Behavior of Monoclonal Antibodies: Relation Between the Second Virial Coefficient (B 2) at Low Concentrations and Aggregation Propensity and Viscosity at High Concentrations

Stability of Protein Pharmaceuticals: Recent Advances

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

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.

Quantifying Protein Shape to Elucidate Its Influence on Solution Viscosity in High-Concentration Electrolyte Solutions

Therapeutic proteins with a high concentration and low viscosity are highly desirable for subcutaneous and certain local injections. The shape of a protein is known to influence solution viscosity; however, the precise quantification of protein shape and its relative impact compared to other factors like charge-charge interactions remains unclear. In this study, we utilized seven model proteins of varying shapes and experimentally determined their shape factors (v) based on Einstein's viscosity theory, which correlate strongly with the ratios of the proteins' surface area to the 2/3 power of their respective volumes, based on protein crystal structures resolved experimentally or predicted by AlphaFold. This finding confirms the feasibility of computationally estimating protein shape factors from amino acid sequences alone. Furthermore, our results demonstrated that, in high-concentration electrolyte solutions, a more spherical protein shape increases the protein's critical concentration (C*), the transition concentration beyond which protein viscosity increases exponentially relative to concentration increases. In summary, our work elucidates protein shape as a key determinant of solution viscosity through quantitative analysis and comparison with other contributing factors. This provides insights into molecular engineering strategies to optimize the molecular design of therapeutic proteins, thus optimizing their viscosity.

Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins

Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.

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.

Exploring HCl-HCl interactions: QZVPP calculations, improved Lennard-Jones potential, and second virial coefficient analysis for thermodynamics and industrial applications

In this paper, we present a comprehensive analysis of HCl-HCl interactions, including QZVPP calculations, energy fitting, conformation validation, and the determination of the second virial coefficient B using improved Lennard-Jones (ILJ) potential parameters. To acquire accurate interaction energies, initial QZVPP calculations are performed on approximately 1851 randomly generated HCl-HCl conformations. Then, these energies are used to fit an improved Lennard-Jones potential energy surface, allowing for a robust description of HCl-HCl interactions. The ILJ potential parameters are then used to validate particular HCl dimer conformations, ensuring their stability and consistency with experimental observations. The correlation between calculated and experimental conformations strengthens the validity of the ILJ potential parameters. In addition, the second viral coefficient B is calculated at various temperatures using the ILJ potential. The obtained B values are compared to experimental data, demonstrating close agreement, and validating the ILJ potential's ability to accurately capture the intermolecular interactions and gas-phase behavior of the HCl-HCl system. The results of this study demonstrate the effective implementation of QZVPP calculations, energy fitting, and ILJ potential parameters in validating HCl-HCl conformations and accurately determining the second virial coefficient B. The high degree of concordance between calculated B values and experimental data demonstrates the validity of the ILJ potential and its suitability for modeling HCl-HCl interactions. This research contributes to a greater comprehension of HCl-HCl interactions and their implications for numerous chemical and atmospheric processes. The validated conformations, energy fitting method, and calculated second virial coefficients provide valuable instruments for future research and pave the way for more accurate modeling and simulations of HCl-HCl systems.

A comprehensive evaluation of arginine and its derivatives as protein formulation stabilizers

Arginine and its derivatives (such as arginine ethyl ester and acetyl arginine) have varying degrees of protein aggregation suppressor effect across different protein solutions. To understand this performance ambiguity, we evaluated the activity of arginine, acetyl arginine, and arginine ethyl ester for aggregation suppressor effect against human intravenous immunoglobulin G (IgG) solution at pH 4.8. Both arginine and its cationic derivative arginine ethyl ester in their hydrochloride salt forms significantly reduced the colloidal and conformational stability (reduced kd and Tm) of IgG. Consequently, the monomer content was decreased with an increase in subvisible particulates after agitation or thermal stress. Furthermore, compared to arginine, arginine ethyl ester with one more cationic charge and hydrochloride salt form readily precipitated IgG at temperatures higher than 25 °C. On the contrary, acetyl arginine, which mostly exists in a neutral state at pH 4.8, efficiently suppressed the formation of subvisible particles retaining a high amount of monomer owing to its higher colloidal and conformational stability. Concisely, the charged state of additives significantly impacts protein stability. This study demonstrated that contrary to popular belief, arginine and its derivatives may either enhance or suppress protein aggregation depending on their net charge and concentration.

