Predicting accelerated aggregation rates for monoclonal antibody formulations, and challenges for low-temperature predictions

Extrapolating differential scanning calorimetry data for monoclonal antibodies to low temperatures

For irreversible denaturation transitions such as those exhibited by monoclonal antibodies, differential scanning calorimetry provides the denaturation temperature, Tm, the rate of denaturation at Tm, and the activation energy at Tm. These three quantities are essential but not sufficient for an accurate extrapolation of the rate of denaturation to temperatures of 25 °C and below. We have observed that the activation energy is not constant but temperature dependent due to the existence of an activation heat capacity, Cp,a. It is shown in this paper that a model that incorporates Cp,a is able to account for previous observations like, for example, that increasing the Tm does not always improve the stability at low temperatures; that some antibodies exhibit lower stabilities at 5 °C than at 25 °C; or that low temperature stabilities do not follow the rank order derived from Tm values. Most importantly, the activation heat capacity model is able to reproduce time dependent stabilities measured by size exclusion chromatography at low temperatures.

DSC Derived (Ea & ΔG) Energetics and Aggregation Predictions for mAbs

The Arrhenius energy of activation of unfolding Ea unfolding and Gibbs free energy of unfolding ΔG unfolding have been calculated utilizing DSC differential scanning calorimetry for 4 mAbs (1 biosimilar) in 3 formulations. DSC derived ΔTm melting temperature changes for each mAb domain (CH2, Fab, CH3) at calorimetric scan rates at 60 °C, 90 °C, 150 °C and 200 °C / hr. were utilized to calculate the kinetic Eaunfolding. The DSC derived Ea trend with observed aggregate formation and can be used to predict%HMW formation post 9-month storage at 5 °C and 40 °C for all formulations analyzed. Additionally, thermodynamic ΔG unfolding energies were also derived (Tm, ΔCp and ΔH measurements) for each mAb at every scan rate to observe scan rate dependence of ΔG and for extrapolation to 0 °C/hr. (to report ΔG at true equilibrium conditions). Both derived thermodynamic ΔG and kinetic Ea energies were combined to build full energetic landscapes for mAb unfolding and aggregation. Statistical multivariate analysis of kinetic (Ea CH2, Ea Fab, Ea CH3) energies, thermodynamic (ΔG5 °C and ΔG40 °C) energies and in-silico modeled surface properties was also performed. Analysis revealed key significant parameters contributing to aggregation. These parameters were utilized to build predictive aggregation models for 25 mg/mL mAb formulations stored 9-months at 5 °C and 40 °C.

Designing Robust Monoclonal Antibody Drug Products: Pitfalls of Simplistic Approaches for Stability Prediction

Thermal stability attributes including unfolding onset (Tonset) and mid-point (Tm) are often utilized for efficient development of monoclonal antibody (mAb) products during lead selection and formulation screening workflows. An assumption of direct correlation between thermal and kinetic physical stability underpins this basic approach. While literature reports have substantiated this general approach under specific conditions, clear exceptions have been highlighted alongside. Herein, a set of mAbs formulated under diverse solution conditions to generate a broad array of thermal and kinetic stability profiles were systematically analyzed. Sequence modifications in the Fc region were purposefully engineered to generate a set of low-melting mAbs. A diverse set of excipients were subsequently utilized and shown to modulate the Tm over a wide range. While a general correlation between high Tm and low aggregation rate was observed under accelerated conditions, the predictive utility of Tm under relevant product storage conditions was inadequate at best. Critically, Tm data did not correlate with long-term aggregation rates under refrigerated or room temperature conditions. Even under accelerated conditions, Tm appeared to be a poor predictor of aggregation once it exceeded the solution storage temperature (40°C) by ∼15°C, similar to conditions routinely encountered in the development of canonical mAbs (Tm > 60°C). Pitfalls of simplistic correlative approaches are discussed in the context of practical biologics product development.

