Specific interactions in high concentration antibody solutions resulting in high viscosity

Portable Microfluidic Viscometer for Formulation Development and in Situ Quality Control of Protein and Antibody Solutions

Viscosity of protein solutions is a critical product quality attribute for protein therapeutics such as monoclonal antibodies. Here we introduce a portable single-use analytical chip-based viscometer for determining the viscosity of protein solutions using low sample volumes of 10 μL. Through the combined use of a microfluidic viscometer, a smartphone camera for image capture, and an automated data processing algorithm for the calculation of the viscosity of fluids, we enable measurement of viscosity of multiple samples in parallel. We first validate the viscometer using glycerol-water mixtures and subsequently demonstrate the ability to perform rapid characterization of viscosity in four different monoclonal antibody formulations in a broad concentration (1 to 320 mg/mL) and viscosity (1 to 600 cP) range, showing excellent agreement with values obtained by a conventional cone-plate rheometer. Not only does the platform offer benefits of viscosity measurements using minimal sample volumes, but enables higher throughput compared to gold-standard methodologies owing to multiplexing of the measurement and single-use characteristics of the viscometer, thus showing great promise in developability studies. Additionally, as our platform has the capability of performing viscosity measurements at the point of sample collection, it offers the opportunity to employ viscosity measurement as an in situ quality control of therapeutic proteins and antibodies.

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.

Poly(glutamic acid)-Based Viscosity Reducers for Concentrated Formulations of a Monoclonal IgG Antibody

Above a concentration threshold, the viscosity of solutions of proteins increases abruptly, which hampers the injectability of therapeutic formulations. Concentrations above 200 g/L are an ideal goal for subcutaneous application of antibodies. Molecular additives, such as amino acids (e.g., arginine) help decrease the viscosity, but they are used at concentrations as high as about 200 mmol/L. We addressed the question of whether poly(amino acids) could be more efficient than small molecular additives. We observed marked fluidification of a model therapeutic monoclonal antibody (mAb) solution by poly(d,l-glutamic acid) and poly(l-glutamic acid) derivatives added at concentrations of <6.5 g/L (i.e., a mAb/polymer chain molar ratio between 4:1 and 1:1 mol/mol). The bare poly(glutamate) parent chains were compared with polyethylene glycol-grafted chains as PEGylation is a common way to enhance stability. Viscosity could be decreased to ∼20 mPa s as compared to values of ∼100 mPa s in the absence of polymers at 200 g/L mAb. Formation of complexes between the mAb and the polyglutamates was characterized by capillary electrophoresis analysis in dilute solutions (1 g/L mAb) and by observation of phase separation at higher concentrations, suggesting tight association at about 2:1 mol/mol mAb/polymer. Altogether, these results show that polyglutamate derivatives hold an untapped potential as an excipient for fluidification of concentrated protein solutions.

The Osmolality and Hemolysis of High-Concentration Monoclonal Antibody Formulations

PURPOSES

Highly concentrated monoclonal antibody (mAb) formulations for subcutaneous administration are becoming increasingly preferred within the biopharmaceutical industry for ease of use and improved patient compliance. A common phenomenon observed in the industry is that osmolality detected via freezing-point depression (FPD) in high-concentration mAb formulations is much higher than the theoretical concentrations, yet the occurrence of this phenomenon and its possible safety issues have been rarely reported.

METHODS

The current study summarized theoretical osmolality of U.S. Food and Drug Administration approved high-concentration mAb formulations and evaluated effects of high osmolality on safety using hemolysis experiments for the first time. Two mAbs formulated at 150 mg/mL were used as models and configured into two isotonic solutions: a, a theoretically calculated molarity in the isotonic range (H) and b, an osmolality value measured via the FPD in the isotonic range (I). The H and I formulations of each mAb were individually subjected to hemolysis experiments, and the hemolysis rates of the two formulations of the same mAb were compared. Besides, the effect of mAb concentration on osmolality detected by FPD was explored as well.

RESULTS

The results indicated that the hemolysis rates were similar between the H and I formulations of mAbs at the same sample addition volume, and the osmolality values increased approximately linearly with the increase in mAb concentration.

CONCLUSIONS

High osmolality for high-concentration mAb formulations would not affect product safety and the excipients could be added at relatively high levels to maintain product stability, especially for labile products.