Application of Formulation Principles to Stability Issues Encountered During Processing, Manufacturing, and Storage of Drug Substance and Drug Product Protein Therapeutics

The field of formulation and stabilization of protein therapeutics has become rather extensive. However, most of the focus has been on stabilization of the final drug product. Yet, proteins experience stress and degradation through the manufacturing process, starting with fermentaition. This review describes how formulation principles can be applied to stabilize biopharmaceutical proteins during bioprocessing and manufacturing, considering each unit operation involved in prepration of the drug substance. In addition, the impact of the container on stabilty is discussed as well.

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.

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.

Chemometrics in Protein Formulation: Stability Governed by Repulsion and Protein Unfolding

Therapeutic proteins can be challenging to develop due to their complexity and the requirement of an acceptable formulation to ensure patient safety and efficacy. To date, there is no universal formulation development strategy that can identify optimal formulation conditions for all types of proteins in a fast and reliable manner. In this work, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients. Multivariate data analysis and chemometrics were used to analyze the data in an unbiased way. First, observed changes in stability were primarily determined by the individual protein. Second, pH and ionic strength are the two most important factors determining the physical stability of proteins, where there exists a significant statistical interaction between protein and pH/ionic strength. Additionally, we developed prediction methods by partial least-squares regression. Colloidal stability indicators are important for prediction of real-time stability, while conformational stability indicators are important for prediction of stability under accelerated stress conditions at 40 °C. In order to predict real-time storage stability, protein-protein repulsion and the initial monomer fraction are the most important properties to monitor.

An Intercompany Perspective on Practical Experiences of Predicting, Optimizing and Analyzing High Concentration Biologic Therapeutic Formulations

Developing high-dose biologic drugs for subcutaneous injection often requires high-concentration formulations and optimizing viscosity, solubility, and stability while overcoming analytical, manufacturing, and administration challenges. To understand industry approaches for developing high-concentration formulations, the Formulation Workstream of the BioPhorum Development Group, an industry-wide consortium, conducted an inter-company collaborative exercise which included several surveys. This collaboration provided an industry perspective, experience, and insight into the practicalities for developing high-concentration biologics. To understand solubility and viscosity, companies desire predictive tools, but experience indicates that these are not reliable and experimental strategies are best. Similarly, most companies prefer accelerated and stress stability studies to in-silico or biophysical-based prediction methods to assess aggregation. In addition, optimization of primary container-closure and devices are pursued to mitigate challenges associated with high viscosity of the formulation. Formulation strategies including excipient selection and application of studies at low concentration to high-concentration formulations are reported. Finally, analytical approaches to high concentration formulations are presented. The survey suggests that although prediction of viscosity, solubility, and long-term stability is desirable, the outcome can be inconsistent and molecule dependent. Significant experimental studies are required to confirm robust product definition as modeling at low protein concentrations will not necessarily extrapolate to high concentration formulations.

Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks

Solutions of monoclonal antibodies (mAbs) can show increased viscosity at high concentration, which can be a disadvantage during protein purification, filling, and administration. The viscosity is determined by protein-protein-interactions, which are influenced by the antibody's sequence as well as solution conditions, like pH, buffer type, or the presence of salts and other excipients. To predict viscosity, experimental parameters, like the diffusion interaction parameter (kD), or computational tools harnessing information derived from primary sequence, are often used, but a reliable predictive tool is still missing. We present a modeling approach employing artificial neural networks (ANNs) using experimental factors combined with simulation-derived parameters plus viscosity data from 27 highly concentrated (180 mg/mL) mAbs. These ANNs can be used to predict if mAbs exhibit problematic viscosity at distinct concentrations or to model viscosity-concentration-curves.

High concentration formulation developability approaches and considerations

The growing need for biologics to be administered subcutaneously and ocularly, coupled with certain indications requiring high doses, has resulted in an increase in drug substance (DS) and drug product (DP) protein concentrations. With this increase, more emphasis must be placed on identifying critical physico-chemical liabilities during drug development, including protein aggregation, precipitation, opalescence, particle formation, and high viscosity. Depending on the molecule, liabilities, and administration route, different formulation strategies can be used to overcome these challenges. However, due to the high material requirements, identifying optimal conditions can be slow, costly, and often prevent therapeutics from moving rapidly into the clinic/market. In order to accelerate and derisk development, new experimental and in-silico methods have emerged that can predict high concentration liabilities. Here, we review the challenges in developing high concentration formulations, the advances that have been made in establishing low mass and high-throughput predictive analytics, and advances in in-silico tools and algorithms aimed at identifying risks and understanding high concentration protein behavior.