Adeno-associated viral capsid stability on anion exchange chromatography column and its impact on empty and full capsid separation

Recombinant adeno-associated viral vector (rAAV) mediated gene therapy is gaining traction in treating genetic disorders. Current rAAV production systems yield a mixture of capsids largely devoid of the transgene (empty capsid) compared with the desired therapeutic product (full capsid). Anion exchange chromatography (AEX) is an attractive method for separating empty and full AAV capsids because of its scalability. Resin types and buffer composition are key considerations for AEX and must support capsid stability to be suitable for downstream processing. We examined the impact of binding durations (0-8 h) using various binding ionic strengths (15-75 mM), pH (7.5-9.0), resin chemistry (POROS XQ, POROS HQ, POROS I, and BIA QA monolith), and proprietary Q resins with different ligand densities for effects on capsid stability. Empty capsids were altered upon extended binding, leading to retention time shifts and loss of resolution between empty and full capsids. Viral capsid protein analysis reveals that full capsids have more viral capsid protein 3 (VP3) proteins than empty capsids. Analytical hydrophilic liquid chromatography showed that empty capsid retention time shift is accompanied by changes to the empty capsid's native VP3 protein. Among the potential stabilizing additives considered, magnesium chloride was the most effective at reducing negative impacts caused by extended binding.

Antibody fragments functionalized with non-canonical amino acids preserving structure and functionality - A door opener for new biological and therapeutic applications

Functionalization of proteins by incorporating reactive non-canonical amino acids (ncAAs) has been widely applied for numerous biological and therapeutic applications. The requirement not to lose the intrinsic properties of these proteins is often underestimated and not considered. Main purpose of this study was to answer the question whether functionalization via residue-specific incorporation of the ncAA N6-[(2-Azidoethoxy) carbonyl]-l-lysine (Azk) influences the properties of the anti-tumor-necrosis-factor-α-Fab (FTN2). Therefore, FTN2Azk variants with different Azk incorporation sites were designed and amber codon suppression was used for production. The functionalized FTN2Azk variants were efficiently produced in fed-batch like μ-bioreactor cultivations in the periplasm of E. coli displaying correct structure and antigen binding affinities comparable to those of wild-type FTN2. Our FTN2Azk variants with reactive handles for diverse conjugates enable tracking of recombinant protein in the production cell, pharmacological studies and translation into new pharmaceutical applications.

Native and Non-Native aggregation pathways of antibodies anticipated by cold-accelerated studies

Assessment of cold stability is essential for manufacture and commercialization of biotherapeutics. Storage stability is often estimated by measuring accelerated rates at elevated temperature and using mathematical models (as the Arrhenius equation). Although, this strategy often leads to an underestimation of protein aggregation during storage. In this work, we measured the aggregation rates of two antibodies in a broad temperature range (from 60 °C to -25 °C), using an isochoric cooling method to prevent freezing of the formulations below 0 °C. Both antibodies evidenced increasing aggregation rates when approaching extreme temperatures, because of hot and cold denaturation. This behavior was modelled using Arrhenius and Gibbs-Helmholtz equations, which enabled to deconvolute the contribution of unfolding from the protein association kinetics. This approach made possible to model the aggregation rates at refrigeration temperature (5 °C) in a relatively short timeframe (1-2 weeks) and using standard characterization techniques (SEC-HPLC and DLS).

Antibodies Adsorbed to the Air-Water Interface Form Soft Glasses

When monoclonal antibodies are exposed to an air-water interface, they form aggregates, which negatively impacts their performance. Until now, the detection and characterization of interfacial aggregation have been difficult. Here, we exploit the mechanical response imparted by interfacial adsorption by measuring the interfacial shear rheology of a model antibody, anti-streptavidin immunoglobulin-1 (AS-IgG1), at the air-water interface. Strong viscoelastic layers of AS-IgG1 form when the protein is adsorbed from the bulk solution. Creep experiments correlate the compliance of the interfacial protein layer with the subphase solution pH and bulk concentration. These, along with oscillatory strain amplitude and frequency sweeps, show that the viscoelastic behavior of the adsorbed layers is that of a soft glass with interfacial shear moduli on the order of 10-3 Pa m. Shifting the creep compliance curves under different applied stresses forms master curves consistent with stress-time superposition of soft interfacial glasses. The interfacial rheology results are discussed in the context of the interface-mediated aggregation of AS-IgG1.