Modulation of the high concentration viscosity of IgG1 antibodies using clinically validated Fc mutations

The self-association of therapeutic antibodies can result in elevated viscosity and create problems in manufacturing and formulation, as well as limit delivery by subcutaneous injection. The high concentration viscosity of some antibodies has been reduced by variable domain mutations or by the addition of formulation excipients. In contrast, the impact of Fc mutations on antibody viscosity has been minimally explored. Here, we studied the effect of a panel of common and clinically validated Fc mutations on the viscosity of two closely related humanized IgG1, κ antibodies, omalizumab (anti-IgE) and trastuzumab (anti-HER2). Data presented here suggest that both Fab-Fab and Fab-Fc interactions contribute to the high viscosity of omalizumab, in a four-contact model of self-association. Most strikingly, the high viscosity of omalizumab (176 cP) was reduced 10.7- and 2.2-fold by Fc modifications for half-life extension (M252Y:S254T:T256E) and aglycosylation (N297G), respectively. Related single mutations (S254T and T256E) each reduced the viscosity of omalizumab by ~6-fold. An alternative half-life extension Fc mutant (M428L:N434S) had the opposite effect in increasing the viscosity of omalizumab by 1.5-fold. The low viscosity of trastuzumab (8.6 cP) was unchanged or increased by ≤ 2-fold by the different Fc variants. Molecular dynamics simulations provided mechanistic insight into the impact of Fc mutations in modulating electrostatic and hydrophobic surface properties as well as conformational stability of the Fc. This study demonstrates that high viscosity of some IgG1 antibodies can be mitigated by Fc mutations, and thereby offers an additional tool to help design future antibody therapeutics potentially suitable for subcutaneous delivery.

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.

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.

Protein Association in Solution: Statistical Mechanical Modeling

Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure-property relations. Recently, this limitation has been partly overcome by bringing the powerful Wertheim theory of associating molecules to bear on protein association equilibria. Here, we review these developments.

Biophysical Determinants for the Viscosity of Concentrated Monoclonal Antibody Solutions

Monoclonal antibodies (mAbs) are particularly relevant for therapeutics due to their high specificity and versatility, and mAb-based drugs are hence used to treat numerous diseases. The increased patient compliance of self-administration motivates the formulation of products for subcutaneous (SC) administration. The associated challenge is to formulate highly concentrated antibody solutions to achieve a significant therapeutic effect, while limiting their viscosity and preserving their physicochemical stability. Protein-protein interactions (PPIs) are in fact the root cause of several potential problems concerning the stability, manufacturability, and delivery of a drug product. The understanding of macroscopic viscosity requires an in-depth knowledge on protein diffusion, PPIs, and self-association/aggregation. Here, we study the self-diffusion of different mAbs of the IgG1 subtype in aqueous solution as a function of the concentration and temperature by quasi-elastic neutron scattering (QENS). QENS allows us to probe the short-time self-diffusion of the molecules and therefore to determine the hydrodynamic mAb cluster size and to gain information on the internal mAb dynamics. Small-angle neutron scattering (SANS) is jointly employed to probe structural details and to understand the nature and intensity of PPIs. Complementary information is provided by molecular dynamics (MD) simulations and viscometry, thus obtaining a comprehensive picture of mAb diffusion.

Raman Spectroscopic Analysis of Highly-Concentrated Antibodies under the Acid-Treated Conditions

PURPOSE

Antibody drugs are usually formulated as highly-concentrated solutions, which would easily generate aggregates, resulting in loss of efficacy. Although low pH increases the colloidal dispersion of antibodies, acid denaturation can be an issue. Therefore, knowing the physical properties at low pH under high concentration conditions is important.

METHODS

Raman spectroscopy was used to investigate pH-induced conformational changes of antibodies at 50 mg/ml. Experiments in pH 3 to 7 were performed for human serum IgG and recombinant rituximab.

RESULTS

We detected the evident changes at pH 3 in Tyr and Trp bands, which are the sensitive markers of intermolecular interactions. Thermal transition analysis over the pH range demonstrated that the thermal transition temperature (Tm) was highest at pH 3. Acid-treated and neutralized one showed higher Tm than that of pH 7, indicating that their extent of intermolecular interactions correlated with the Tm values. Onset temperature was clearly different between concentrated and diluted samples. Colloidal analyses confirmed the findings of the Raman analysis.

CONCLUSION

Our studies demonstrated the positive correlation between Raman analysis and colloidal information, validating as a method for evaluating antibody conformation associated with aggregation propensities.

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.

Hollow silicon microneedles, fabricated using combined wet and dry etching techniques, for transdermal delivery and diagnostics

Microneedle-based technologies are the subject of intense research and commercial interest for applications in transdermal delivery and diagnostics, primarily because of their minimally invasive and painless nature, which in turn could lead to increased patient compliance and self-administration. In this paper, a process for the fabrication of arrays of hollow silicon microneedles is described. This method uses just two bulk silicon etches - a front-side wet etch to define the 500 μm tall octagonal needle structure itself, and a rear-side dry etch to create a 50 μm diameter bore through the needle. This reduces the number of etches and process complexity over the approaches described elsewhere. Ex-vivo human skin and a customised applicator were used to demonstrate biomechanical reliability and the feasibility of using these microneedles for both transdermal delivery and diagnostics. Microneedle arrays show no damage even when applied to skin up to 40 times, are capable of delivering several mL of fluid at flowrates of 30 μL/min, and of withdrawing 1 μL of interstitial fluid using capillary action.