NMR Reveals Functionally Relevant Thermally Induced Structural Changes within the Native Ensemble of G-CSF

Structure–function relationships in proteins refer to a trade-off between stability and bioactivity, molded by evolution of the molecule. Identifying which protein amino acid residues jeopardize global or local stability for the benefit of bioactivity would reveal residues pivotal to this structure–function trade-off. Here, we use ¹⁵N–¹H heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectroscopy to probe the microenvironment and dynamics of residues in granulocyte colony-stimulating factor (G-CSF) through thermal perturbation. From this analysis, we identified four residues (G4, A6, T133, and Q134) that we classed as significant to global stability, given that they all experienced large environmental and dynamic changes and were closely correlated to each other in their NMR characteristics. Additionally, we observe that roughly four structural clusters are subject to localized conformational changes or partial unfolding prior to global unfolding at higher temperature. Combining NMR observables with structure relaxation methods reveals that these structural clusters concentrate around loop AB (binding site III inclusive). This loop has been previously implicated in conformational changes that result in an aggregation prone state of G-CSF. Residues H43, V48, and S63 appear to be pivotal to an opening motion of loop AB, a change that is possibly also important for function. Hence, we present here an approach to profiling residues in order to highlight their potential roles in the two vital characteristics of proteins: stability and bioactivity.

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.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

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.

Towards an improved prediction of concentrated antibody solution viscosity using the Huggins coefficient

The viscosity of a monoclonal antibody solution must be monitored and controlled as it can adversely affect product processing, packaging and administration. Engineering low viscosity mAb formulations is challenging as prohibitive amounts of material are required for concentrated solution analysis, and it is difficult to predict viscosity from parameters obtained through low-volume, high-throughput measurements such as the interaction parameter, k_D, and the second osmotic virial coefficient, B₂₂. As a measure encompassing the effect of intermolecular interactions on dilute solution viscosity, the Huggins coefficient, k_h, is a promising candidate as a parameter measureable at low concentrations, but indicative of concentrated solution viscosity. In this study, a differential viscometry technique is developed to measure the intrinsic viscosity, [η], and the Huggins coefficient, k_h, of protein solutions. To understand the effect of colloidal protein-protein interactions on the viscosity of concentrated protein formulations, the viscometric parameters are compared to k_D and B₂₂ of two mAbs, tuning the contributions of repulsive and attractive forces to the net protein-protein interaction by adjusting solution pH and ionic strength. We find a strong correlation between the concentrated protein solution viscosity and the k_h but this was not observed for the k_D or the b₂₂, which have been previously used as indicators of high concentration viscosity. Trends observed in [η] and k_h values as a function of pH and ionic strength are rationalised in terms of protein-protein interactions.

Syringe Filling of High-Concentration mAb Products Using Peristaltic Pump-Based Mechanism: Challenges and Mitigation Strategies

Syringe filling of high-concentration mAb formulation during manufacturing of large-scale drug product batches may present challenges such as product deposition onto the area of the syringe barrel where the stopper is inserted, product splashing or dripping, droplets left after the fill cycle, filling needle clogging, product build-up inside the needle during line stoppages, variation in fill weight/volume, and potential impact on product quality attributes. In this article, a summary of these issues and approaches to overcome them are summarized. Potential failure modes of the syringe filling process and appropriate in-process controls are provided. In addition to developing the filling process or resolving manufacturing issues, the pharmaceutical company developing the product and associated drug product manufacturing process may want to implement long-term strategic approaches to support the portfolio progression. Potential long-term approaches such as use of a viscosity reducing formulation development approach, improving peristaltic filling technology performance, building small-scale filling capability and establishing a streamlined filling process management cycle are also summarized. The aspects summarized in this article may be used to develop a robust filling process and control strategy for high-concentration mAb products and implement long-term strategic approaches to support the portfolio progression.

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.