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.

Effects of Salts and Surface Charge on the Biophysical Stability of a Low pI Monoclonal Antibody

The impact of five representative Hofmeister salts (NaCl, KCl, MgCl₂, Na₂SO₄, and NaSCN) on the thermal stability and aggregation kinetics of a slightly acidic monoclonal antibody (mAb) were investigated under different pH conditions. The thermal stability of the mAb was assessed by measuring the lowest unfolding transition temperature, T_m, with differential scanning fluorimetry. MgCl₂ and NaSCN significantly decreased T_m at all three charged states of the mAb, but to the greatest extent when the mAb surface charge was net positive. Non-native aggregation kinetics was monitored by measuring Rayleigh light scattering. When the mAb surface charge was net positive or net neutral, the nucleation rate increased non-monotonically with MgCl₂ and NaSCN but decreased monotonically with NaCl, KCl, and Na₂SO₄. By contrast, when the mAb surface was negatively charged, there were only minor changes in the nucleation rate with all salts tested. Furthermore, there was less structural perturbation and slower aggregation rates when the mAb was net negatively charged than when it was net neutrally or positively charged. The observed salt effects on thermal unfolding are consistent with ion-specific mechanisms dominated by short-range amide backbone binding. On the other hand, the salt effects on nucleation rates appear to be influenced by both amide backbone binding and long-range electrostatic binding of ions to charged amino acid side chains.

Accelerated Storage for Shelf-Life Prediction of Lyophiles: Temperature Dependence of Degradation of Amorphous Small Molecular Weight Drugs and Proteins

Prediction of lyophilized product shelf-life using accelerated stability data requires understanding the temperature dependence of the degradation rate. Despite the abundance of published studies on stability of freeze-dried formulations and other amorphous materials, there are no definitive conclusions on the type of pattern one can expect for the temperature dependence of degradation. This lack of consensus represents a significant gap which may impact development and regulatory acceptance of freeze-dried pharmaceuticals and biopharmaceuticals. Review of the literature demonstrates that the temperature dependence of degradation rate constants in lyophiles can be represented by the Arrhenius equation in most cases. In some instances there is a break in the Arrhenius plot around the glass transition temperature or a related characteristic temperature. The majority of the activation energies (E_a), which are reported for various degradation pathways in lyophiles, falls in the range of 8 to 25 kcal/mol. The degradation E_a values for lyophiles are compared with the E_a for relaxation processes and diffusion in glasses, as wells as solution chemical reactions. Collectively, analysis of the literature demonstrates that the Arrhenius equation represents a reasonable empirical tool for analysis, presentation, and extrapolation of stability data for lyophiles, provided that specific conditions are met.

Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis

Monoclonal antibodies are the fastest growing class of therapeutics. However, aggregation limits their shelf life and can lead to adverse immune responses. Assessment and optimization of the long-term antibody stability are therefore key challenges in the biologic drug development. Here, we present a platform based on the analysis of temperature-dependent aggregation data that can dramatically shorten the assessment of the long-term aggregation stability and thus accelerate the optimization of antibody formulations. For a set of antibodies used in the therapeutic areas from oncology to rheumatology and osteoporosis, we obtain an accurate prediction of aggregate fractions for up to three years using the data obtained on a much shorter time scale. Significantly, the strategy combining kinetic and thermodynamic analysis not only contributes to a better understanding of the molecular mechanisms of antibody aggregation but has already proven to be very effective in the development and production of biological therapeutics.