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.

A systematic review of commercial high concentration antibody drug products approved in the US: formulation composition, dosage form design and primary packaging considerations

Three critical aspects that define high concentration antibody products (HCAPs) are as follows: 1) formulation composition, 2) dosage form, and 3) primary packaging configuration. HCAPs have become successful in the therapeutic sector due to their unique advantage of allowing subcutaneous self-administration. Technical challenges, such as physical and chemical instability, viscosity, delivery volume limitations, and product immunogenicity, can hinder successful development and commercialization of HCAPs. Such challenges can be overcome by robust formulation and process development strategies, as well as rational selection of excipients and packaging components. We compiled and analyzed data from US Food and Drug Administration-approved and marketed HCAPs that are ≥100 mg/mL to identify trends in formulation composition and quality target product profile. This review presents our findings and discusses novel formulation and processing technologies that enable the development of improved HCAPs at ≥200 mg/mL. The observed trends can be used as a guide for further advancements in the development of HCAPs as more complex antibody-based modalities enter biologics product development.

Structure-Based Optimization of Antibody-Based Biotherapeutics for Improved Developability: A Practical Guide for Molecular Modelers

A great effort to avoid known developability risks is now more often being made earlier during the lead candidate discovery and optimization phase of biotherapeutic drug development. Predictive computational strategies, used in the early stages of antibody discovery and development, to mitigate the risk of late-stage failure of antibody candidates, are highly valuable. Various structure-based methods exist for accurately predicting properties critical to developability, and, in this chapter, we discuss the history of their development and demonstrate how they can be used to filter large sets of candidates arising from target affinity screening and to optimize lead candidates for developability. Methods for modeling antibody structures from sequence and detecting post-translational modifications and chemical degradation liabilities are also discussed.

Developability profiling of a panel of Fc engineered SARS-CoV-2 neutralizing antibodies

To combat the COVID-19 pandemic, potential therapies have been developed and moved into clinical trials at an unprecedented pace. Some of the most promising therapies are neutralizing antibodies against SARS-CoV-2. In order to maximize the therapeutic effectiveness of such neutralizing antibodies, Fc engineering to modulate effector functions and to extend half-life is desirable. However, it is critical that Fc engineering does not negatively impact the developability properties of the antibodies, as these properties play a key role in ensuring rapid development, successful manufacturing, and improved overall chances of clinical success. In this study, we describe the biophysical characterization of a panel of Fc engineered ("TM-YTE") SARS-CoV-2 neutralizing antibodies, the same Fc modifications as those found in AstraZeneca's Evusheld (AZD7442; tixagevimab and cilgavimab), in which the TM modification (L234F/L235E/P331S) reduce binding to FcγR and C1q and the YTE modification (M252Y/S254T/T256E) extends serum half-life. We have previously shown that combining both the TM and YTE Fc modifications can reduce the thermal stability of the CH2 domain and possibly lead to developability challenges. Here we show, using a diverse panel of TM-YTE SARS-CoV-2 neutralizing antibodies, that despite lowering the thermal stability of the Fc CH2 domain, the TM-YTE platform does not have any inherent developability liabilities and shows an in vivo pharmacokinetic profile in human FcRn transgenic mice similar to the well-characterized YTE platform. The TM-YTE is therefore a developable, effector function reduced, half-life extended antibody platform.

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.

Synergistic Effects of Multiple Excipients on Controlling Viscosity of Concentrated Protein Dispersions

Viscosity control is essential for the manufacturing and delivery of concentrated therapeutic proteins. Limited availability of the precious protein-based drugs hinders the characterization and screening of the formulation conditions with new types or different combinations of excipients. In this work, a droplet-based microfluidic device with incorporated multiple particle tracking microrheology (MPT) is developed to quantify the effects of two excipients, arginine hydrochloride (ArgHCl) and caffeine, on the viscosity of concentrated bovine gamma globulin (BGG) dispersions at two different values of pH. The effectiveness of both ArgHCl and caffeine show dependence on the BGG concentration and solution pH. The data set with high compositional resolution provides useful information to guide formulation with multiple viscosity-reducing excipients and quantification appropriate to start elucidating the connection to protein-protein interaction mechanisms. Overall, this work has demonstrated that the developed microfluidic approach has the potential to effectively assess the impact of multiple excipients on the viscosity and provide data for computational methods to predict viscosity for high concentration protein formulations.