Influence of Protein Adsorption on Aggregation in Prefilled Syringes

Protein aggregate formation in prefilled syringes (PFSs) can be influenced by protein adsorption and desorption at the solid-liquid interface. Although inhibition of protein adsorption on the PFS surface can lead to a decrease in the amount of aggregation, the mechanism underlying protein adsorption-mediated aggregation in PFSs is unclear. This study investigated protein aggregation caused by protein adsorption on silicone oil-free PFS surfaces [borosilicate glass (GLS) and cycloolefin polymer (COP)] and the factors affecting the protein adsorption on the PFS surfaces. The adsorbed proteins formed multilayered structures that consisted of two distinct types of layers: proteins adsorbed on the surface of the material and proteins adsorbed on top of the proteins on the surface. A pH-dependent electrostatic interaction was the dominant force for protein adsorption on the GLS surface, while hydrophobic effects were dominant for protein adsorption on the COP surface. When the repulsion force between proteins was weak, protein adsorption on the adsorbed protein layer was increased for both materials and as a result, protein aggregation increased. Therefore, a formulation with high colloidal stability can minimize protein adsorption on the COP surface, leading to reduced protein aggregation.

Measuring aggregates, self-association, and weak interactions in concentrated therapeutic antibody solutions

Monoclonal antibodies are a class of biotherapeutics used for an increasing variety of disorders, including cancer, autoimmune, neurodegenerative, and viral diseases. Besides their antigen specificity, therapeutic use also mandates control of their solution interactions and colloidal properties in order to achieve a stable, efficacious, non-immunogenic, and low viscosity antibody solution at concentrations in the range of 50–150 mg/mL. This requires characterization of their reversible self-association, aggregation, and weak attractive and repulsive interactions governing macromolecular distance distributions in solution. Simultaneous measurement of these properties, however, has been hampered by solution nonideality. Based on a recently introduced sedimentation velocity method for measuring macromolecular size distributions in a mean-field approximation for hydrodynamic interactions, we demonstrate simultaneous measurement of polydispersity and weak and strong solution interactions in a panel of antibodies with concentrations up to 45 mg/mL. By allowing approximately an order of magnitude higher concentrations than previously possible in sedimentation velocity size distribution analysis, this approach can substantially improve efficiency and sensitivity for characterizing polydispersity and interactions of therapeutic antibodies at or close to formulation conditions.

Ultradilute Measurements of Self-Association for the Identification of Antibodies with Favorable High-Concentration Solution Properties

There is significant interest in formulating antibody therapeutics as concentrated liquid solutions, but early identification of developable antibodies with optimal manufacturability, stability, and delivery attributes remains challenging. Traditional methods of identifying developable mAbs with low self-association in common antibody formulations require relatively concentrated protein solutions (>1 mg/mL), and this single challenge has frustrated early-stage and large-scale identification of antibody candidates with drug-like colloidal properties. Here, we describe charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), an affinity-capture nanoparticle assay that measures colloidal self-interactions at ultradilute antibody concentrations (0.01 mg/mL), and is predictive of antibody developability issues of high viscosity and opalescence that manifest at four orders of magnitude higher concentrations (>100 mg/mL). CS-SINS enables large-scale, high-throughput selection of developable antibodies during early discovery.

Mimicking Low pH Virus Inactivation Used in Antibody Manufacturing Processes: Effect of Processing Conditions and Biophysical Properties on Antibody Aggregation and Particle Formation

Low pH virus inactivation (VI) step is routinely used in antibody production manufacturing. In this work, a mimic of the VI step was developed to focus on evaluating adverse effects on product quality. A commercially available lab-scale glass reactor system was utilized to assess impacts of process and solution conditions on process-induced monoclonal antibody particle formation. Flow imaging was found to be more sensitive than light obscuration in detecting microparticles. NaOH as a base titrant increased protein microparticles more than Tris. Both stirring and NaCl accelerated particle formation, indicating that interfacial stress and protein colloidal stability were important factors. Polysorbate 80 was effective at suppressing particle formation induced by stirring. In contrast, trehalose led to higher microparticle levels suggesting a conformational stabilizer may have other adverse effects during titration with stirring. Additionally, conformational and colloidal stability of antibodies were characterized to investigate the potential roles of antibody physicochemical properties in microparticle formation during VI. The stability data were supportive in rationalizing particle formation behaviors, but they were not predictive of particle formation during the mimicked viral inactivation steps. Overall, the results demonstrate the value of testing various solution and processing conditions in a scaled-down system prior to larger-scale VI bioprocesses.

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.

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.

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.