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics

Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies. Features obtained from molecular dynamics simulations of the full-length antibody and sequences were used for machine learning model construction. We found a k-nearest neighbors regression model with two features, spatial positive charge map on the CDRH2 and solvent-accessible surface area of hydrophobic residues on the variable fragment, gives the best performance for predicting antibody aggregation rates (r = 0.89). For the viscosity classification model, the model with the highest accuracy is a logistic regression model with two features, spatial negative charge map on the heavy chain variable region and spatial negative charge map on the light chain variable region. The accuracy and the area under precision recall curve of the classification model from validation tests are 0.86 and 0.70, respectively. In addition, we combined data from another 27 commercial mAbs to develop a viscosity predictive model. The best model is a logistic regression model with two features, number of hydrophobic residues on the light chain variable region and net charges on the light chain variable region. The accuracy and the area under precision recall curve of the classification model are 0.85 and 0.6, respectively. The aggregation rates and viscosity models can be used to predict antibody stability to facilitate pharmaceutical development.

Protein Engineering and HDX Identify Structural Regions of G-CSF Critical to Its Stability and Aggregation

The protein engineering and formulation of therapeutic proteins for prolonged shelf-life remain a major challenge in the biopharmaceutical industry. Understanding the influence of mutations and formulations on the protein structure and dynamics could lead to more predictive approaches to their improvement. Previous intrinsic fluorescence analysis of the chemically denatured granulocyte colony-stimulating factor (G-CSF) suggested that loop AB could subtly reorganize to form an aggregation-prone intermediate state. Hydrogen deuterium exchange mass spectrometry (HDX-MS) has also revealed that excipient binding increased the thermal unfolding transition midpoint (T_m) by stabilizing loop AB. Here, we have combined protein engineering with biophysical analyses and HDX-MS to reveal that increased exchange in a core region of the G-CSF comprising loop AB (ABI, a small helix, ABII) and loop CD packed onto helix B and the beginning of loop BC leads to a decrease in T_m and higher aggregation rates. Furthermore, some mutations can increase the population of the aggregation-prone conformation within the native ensemble, as measured by the greater local exchange within this core region.

Evaluating the combined impact of temperature and application of interfacial dilatational stresses on surface-mediated protein particle formation in monoclonal antibody formulations

Formation of submicron and subvisible protein particles (0.1-100 μm) present a major obstacle during processing and storage of therapeutic proteins. While protein aggregation resulting in particle formation is well-understood in bulk solution, the mechanisms of aggregation due to interfacial stresses is less understood. Particularly, in this study, we focus on understanding the combined effect of temperature and application of interfacial dilatational stresses, on interface-induced protein particle formation, using two industrially relevant monoclonal antibodies (mAbs). The surface activity of Molecule C (MC) and Molecule B (MB) were measured at room temperature (RT) and 4°C in the absence and presence of interfacial dilatation stress using a Langmuir trough. These results were correlated with Micro-flow imaging (MFI) to characterize formation of subvisible protein particles at the interface and in the bulk solution. Our results show that the surface activity for both proteins is temperature dependent. However, the extent of the impact of temperature on the mechanical properties of the monomolecular protein films when subjected to dilatational stresses is protein dependent. Protein particle analysis provided evidence that protein particles formed in bulk solution originate at the interface and are dependent on both application of thermal stresses and interfacial dilatational stresses. In the absence of any interfacial stresses, more and larger protein particles were formed at the interface at RT than at 4°C. When mAb formulations are subjected to interfacial dilatational stresses, protein particle formation in bulk solution was found to be temperature dependent. Together our results validate that mAb solutions maintained at 4°C can lower the surface activity of proteins and reduce their tendency to form interface-induced protein particles both in the absence and presence of interfacial dilatational stresses.