Alternative Excipients for Protein Stabilization in Protein Therapeutics: Overcoming the Limitations of Polysorbates

Given their safety and efficiency in protecting protein integrity, polysorbates (PSs) have been the most widely used excipients for the stabilization of protein therapeutics for years. In recent decades, however, there have been numerous reports about visible or sub-visible particles in PS-containing biotherapeutic products, which is a major quality concern for parenteral drugs. Alternative excipients that are safe for parenteral administration, efficient in protecting different protein drugs against various stress conditions, effective in protein stabilization in high-concentrated liquid formulations, stable under the storage conditions for the duration of the product's shelf-life, and compatible with other formulation components and the primary packaging are highly sought after. The aim of this paper is to review potential alternative excipients from different families, including surfactants, carbohydrate- and amino acid-based excipients, synthetic amphiphilic polymers, and ionic liquids that enable protein stabilization. For each category, important characteristics such as the ability to stabilize proteins against thermal and mechanical stresses, current knowledge related to the safety profile for parenteral administration, potential interactions with other formulation components, and primary packaging are debated. Based on the provided information and the detailed discussion thereof, this paper may pave the way for the identification or development of efficient excipients for biotherapeutic protein stabilization.

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.

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

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

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.

Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using Coarse-Grained Molecular Simulations

Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B₂₂) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B₂₂ values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B₂₂ calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B₂₂ values at pH conditions near the pK_a of titratable residues.

Ionic Liquid-Based Strategy for Predicting Protein Aggregation Propensity and Thermodynamic Stability

Novel drug candidates are continuously being developed to combat the most life-threatening diseases; however, many promising protein therapeutics are dropped from the pipeline. During biological and industrial processes, protein therapeutics are exposed to various stresses such as fluctuations in temperature, solvent pH, and ionic strength. These can lead to enhanced protein aggregation propensity, one of the greatest challenges in drug development. Recently, ionic liquids (ILs), in particular, biocompatible choline chloride ([Cho]Cl)-based ILs, have been used to hinder stress-induced protein conformational changes. Herein, we develop an IL-based strategy to predict protein aggregation propensity and thermodynamic stability. We examine three key variables influencing protein misfolding: pH, ionic strength, and temperature. Using dynamic light scattering, zeta potential, and variable temperature circular dichroism measurements, we systematically evaluate the structural, thermal, and thermodynamic stability of fresh immunoglobin G4 (IgG4) antibody in water and 10, 30, and 50 wt % [Cho]Cl. Additionally, we conduct molecular dynamics simulations to examine IgG4 aggregation propensity in each system and the relative favorability of different [Cho]Cl-IgG4 packing interactions. We re-evaluate each system following 365 days of storage at 4 °C and demonstrate how to predict the thermodynamic properties and protein aggregation propensity over extended storage, even under stress conditions. We find that increasing [Cho]Cl concentration reduced IgG4 aggregation propensity both fresh and following 365 days of storage and demonstrate the potential of using our predictive IL-based strategy and formulations to radically increase protein stability and storage.

Viscosity increase/gelation of therapeutic IgG monoclonal antibodies induced by Zn2+: one possible root cause of clogging of staked-in-needle prefilled syringes

We investigated the elution of zinc ions (Zn²⁺) from the elastomer of rigid needle shields (RNS) attached to staked-in-needle prefilled syringes (SIN-PFS) and the physicochemical impacts of Zn²⁺ on therapeutic IgG monoclonal antibody (mAb) solutions. The elution of metal ions from typical RNS elastomer under realistic buffer and storage conditions was investigated by inductively coupled plasma-mass spectrometry. Among the metal ions examined, only Zn²⁺ was detected. The elution of Zn²⁺ from RNS elastomer was found to be buffer-dependent. We investigated the influence of Zn²⁺ on the viscosity of seven mAb solutions at 180 mg/mL. The effect of Zn²⁺ clearly depended on antibody type. Drastic increases in viscosity or gelation were observed in four out of the seven mAbs. Dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS) showed the effect of Zn²⁺ on mAb viscosity was explained by the colloidal destabilization of mAb solutions. Thus, Zn²⁺ leaching from RNS elastomer may possibly increase viscosity or cause gelation, and consequently cause possible needle clogging during long-term storage. DLS and SAXS can predict reactivity of mAbs to Zn²⁺, and require only small amounts of samples. This makes it possible to predict compatibility with RNS elastomer and evaluate needle clogging risk in SIN-PFSs in the early stages of mAb development.

