dependence for protein-protein interactions (PPI) indicates highly anisotropic, short-ranged attractions that could lead to higher solution viscosities. The semi-empirical Ross-Minton model was used to determine the apparent intrinsic viscosity, shape, and "crowding" factors for each protein as a function of temperature and formulation conditions. The apparent intrinsic viscosity was independent of temperature for aCgn, while a slight decrease with increasing temperature was observed for the MAbs. The temperature dependence of solution viscosity was analyzed using the Andrade-Eyring equation to determine the effective activation energy of viscous flow (E_a,η). While E_a,η values were different for each protein, they were independent of formulation conditions for a given protein. PPI were quantified via the osmotic second virial coefficient (B₂₂) and the protein diffusion interaction parameter (k_D) as a function of temperature under the same formulation conditions as the viscosity measurements. Net interactions ranged from strongly attractive to repulsive by changing formulation pH and ionic strength for each protein. Overall, larger activation energies for PPI corresponded to larger activation energies for η, and those were predictive of the highest η values at higher protein concentrations.

Assessing the Structures and Interactions of γD-Crystallin Deamidation Variants

Cataracts involve the deposition of the crystallin proteins in the vertebrate eye lens, causing opacification and blindness. They are associated with either genetic mutation or protein damage that accumulates over the lifetime of the organism. Deamidation of Asn residues in several different crystallins has been observed and is frequently invoked as a cause of cataract. Here, we investigated the properties of Asp variants, deamidation products of γD-crystallin, by solution NMR, X-ray crystallography, and other biophysical techniques. No substantive structural or stability changes were noted for all seven Asn to Asp γD-crystallins. Importantly, no changes in diffusion interaction behavior could be detected. Our combined experimental results demonstrate that introduction of single Asp residues on the surface of γD-crystallin by deamidation is unlikely to be the driver of cataract formation in the eye lens.

Freeze concentration during freezing: How does the maximally freeze concentrated solution influence protein stability?

During freeze drying of biologics, a highly viscous freeze concentrate (FC) is formed upon the initial freezing due to the crystallisation of ice. Protein stability in this freeze concentrated phase is not yet well understood, but can decide upon the success of the lyophilisation itself. Protein stability may be high below the T_g' as it is typically the case during primary drying but decreases above T_g', e.g. during annealing or during aggressive freeze drying above T_g' in presence of a crystalline bulking agent or, beyond freeze drying, during storage of frozen bulk. Different FCs containing monoclonal antibody, sucrose, histidine or phosphate buffer and sodium chloride were prepared via partial freeze drying and analysed for protein aggregation. No solute crystallisation is visible and the systems are vitrifying during cooling. Increasing sugar or buffer concentration showed positive effects on either melting and aggregation temperature or on protein self-interaction as indicated by A₂ values. Protein integrity in the FC was not affected by 1 month storage at temperatures above T_g'. Thus, upconcentration of solutes during freezing does not negatively impact protein stability. Exceeding T_g' during freeze drying e.g. upon annealing or, intentionally or unintentionally, during primary drying does not lead to protein aggregation.

Mitigation of liquid-liquid phase separation of a monoclonal antibody by mutations of negative charges on the Fab surface

Some monoclonal antibodies undergo liquid-liquid phase separation owing to self-attractive associations involving electrostatic and other soft interactions, thereby rendering monoclonal antibodies unsuitable as therapeutics. To mitigate the phase separation, formulation optimization is often performed. However, this is sometimes unsuccessful because of the limited time for the development of therapeutic antibodies. Thus, protein mutations with appropriate design are required. In this report, we describe a case study involving the design of mutants of negatively charged surface residues to reduce liquid-liquid phase separation propensity. Physicochemical analysis of the resulting mutants demonstrated the mutual correlation between the sign of second virial coefficient B2, the Fab dipole moment, and the reduction of liquid-liquid phase separation propensity. Moreover, both the magnitude and direction of the dipole moment appeared to be essential for liquid-liquid phase separation propensity, where electrostatic interaction was the dominant mechanism. These findings could contribute to a better design of mutants with reduced liquid-liquid phase separation propensity and improved drug-like biophysical properties.

In-Use Interfacial Stability of Monoclonal Antibody Formulations Diluted in Saline i.v. Bags

The use of monoclonal antibodies (mAbs) for the treatment of a variety of diseases is rapidly growing each year. Many mAbs are administered intravenously using i.v. bags containing 0.9% NaCl (normal saline). We studied the aggregation propensity of these antibody solutions in saline and compared it with a low ionic strength formulation buffer. The mAb studied in this work is prone to aggregate, and is known to form a viscoelastic network at the air-solution interface. We observed that this interfacial elasticity increased when formulated in saline. In the bulk, the mAbs exhibited a tendency to self-associate that was higher in saline. We also studied the aggregation of the mAbs in the presence of polysorbate-20, typically added to formulations to mitigate interfacial aggregation. We observed that with surfactants, the presence of salt in the buffer led to a greater mAb adsorption at the interface and resulted in the formation of more particulate aggregates. Our results show that the addition of salt to the buffer led to differences in the interfacial aggregation in mAb formulations, showing that stress studies used to screen for mAb aggregation intended for i.v. administration should be performed in conditions representative of their intended route of administration.

A single molecular descriptor to predict solution behavior of therapeutic antibodies

Despite the therapeutic success of monoclonal antibodies (mAbs), early identification of developable mAb drug candidates with optimal manufacturability, stability, and delivery attributes remains elusive. Poor solution behavior, which manifests as high solution viscosity or opalescence, profoundly affects the developability of mAb drugs. Using a diverse dataset of 59 mAbs, including 43 approved products, and an array of molecular descriptors spanning colloidal, conformational, charge-based, hydrodynamic, and hydrophobic properties, we show that poor solution behavior is prevalent (>30%) in mAbs and is singularly predicted (>90%) by the diffusion interaction parameter (k _D), a dilute-solution measure of colloidal self-interaction. No other descriptor, individually or in combination, was found to be as effective as k _D. We also show that well-behaved mAbs, a substantial subset of which bear high positive charge and pI, present no disadvantages with respect to pharmacokinetics in humans. Here, we provide a systematic framework with quantitative thresholds for selecting well-behaved therapeutic mAbs during drug discovery.

A Confirmation for the Positive Electric Charge of Bio-Molecular Motors through Utilizing a Novel Nano-Technology Approach In Vitro

Molecular motors are microtubule-based proteins which contribute to many cell functions, such as intracellular transportation and cell division. The details of the nature of the mutual interactions between motors and microtubules still needs to be extensively explored. However, electrostatic interaction is known as one of the key factors making motor-microtubule association possible. The association rate of molecular motors to microtubules is a way to observe and evaluate the charge of the bio-motors in vivo. Growing evidence indicates that microtubules with distinct structural compositions in terms of beta tubulin isotypes carry different charges. Therefore, the electrostatic-driven association rate of motors–microtubules, which is a base for identifying the charge of motors, can be more likely influenced. Here, we present a novel method to experimentally confirm the charge of molecular motors in vitro. The offered nanotechnology-based approach can validate the charge of motors in the absence of any cellular components through the observation and analysis of the changes that biomolecular motors can cause on the dynamic of charged microspheres inside a uniform electric field produced by a microscope slide-based nanocapacitor. This new in vitro experimental method is significant as it minimizes the intracellular factors that may interfere the electric charge that molecular motors carry.