In Situ Monitoring of Protein Unfolding/Structural States under Cold High-Pressure Stress

Biopharmaceutical formulations may be compromised by freezing, which has been attributed to protein conformational changes at a low temperature, and adsorption to ice-liquid interfaces. However, direct measurements of unfolding/conformational changes in sub-0 °C environments are limited because at ambient pressure, freezing of water can occur, which limits the applicability of otherwise commonly used analytical techniques without specifically tailored instrumentation. In this report, small-angle neutron scattering (SANS) and intrinsic fluorescence (FL) were used to provide in situ analysis of protein tertiary structure/folding at temperatures as low as -15 °C utilizing a high-pressure (HP) environment (up to 3 kbar) that prevents water from freezing. The results show that the α-chymotrypsinogen A (aCgn) structure is reasonably maintained under acidic pH (and corresponding pD) for all conditions of pressure and temperature tested. On the other hand, reversible structural changes and formation of oligomeric species were detected near -10 °C via HP-SANS for ovalbumin under neutral pD conditions. This was found to be related to the proximity of the temperature of cold denaturation of ovalbumin (T_CD ∼ -17 °C; calculated via isothermal chemical denaturation and Gibbs-Helmholtz extrapolation) rather than a pressure effect. Significant structural changes were also observed for a monoclonal antibody, anti-streptavidin IgG1 (AS-IgG1), under acidic conditions near -5 °C and a pressure of ∼2 kbar. The conformational perturbation detected for AS-IgG1 is proposed to be consistent with the formation of unfolding intermediates such as molten globule states. Overall, the in situ approaches described here offer a means to characterize the conformational stability of biopharmaceuticals and proteins more generally under cold-temperature stress by the assessment of structural alteration, self-association, and reversibility of each process. This offers an alternative to current ex situ methods that are based on higher temperatures and subsequent extrapolation of the data and interpretations to the cold-temperature regime.

Long-term stability predictions of therapeutic monoclonal antibodies in solution using Arrhenius-based kinetics

Long-term stability of monoclonal antibodies to be used as biologics is a key aspect in their development. Therefore, its possible early prediction from accelerated stability studies is of major interest, despite currently being regarded as not sufficiently robust. In this work, using a combination of accelerated stability studies (up to 6 months) and first order degradation kinetic model, we are able to predict the long-term stability (up to 3 years) of multiple monoclonal antibody formulations. More specifically, we can robustly predict the long-term stability behaviour of a protein at the intended storage condition (5 °C), based on up to six months of data obtained for multiple quality attributes from different temperatures, usually from intended (5 °C), accelerated (25 °C) and stress conditions (40 °C). We have performed stability studies and evaluated the stability data of several mAbs including IgG1, IgG2, and fusion proteins, and validated our model by overlaying the 95% prediction interval and experimental stability data from up to 36 months. We demonstrated improved robustness, speed and accuracy of kinetic long-term stability prediction as compared to classical linear extrapolation used today, which justifies long-term stability prediction and shelf-life extrapolation for some biologics such as monoclonal antibodies. This work aims to contribute towards further development and refinement of the regulatory landscape that could steer toward allowing extrapolation for biologics during the developmental phase, clinical phase, and also in marketing authorisation applications, as already established today for small molecules.

Combining Unfolding Reversibility Studies and Molecular Dynamics Simulations to Select Aggregation-Resistant Antibodies

The efficient development of new therapeutic antibodies relies on developability assessment with biophysical and computational methods to find molecules with drug-like properties such as resistance to aggregation. Despite the many novel approaches to select well-behaved proteins, antibody aggregation during storage is still challenging to predict. For this reason, there is a high demand for methods that can identify aggregation-resistant antibodies. Here, we show that three straightforward techniques can select the aggregation-resistant antibodies from a dataset with 13 molecules. The ReFOLD assay provided information about the ability of the antibodies to refold to monomers after unfolding with chemical denaturants. Modulated scanning fluorimetry (MSF) yielded the temperatures that start causing irreversible unfolding of the proteins. Aggregation was the main reason for poor unfolding reversibility in both ReFOLD and MSF experiments. We therefore performed temperature ramps in molecular dynamics (MD) simulations to obtain partially unfolded antibody domains in silico and used CamSol to assess their aggregation potential. We compared the information from ReFOLD, MSF, and MD to size-exclusion chromatography (SEC) data that shows whether the antibodies aggregated during storage at 4, 25, and 40 °C. Contrary to the aggregation-prone molecules, the antibodies that were resistant to aggregation during storage at 40 °C shared three common features: (i) higher tendency to refold to monomers after unfolding with chemical denaturants, (ii) higher onset temperature of nonreversible unfolding, and (iii) unfolding of regions containing aggregation-prone sequences at higher temperatures in MD simulations.