How neutron scattering techniques benefit investigating structures and dynamics of monoclonal antibody

Over the past several decades, great progresses have been made for the pharmaceutical industry of monoclonal antibody (mAb). More and more mAb products were approved for human therapeutics. This review describes the state of art of utilizing neutron scattering to investigate mAbs, in the aspects of structures, dynamics, physicochemical stability, functionality, etc. Firstly, brief histories of mAbs and neutron scattering, as well as some basic knowledges and principles of neutron scattering were introduced. Then specific examples were demonstrated. For the structure and structural evolution investigation of in dilute and concentrated mAbs solution, in situ small angle neutron scattering (SANS) was frequently utilized. Neutron reflectometry (NR) is powerful to probe the absorption behaviors of mAbs on various surfaces and interfaces. While for dynamic investigation, quasi-elastic scattering techniques such as neutron spin echo (NSE) demonstrate the capabilities. With this review, how to utilize and take advantages of neutron scattering on investigating structures and dynamics of mAbs were demonstrated and discussed.

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.

A Microfluidic Prototype for High-Frequency, Large Strain Oscillatory Flow Rheometry

We introduce a “Rheo-chip” prototypical rheometer which is able to characterise model fluids under oscillatory flow at frequencies f up to 80 Hz and nominal strain up to 350, with sample consumption of less than 1 mL, and with minimum inertial effects. Experiments carried out with deionized (DI) water demonstrate that the amplitude of the measured pressure drop ΔPM falls below the Newtonian prediction at f≥ 3 Hz. By introducing a simple model which assumes a linear dependence between the back force and the dead volume within the fluid chambers, the frequency response of both ΔPM and of the phase delay could be modeled more efficiently. Such effects need to be taken into account when using this type of technology for characterising the frequency response of non-Newtonian fluids.

Deciphering the high viscosity of a therapeutic monoclonal antibody in high concentration formulations by microdialysis-hydrogen/deuterium exchange mass spectrometry

High concentration formulations of therapeutic monoclonal antibodies (mAbs) are highly desired for subcutaneous injection. However, high concentration formulations can exhibit unusual molecular behaviors, such as high viscosity or aggregation, that present challenges for manufacturing and administration. To understand the molecular mechanism of the high viscosity exhibited by high concentration protein formulations, we analyzed a human IgG4 (mAb1) at high protein concentrations using sedimentation velocity analytical ultracentrifugation (SV-AUC), X-ray crystallography, hydrogen/deuterium exchange mass spectrometry (HDX-MS), and protein surface patches analysis. Particularly, we developed a microdialysis HDX-MS method to determine intermolecular interactions at different protein concentrations. SV-AUC revealed that mAb1 displayed a propensity for self-association of Fab-Fab, Fab-Fc, and Fc-Fc. mAb1 crystal structure and HDX-MS results demonstrated self-association between complementarity-determining regions (CDRs) and Fc through electrostatic interactions. HDX-MS also indicated Fab-Fab interactions through hydrophobic surface patches constructed by mAb1 CDRs. Our multi-method approach, including fast screening of SV-AUC as well as interface analysis by X-ray crystallography and HDX-MS, helped to elucidate the high viscosity of mAb1 at high concentrations as induced by self-associations of Fab-Fc and Fab-Fab.

Development of QSAR models for in silico screening of antibody solubility

Although monoclonal antibodies (mAbs) have been shown to be extremely effective in treating a number of diseases, they often suffer from poor developability attributes, such as high viscosity and low solubility at elevated concentrations. Since experimental candidate screening is often materials and labor intensive, there is substantial interest in developing in silico tools for expediting mAb design. Here, we present a strategy using machine learning-based QSAR models for the a priori estimation of mAb solubility. The extrapolated protein solubilities of a set of 111 antibodies in a histidine buffer were determined using a high throughput PEG precipitation assay. 3D homology models of the antibodies were determined, and a large set of in house and commercially available molecular descriptors were then calculated. The resulting experimental and descriptor data were then used for the development of QSAR models of mAb solubilities. After feature selection and training with different machine learning algorithms, the models were evaluated with external test sets. The resulting regression models were able to estimate the solubility values of external test set data with R² of 0.81 and 0.85 for the two regression models developed. In addition, three class and binary classification models were developed and shown to be good estimators of mAb solubility behavior, with overall test set accuracies of 0.70 and 0.95, respectively. The analysis of the selected molecular descriptors in these models was also found to be informative and suggested that several charge-based descriptors and isotype may play important roles in mAb solubility. The combination of high throughput relative solubility experimental techniques in concert with efficient machine learning QSAR models offers an opportunity to rapidly screen potential mAb candidates and to design therapeutics with improved solubility characteristics.

Simulate SubQ: The Methods and the Media

For decades, there has been a growing interest in injectable subcutaneous formulations to improve the absorption of drugs into the systemic circulation and to prolong their release over a longer period. However, fluctuations in the blood plasma levels together with bioavailability issues often limit their clinical success. This warrants a closer look at the performance of long-acting depots, for example, and their dependence on the complex interplay between the dosage form and the physiological microenvironment. For this, biopredictive performance testing is used for a thorough understanding of the biophysical processes affecting the absorption of compounds from the injection site in vivo and their simulation in vitro. In the present work, we discuss in vitro methodologies including methods and media developed for the subcutaneous route of administration on the background of the most relevant absorption mechanisms. Also, we highlight some important knowledge gaps and shortcomings of the existing methodologies to provide the reader with a better understanding of the scientific evidence underlying these models.