Adenosine Triphosphate-Induced Rapid Liquid-Liquid Phase Separation of a Model IgG1 mAb

Adenosine triphosphate (ATP) is amphiphilic in nature and has the characteristics of a hydrotrope because of the charged triphosphate moiety and the large aromatic ring located on each end of its structure. Previous studies revealed that ATP can effectively maintain the solubility and prevent liquid-liquid phase separation (LLPS) of some biological proteins. In this study, we assessed the impact of ATP on the stability of a model therapeutic IgG1 antibody (MA1) to evaluate its potential application in protein formulation design. In our system, ATP promotes rapid LLPS of MA1 and we demonstrate that the ATP-MA1 static interaction drives phase separation of MA1. The attractive protein-protein interaction increased exclusively in the presence of ATP but not in the presence of other ATP analogues, such as adenosine diphosphate, adenosine monophosphate, and adenine. Through an intrinsic fluorescence quenching study, we revealed that ATP bound to MA1 electrostatically and formed static interactions; furthermore, such static ATP-MA1 interactions significantly altered the surface property of the protein and the protein-protein interactions and subsequently induced LLPS of MA1. This ATP-induced LLPS could be effectively eliminated by Mg²⁺, which chelated with ATP and thus negated ATP-MA1 static interaction. Our results revealed the unique molecular mechanism of ATP-induced rapid LLPS of MA1.

N-Acetylated-L-arginine (NALA) is an enhanced protein aggregation suppressor under interfacial stresses and elevated temperature for protein liquid formulations

Even though arginine hydrochloride has been recognized as a protein aggregation suppressor in the biopharmaceutical industry, its use has been questioned due to decreasing transition unfolding temperatures (T_m). Four compounds were designed to enhance the role of arginine by changing the length of the carbon chain with removal or N-acetylation of α-amino group. Biophysical properties were observed by differential scanning calorimetry (DSC), dynamic light scattering (DLS), size-exclusion chromatography (SEC), and flow imaging (FI). N-Acetyl-L-arginine (NALA) performed the best at minimizing decrease in T_m with arginine at different pH. NALA also demonstrated relatively higher colloidal stability than arginine hydrochloride, especially in the acidic pH, thereby reducing agitation stress of IgG. Moreover, NALA exhibited a cooperative effect with commercially used glycine buffer for IVIG to maintain the monomer contents with almost no change and suppressed larger particle formation after agitation with heat. The study concludes that the decreasing T_m of proteins by arginine hydrochloride is due to amide group in the α-carbon chain. Moreover, chemical modification on the group compared to removing it will be a breakthrough of arginine's limitations and optimize storage stability of protein therapeutics.

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.

Aggregation, liquid-liquid phase separation, and percolation behaviour of a model antibody fluid constrained by hard-sphere obstacles

This study is concerned with the behaviour of proteins within confinement created by hard-sphere obstacles. An individual antibody molecule is depicted as an assembly of seven hard spheres, organized to resemble a Y-shaped (on average) antibody (7-bead model) protein. For comparison with other studies we, in one case, model the protein as a hard sphere decorated by three short-range attractive sites. The antibody has two Fab and one Fc domains located in the corners of the letter Y. In this calculation, only the Fab-Fab and Fab-Fc attractive pair interactions are possible. The confinement is formed by the randomly distributed hard-sphere obstacles fixed in space. Aside from size exclusion, the obstacles do not interact with antibodies, but they affect the protein-protein correlation. We used a combination of the scaled-particle theory, Wertheim's thermodynamic perturbation theory and the Flory-Stockmayer theory to calculate: (i) the second virial coefficient of the protein fluid, (ii) the percolation threshold, (iii) cluster size distributions, and (iv) the liquid-liquid phase separation as a function of the strength of the various pair interactions of the protein and the model parameters, such as protein concentration and the packing fraction of obstacles. The conclusion is that hard-sphere obstacles strongly decrease the critical density and also, but to a much lesser extent, the critical temperature. Also, the confinement enhances clustering, making the percolating region broader. The effect depends on the model parameters, such as the packing fraction of obstacles η0, the inter-site interaction strength εIJ, and the ratio between the size of the obstacle σ0 and the size of one bead of the model antibody σhs; the value of this ratio is varied here from 2 to 5. Interestingly, at low to moderate packing fractions of obstacles, the second virial coefficient first slightly decreases (destabilization), and the slope depends on the observation temperature, but then at higher values of η0 it increases. The calculated values of the second virial coefficient also depend on the size of the obstacles.

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.