A Rapid, Small-Volume Approach to Evaluate Protein Aggregation at Air-Water Interfaces

Non-native protein aggregation is a common concern for biopharmaceuticals. A given protein may aggregate through a variety of mechanisms that depend on solution and physico-chemical stress conditions. A thorough evaluation of aggregation behavior for a protein under all conditions of interest is necessary to ensure drug safety and efficacy. This work introduces a rapid, small-volume approach to evaluate protein aggregation propensity upon exposure to air-water interfaces (AWI). A microtensiometer apparatus is used to aerate a small volume of a protein solution with microbubbles for short periods of time (≤10 s). Sub-visible particles that form are captured and analyzed using backgrounded membrane imaging. This allows one to capture all particles in the solution while being sample sparing. The surface-mediated aggregation of two model monoclonal antibodies (MAbs) and a globular protein (aCgn) was tested as a function of pH and temperature. Temperature had a negligible effect under the rapid interface turnover time scales with this technique. Electrostatic protein-protein interactions, mediated by pH changes, were more influential for particle formation via AWI. Nonionic surfactants substantially reduced particle formation for all MAb solutions, but not aCgn. The results are contrasted with expectations when exposing samples to much larger air-water interfacial stress.

Room Temperature Intrinsic Emission Ratio of BSA Correlates With Percent Aggregates During Long-Term Storage

Successful formulation development hinges on the ability to screen and identify excipients that stabilize drug products during long-term storage. Biophysical and accelerated stability studies are used to screen for excipients that stabilize protein drug products. However, these studies are not always predictive of aggregation during long-term storage. In this study, we used multivariate experimentation to compare the effectiveness of intrinsic fluorescence and size exclusion chromatography accelerated stability parameters to predict excipients that stabilized bovine serum albumin (BSA) against aggregation on long-term storage at 4 °C. Emission intensity ratio (IR_330/350) data was more sensitive than emission maxima (λ_max) or intensity measurements in identifying significant factors and interactions. We observed the expected inverse correlation between the mid-points of fluorescence thermal transitions (T_ms) and insoluble aggregates at 4 and 40 °C. However, there were positive correlations between T_ms and % aggregates at 4 °C, indicating that if T_m was used as a predictive tool, it would select formulations that promoted soluble aggregates on long-term storage. Ambient temperature IR_330/350 measurements identified excipients that reduced BSA soluble aggregates on long-term storage. The results show ambient temperature emission ratio measurements can be useful for protein formulation development.

Accelerated Aggregation Studies of Monoclonal Antibodies: Considerations for Storage Stability

Aggregation of mAbs is a crucial concern with respect to their safety and efficacy. Among the various properties of protein aggregates, it is emerging that their size can potentially impact their immunogenicity. Therefore, stability studies of antibody formulations should not only evaluate the rate of monomer loss but also determine the size distribution of the protein aggregates, which in turn depends on the aggregation mechanism. Here, we study the aggregation behavior of different formulations of 2 monoclonal immunoglobulins (IgGs) in the temperature range from 5°C to 50°C over 52 weeks of storage. We show that the aggregation kinetics of both antibodies follow non-Arrhenius behavior and that the aggregation mechanisms change between 40°C and 5°C, leading to different types of aggregates. Specifically, for a given monomer conversion, dimer formation dominates at low temperatures, while larger aggregates are formed at higher temperatures. We further show that the stability ranking of different molecules as well as of different formulations is drastically different at 40°C and 5°C while it correlates better between 30°C and 5°C. Our findings have implications for the level of information provided by accelerated aggregation studies with respect to protein stability under storage conditions.