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.

Insights into the Conformation and Self-Association of a Concentrated Monoclonal Antibody using Isothermal Chemical Denaturation and Nuclear Magnetic Resonance

The purpose of this investigation was to highlight the utility of nuclear magnetic resonance (NMR) as a multi-attribute method for the characterization of therapeutic antibodies. In this case study, we compared results from isothermal chemical denaturation (ICD) and NMR with standard methods to relate conformational states of a model monoclonal antibody (mAb1) with protein-protein interactions (PPI) that lead to self - association in concentrated solutions. The increase in aggregation rate and relative viscosity for mAb1 was found to be both concentration and pH dependent. The free energy of unfolding (∆G⁰) from ICD and thermal analysis in dilute solutions indicated that although the native state predominated between pH 4 - pH 7, it was disrupted at the CH₂ and unfolded noncooperatively under acidic conditions. One-dimensional (1D) ¹H NMR and two-dimensional (2D) ¹³C-¹H NMR performed, in concentrated solutions, confirmed that PPI between pH 4-7 occurred while mAb1 was in the native state. NMR corroborated that mAb1 maintained a dominant native state at formulation-relevant conditions at the tested pH range, had increased global molecular tumbling dynamics at lower pH and confirmed increased PPI at higher pH conditions. This report aligns and compares typical characterization of an IgG1 with assessment of structure by NMR and provided a more precise assessment and deeper insight into the conformation of an IgG1 in concentrated solutions.

Caffeine as a Viscosity Reducer for Highly Concentrated Monoclonal Antibody Solutions

Many monoclonal antibody (mAb) solutions exhibit high viscosity at elevated concentrations, which prevents manufacturing and injecting of concentrated mAb drug products at the small volumes needed for subcutaneous (SC) administration. Addition of excipients that interrupt intermolecular interactions is a common approach to reduce viscosity of high concentration mAb formulations. However, in some cases widely used excipients can fail to lower viscosity. Here, using infliximab and ipilimumab as model proteins, we show that caffeine effectively lowers the viscosity of both mAb formulations, whereas other common viscosity-reducing excipients, sodium chloride and arginine, do not. Furthermore, stability studies under accelerated conditions show that caffeine has no impact on stability of lyophilized infliximab or liquid ipilimumab formulations. In addition, presence of caffeine in the formulations does not affect in vitro bioactivities of infliximab or ipilimumab. Results from this study suggest that caffeine could be a useful viscosity reducing agent that complements other traditional excipients and provides viscosity reduction to a wider range of mAb drug products.

Cluster Percolation Causes Shear Thinning Behavior in Concentrated Solutions of Monoclonal Antibodies

High-concentration (>100 g/L) solutions of monoclonal antibodies (mAbs) are typically characterized by anomalously large solution viscosity and shear thinning behavior for strain rates ≥10³ s^-1. Here, the link between protein-protein interactions (PPIs) and the rheology of concentrated solutions of COE-03 and COE-19 mAbs is studied by means of static and dynamic light scattering and microfluidic rheometry. By comparing the experimental data with predictions based on the Baxter sticky hard-sphere model, we surprisingly find a connection between the observed shear thinning and the predicted percolation threshold. The longest shear relaxation time of mAbs was much larger than that of model sticky hard spheres within the same region of the phase diagram, which is attributed to the anisotropy of the mAb PPIs. Our results suggest that not only the strength but also the patchiness of short-range attractive PPIs should be explicitly accounted for by theoretical approaches aimed at predicting the shear rate-dependent viscosity of dense mAb solutions.

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.

Comparison of Huggins Coefficients and Osmotic Second Virial Coefficients of Buffered Solutions of Monoclonal Antibodies