First-order nucleation and subsequent growth promote liquid-liquid phase separation of a model IgG1 mAb

Although protein aggregation is commonly encountered during the manufacturing and storage of bio-therapeutics, the actual aggregation mechanism remains unclear, and little has been reported about the protein aggregation kinetics from time zero under particular solution conditions. In this study, we used real-time dynamic light scattering (DLS) to continuously monitor the time-dependent evolution of the Z-average hydrodynamic radius of a model IgG1 (JM2) immediately after the JM2 solution was subjected to various low temperatures (0-4 °C). We observed that JM2 aggregated to form nuclei first, and then it subsequently grew to small liquid droplets via a two-step, first-order, reversible process without causing irreversible structural changes: a slow first step defined as the "nucleation" step, wherein nuclei formed slowly until reaching a transitional time point (t_onset), and a much faster second step initiated after t_onset and the nucleus size of the protein increased rapidly, which eventually caused liquid droplet formation and liquid-liquid phase separation (LLPS). The "nucleation" rate constant (K_nucleation) and particle growth rate constant (K_growth), as well as t_onset, were found to be temperature, pH and concentration dependent. The aggregation of JM2 could be universally described by these two-step first-order kinetics: under conditions where JM2 aggregated very slowly, the second step was not observed within the experimental time scale, while under conditions where JM2 aggregated very rapidly, the first step could not be recorded. We believe that these three parameters, K_nucleation, K_growth, and t_onset, can be used to quantify and compare the aggregation kinetics of JM2 under different solution and temperature conditions and, furthermore, serve as a theoretical base to account for the key characteristics of the aggregation kinetics of JM2 and other protein therapeutics under conditions of interest.

Protein aggregation and immunogenicity of biotherapeutics

Recombinant proteins are the mainstay of biopharmaceuticals. A key challenge in the manufacturing and formulation of protein biologic products is the tendency for the active pharmaceutical ingredients to aggregate, resulting in irreversible drug loss, and an increase in immunogenicity risk. While the molecular mechanisms of protein aggregation have been discussed extensively in the literature, knowledge gaps remain in connecting the phenomenon in the context of immunogenicity of biotherapeutics. In this review, we discussed factors that drive aggregation of pharmaceutical recombinant proteins, and highlighted methods of prediction and mitigation that can be deployed through the development stages, from formulation to bioproduction. The purpose is to stimulate new dialogs that would bridge the interface between physical characterizations of protein aggregates in biotherapeutics and the functional attributes of the immune system.

On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS)

The crystallization of Anti-CD20, a full-length monoclonal antibody, has been studied in the PEG400/Na2SO4/Water system near Liquid-Liquid Phase Separation (LLPS) conditions by both sitting-drop vapour diffusion and batch methods. In order to understand the Anti-CD20 crystallization propensity in the solvent system of different compositions, we investigated some measurable parameters, normally used to assess protein conformational and colloidal stability in solution, with the aim to understand the aggregation mechanism of this complex biomacromolecule. We propose that under crystallization conditions a minor population of specifically aggregated protein molecules are present. While this minor species hardly contributes to the measured average solution behaviour, it induces and promotes crystal formation. The existence of this minor species is the result of the LLPS occurring concomitantly under crystallization conditions.

The Role of Surface Properties on Protein Aggregation Behavior in Aqueous Solution of Different pH Values

This study aimed to investigate the effect of pH-mediated surface properties of bovine serum albumin (BSA) on protein aggregation and the changes of protein structure and colloidal stability at different solution pH levels. The hydrophobicity of BSA surface was characterized by endogenous fluorescence spectroscopy, fluorescence quenching of acrylamide, and fluorescence probe. The results showed that the hydrophobicity of BSA surface was similar at pH 5, 6, 7.4, followed by pH 4, 8, 9, 10, and finally by pH 3 and 11 with strong acidity and alkalinity. The positive charge on the BSA surface was increased gradually with the decrease of solution pH, while the negative charge on protein surface was increased gradually with the increase of solution pH. The degree of protein aggregation was examined by turbidimetry, flow cytometry, and SDS-PAGE. The results showed that the oscillating aggregation of BSA did not change with the solution pH, but was partially dependent on the relative contribution of electrostatic and hydrophobic interactions between the protein molecules. In addition, the secondary structure, conformational stability, unfolding degree, and colloidal stability of proteins were investigated by circular dichroism, fluorescence spectroscopy, protein pulse hydrolysis, and dynamic light scattering, respectively. The results suggested that the solution pH could change the structure and stability of the protein at different levels. Solution pH has distinct effects on the structural stability of protein at different levels. The change of protein surface properties mediated by solution pH is related to protein aggregation.