The Huggins coefficient kH is a well-known metric for quantifying the increase in solution viscosity arising from intermolecular interactions in relatively dilute macromolecular solutions, and there has been much interest in this solution property in connection with developing improved antibody therapeutics. While numerous kH measurements have been reported for select monoclonal antibodies (mAbs) solutions, there has been limited study of kH in terms of the fundamental molecular interactions that determine this property. In this paper, we compare measurements of the osmotic second virial coefficient B22, a common metric of intermolecular and interparticle interaction strength, to measurements of kH for model antibody solutions. This comparison is motivated by the seminal work of Russel for hard sphere particles having a short-range "sticky" interparticle interaction, and we also compare our data with known results for uncharged flexible polymers having variable excluded volume interactions because proteins are polypeptide chains. Our observations indicate that neither the adhesive hard sphere model, a common colloidal model of globular proteins, nor the familiar uncharged flexible polymer model, an excellent model of intrinsically disordered proteins, describes the dependence of kH of these antibodies on B22. Clearly, an improved understanding of protein and ion solvation by water as well as dipole-dipole and charge-dipole effects is required to understand the significance of kH from the standpoint of fundamental protein-protein interactions. Despite shortcomings in our theoretical understanding of kH for antibody solutions, this quantity provides a useful practical measure of the strength of interprotein interactions at elevated protein concentrations that is of direct significance for the development of antibody formulations that minimize the solution viscosity.

A Multi-Method Approach to Assess the Self-Interaction Behavior of Infliximab

Attractive self-interaction processes in antibody formulations increase the risk of aggregation and extraordinarily elevated viscosity at high protein concentrations. These challenges affect manufacturing and application. This study aimed to understand the self-interaction process of Infliximab as a model system with pronounced attractive self-interaction. The association mechanism was studied by a multi-method approach comprising analytical ultracentrifugation, dynamic light scattering, small angle X-ray scattering, self-interaction bio-layer interferometry and hydrogen-deuterium exchange mass spectrometry. Based on our results, both Fab and Fc regions of Infliximab are involved in self-interaction. We hypothesize a mechanism based on electrostatic interactions of polar and charged residues within the identified areas of the heavy and the light chain of the mAb. The combination of fast and reliable screening methods and low throughput but high resolution methods can contribute to detailed characterization and deeper understanding of specific self-interaction processes.

Monoclonal Antibody Aggregation near Silicone Oil-Water Interfaces

In this work, we study the hydrodynamic behavior of monoclonal antibodies in the presence of silicone oil-water interfaces. We model the antibody molecules using a coarse-grained 24-bead model, where two beads are used to represent each antibody domain. We consider the spatial variation of the antibody polarity in our model as each bead represents a set of hydrophilic or hydrophobic amino acids. We use the dissipative particle dynamics scheme to represent the coarse-grained force field which governs the motion of the beads. In addition, interprotein interactions are modeled using an electrostatic force field. The model parameters are determined by comparing the structure factor against experimental structure factor data ranging from a low concentration regime (10 mg/mL) to a high concentration regime (150 mg/mL). Next, we conduct simulations for a suspension of antibody molecules in the presence of silicone oil-water interfaces. Protein loss from the bulk solution is noticed as the molecules adsorb at the interface. We observe dynamic cluster formation in the solution bulk and at the interface, as the antibody molecules self-associate along their trajectories. We quantify the aggregation using a density clustering algorithm and investigate the effect of the antibody concentration on the diffusivity of the antibody solution, aggregation propensity, and protein loss from the bulk. Our study shows that numerical simulations can be an important tool for understanding the molecular mechanisms driving protein aggregation near hydrophobic interfaces.

Machine Learning Applied to Determine the Molecular Descriptors Responsible for the Viscosity Behavior of Concentrated Therapeutic Antibodies

Predicting the solution viscosity of monoclonal antibody (mAb) drug products remains as one of the main challenges in antibody drug design, manufacturing, and delivery. In this work, the concentration-dependent solution viscosity of 27 FDA-approved mAbs was measured at pH 6.0 in 10 mM histidine-HCl. Six mAbs exhibited high viscosity (>30 cP) in solutions at 150 mg/mL mAb concentration. Combining molecular modeling and machine learning feature selection, we found that the net charge in the mAbs and the amino acid composition in the Fv region are key features which govern the viscosity behavior. For mAbs whose behavior was not dominated by charge effects, we observed that high viscosity is correlated with more hydrophilic and fewer hydrophobic residues in the Fv region. A predictive model based on the net charges of mAbs and a high viscosity index is presented as a fast screening tool for classifying low- and high-viscosity mAbs.

Dissecting the molecular basis of high viscosity of monospecific and bispecific IgG antibodies

Some antibodies exhibit elevated viscosity at high concentrations, making them poorly suited for therapeutic applications requiring administration by injection such as subcutaneous or ocular delivery. Here we studied an anti-IL-13/IL-17 bispecific IgG₄ antibody, which has anomalously high viscosity compared to its parent monospecific antibodies. The viscosity of the bispecific IgG₄ in solution was decreased by only ~30% in the presence of NaCl, suggesting electrostatic interactions are insufficient to fully explain the drivers of viscosity. Intriguingly, addition of arginine-HCl reduced the viscosity of the bispecific IgG₄ by ~50% to its parent IgG level. These data suggest that beyond electrostatics, additional types of interactions such as cation-π and/or π-π may contribute to high viscosity more significantly than previously understood. Molecular dynamics simulations of antibody fragments in the mixed solution of free arginine and explicit water were conducted to identify hotspots involved in self-interactions. Exposed surface aromatic amino acids displayed an increased number of contacts with arginine. Mutagenesis of the majority of aromatic residues pinpointed by molecular dynamics simulations effectively decreased the solution's viscosity when tested experimentally. This mutational method to reduce the viscosity of a bispecific antibody was extended to a monospecific anti-GCGR IgG₁ antibody with elevated viscosity. In all cases, point mutants were readily identified that both reduced viscosity and retained antigen-binding affinity. These studies demonstrate a new approach to mitigate high viscosity of some antibodies by mutagenesis of surface-exposed aromatic residues on complementarity-determining regions that may facilitate some clinical applications.

Structure-based charge calculations for predicting isoelectric point, viscosity, clearance, and profiling antibody therapeutics

The effect of hydrophobicity on antibody aggregation is well understood, and it has been shown that charge calculations can be useful for high-concentration viscosity and pharmacokinetic (PK) clearance predictions. In this work, structure-based charge descriptors are evaluated for their predictive performance on recently published antibody pI, viscosity, and clearance data. From this, we devised four rules for therapeutic antibody profiling which address developability issues arising from hydrophobicity and charged-based solution behavior, PK, and the ability to enrich for those that are approved by the U.S. Food and Drug Administration. Differences in strategy for optimizing the solution behavior of human IgG1 antibodies versus the IgG2 and IgG4 isotypes and the impact of pH alterations in formulation are discussed.

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.

Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development

Developing ultra-high concentration biotherapeutics drug products can be challenging due to increased viscosity, processing, and stability issues. Excipients used to alleviate these concerns are traditionally evaluated at lower protein concentrations. This study investigates whether classically known modulators of stability and viscosity at low (<50 mg/mL) to high (>50 - 150 mg/mL) protein concentrations are beneficial in ultra-high (>150 mg/mL) concentration protein formulations and drug products. This study evaluates the effect of arginine monohydrochloride, proline, and lysine monohydrochloride on viscosity and concentratability at different high and ultra-high protein concentrations using a monoclonal antibody, mAbN, formulation as a candidate protein system. The effect of excipients on the viscosity and concentratability (rate and extent) was different at high versus ultra-high protein concentrations. These results highlight that classical excipients in literature known to modulate protein interactions at low protein concentrations and reduce viscosity at high protein concentrations may need to be evaluated at target protein concentrations in a product-specific manner while developing ultra-high concentration biologics drug products.

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.

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.

Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity

The ability of antibodies to recognize their target antigens with high specificity is fundamental to their natural function. Nevertheless, therapeutic antibodies display variable and difficult-to-predict levels of nonspecific and self-interactions that can lead to various drug development challenges, including antibody aggregation, abnormally high viscosity, and rapid antibody clearance. Here we report a method for predicting the overall specificity of antibodies in terms of their relative risk for displaying high levels of nonspecific or self-interactions at physiological conditions. We find that individual and combined sets of chemical rules that limit the maximum and minimum numbers of certain solvent-exposed amino acids in antibody variable regions are strong predictors of specificity for large panels of preclinical and clinical-stage antibodies. We also demonstrate how the chemical rules can be used to identify sites that mediate nonspecific interactions in suboptimal antibodies and guide the design of targeted sublibraries that yield variants with high antibody specificity. These findings can be readily used to improve the selection and engineering of antibodies with drug-like specificity.

Modeling and mitigation of high-concentration antibody viscosity through structure-based computer-aided protein design

For an antibody to be a successful therapeutic many competing factors require optimization, including binding affinity, biophysical characteristics, and immunogenicity risk. Additional constraints may arise from the need to formulate antibodies at high concentrations (>150 mg/ml) to enable subcutaneous dosing with reasonable volume (ideally <1.0 mL). Unfortunately, antibodies at high concentrations may exhibit high viscosities that place impractical constraints (such as multiple injections or large needle diameters) on delivery and impede efficient manufacturing. Here we describe the optimization of an anti-PDGF-BB antibody to reduce viscosity, enabling an increase in the formulated concentration from 80 mg/ml to greater than 160 mg/ml, while maintaining the binding affinity. We performed two rounds of structure guided rational design to optimize the surface electrostatic properties. Analysis of this set demonstrated that a net-positive charge change, and disruption of negative charge patches were associated with decreased viscosity, but the effect was greatly dependent on the local surface environment. Our work here provides a comprehensive study exploring a wide sampling of charge-changes in the Fv and CDR regions along with targeting multiple negative charge patches. In total, we generated viscosity measurements for 40 unique antibody variants with full sequence information which provides a significantly larger and more complete dataset than has previously been reported.