Coarse-Grained Molecular Dynamics Simulations for Understanding the Impact of Short-Range Anisotropic Attractions on Structure and Viscosity of Concentrated Monoclonal Antibody Solutions

Understanding protein-protein interactions in concentrated therapeutic monoclonal antibody (mAb) solutions is desirable for improved drug discovery, processing, and administration. Here, we deduce both the net protein charge and the magnitude and geometry of short-ranged, anisotropic attractions of a mAb across multiple concentrations and cosolute conditions by comparing structure factors S(q) obtained from small-angle X-ray scattering experiments with those from molecular dynamics (MD) simulations. The simulations, which utilize coarse-grained 12-bead models exhibiting a uniform van der Waals attraction, uniform electrostatic repulsion, and short-range attractions between specific beads, are versatile enough to fit S(q) of a wide range of protein concentrations and ionic strength with the same charge on each bead and a single anisotropic short-range attraction strength. Cluster size distributions (CSDs) obtained from best fit simulations reveal that the experimental structure is consistent with small reversible oligomers in even low viscosity systems and help quantify the impact of these clusters on viscosity. The ability to systematically use experimental S(q) data together with MD simulations to discriminate between different possible protein-protein interactions, as well as to predict viscosities from protein CSDs, is beneficial for designing mAbs and developing formulation strategies that avoid high viscosities and aggregation at high concentration.

Relationship of PEG-induced precipitation with protein-protein interactions and aggregation rates of high concentration mAb formulations at 5 °C

Native protein-protein interactions can play an important role in determining the tendency of monoclonal antibodies (mAbs) to aggregate under storage conditions. In this context, phase separation of mAb solutions induced by the addition of neutral polymers such as poly(ethylene glycol) (PEG) represents a simple method to assess the tendency of proteins to self-associate in the native state. Here, we investigated their relationships between PEG-induced phase separation, protein-protein interactions and long-term aggregation rate of several formulations of four mAbs at 100 mg/mL and 5 °C over 12 weeks of storage. We observed that the location of the phase boundary correlated well with the osmotic second virial coefficient B₂₂ determined in absence of the polymer, indicating that for our solutions PEG primarily leads to depletion forces between protein molecules, which are additive to protein-protein interactions. However, limited correlation between aggregation rate at 5 °C and phase behavior was observed across different mAbs, pH values and ionic strengths, indicating that colloidal stability is not the only determinant of aggregation even at such low temperature and high protein concentration. Our results contribute to the growing realization that aggregation propensity in the context of antibody developability is a complex feature, which depends on a variety of biophysical properties rather than one single parameter.

Potential and limits of a colloid approach to protein solutions

Looking at globular proteins with the eyes of a colloid scientist has a long tradition, in fact a significant part of the early colloid literature was focused on protein solutions. However, it has also been recognized that proteins are much more complex than the typical hard sphere-like synthetic model colloids. Proteins are not perfect spheres, their interaction potentials are in general not isotropic, and using theories developed for such particles are thus clearly inadequate in many cases. In this perspective article, we now take a closer look at the field. In particular, we reflect on the fact that modern colloid science has been undergoing a tremendous development, where a multitude of novel systems have been developed in the lab and in silico. During the last decade we have seen a rapidly increasing number of reports on the synthesis of anisotropic, patchy and/or responsive synthetic colloids, that start to resemble their complex biological counterparts. This experimental development is also reflected in a corresponding theoretical and simulation effort. The experimental and theoretical toolbox of colloid science has thus rapidly expanded, and there is obviously an enormous potential for an application of these new concepts to protein solutions, which has already been realized and harvested in recent years. In this perspective article we make an attempt to critically discuss the exploitation of colloid science concepts to better understand protein solutions. We not only consider classical applications such as the attempt to understand and predict solution stability and phase behaviour, but also discuss new challenges related to the dynamics, flow behaviour and liquid-solid transitions found in concentrated or crowded protein solutions. It not only aims to provide an overview on the progress in experimental and theoretical (bio)colloid science, but also discusses current shortcomings in our ability to correctly reproduce and predict the structural and dynamic properties of protein solutions based on such a colloid approach.