Isotonic concentrations of excipients control the dimerization rate of a therapeutic immunoglobulin G1 antibody during refrigerated storage based on their rank order of native-state interaction

Inert co-solutes, or excipients, are often included in protein biologic formulations to adjust the tonicity of liquid dosage forms intended for subcutaneous delivery. Despite the low concentration of their use, many of these excipients alter protein-protein interactions such as dimerization and aggregation rates of high concentration monoclonal antibody (mAb) therapeutics to varying extents during long-term refrigerated clinical storage, challenging the formulation scientist to make informed excipient selections at the earliest stages of development when protein supply and time are often limited. The objectives of this study were to better understand how isotonic concentrations of excipients influence the dimerization rates of a model mAb stored at refrigerated and room temperatures and explore protein sparing biophysical methods capable of predicting this dependence. Despite their prevalence of use in the biopharmaceutical industry, methods for assessing conformational stability such differential scanning calorimetry and isothermal equilibrium unfolding showed little predictive power and we highlight some of the assumptions and technical challenges of their use with mAbs. Conversely, measures of colloidal stability of the native-state such as preferential interaction coefficients measured by vapor pressure osmometry and solubility assessed by polyethylene-glycol induced precipitation correlated reasonably well with the mAb dimerization data and are most consistent with the excipients tested minimizing dimerization by interacting favorably with the residues comprising the protein-protein association interface.

Fibril Nucleation Kinetics of a Pharmaceutical Peptide: The Role of Conformation Stability, Formulation Factors, and Temperature Effect

Peptide aggregation, such as the formation of fibrils, could pose a significant challenge for the stability of parenteral peptide drugs. To ensure a robust peptide formulation, a thorough understanding of aggregation kinetics and the development of appropriate accelerated testing conditions are necessary. The present research investigated factors that impact the fibrillation kinetics of a helical 29mer pharmaceutical peptide (peptide A) and attempts to correlate results of accelerated kinetic studies with real time kinetics. Conformational flexibility of the peptide and its potential impact on aggregation kinetics were thoroughly evaluated. Three orthogonal approaches to evaluate aggregation kinetics were assessed, thioflavin T fluorescence, turbidity, and soluble peptide concentration. The results from the methods demonstrated that peptide A showed nucleated polymerization kinetics. The lag time of the fibrillation process depends heavily on pH, ionic strength, temperature, agitation, and substrate interface. The temperature-dependent fibril nucleation kinetics follow Arrhenius behavior, despite a helical fold in the peptide structure. This finding suggests a potential opportunity to leverage accelerated testing conditions to project the long-term performance at storage temperatures. The present study provides both fundamental understanding and practical approaches to mitigate the aggregation risk for pharmaceutical peptides with a strong tendency to form fibrils.

Osmolytes in vaccine production, flocculation and storage: a critical review

Small molecule osmolytes, responsible for protecting stresses have long been known to rescue proteins and enzymes from loss of function. In addition to protecting macromolecules integrity, many osmolytes also act as potential antioxidant and also help to prevent protein aggregation, amyloid formation or misfolding, and therefore are considered promising molecules for neurodegenerative and many other genetic diseases. Osmolytes are also known to be involved in the regulation of several key immunological processes. In the present review we discuss in detail the effect of these compounds on important aspects of vaccines i.e., increasing the efficiency, production and purification steps. The present review therefore will help researchers to make a better strategy in vaccine production to formulation by incorporating specific and appropriate osmolytes in the processes.

Parallel chromatography and in situ scattering to interrogate competing protein aggregation pathways

Protein aggregation can follow different pathways, and these can result in different net aggregation rates and kinetic profiles. α-chymotypsinogen A (aCgn) was used as a model system to quantitatively and qualitatively assess an approach that combines ex situ size-exclusion chromatography (SEC) with in situ laser scattering (LS) to monitor aggregation vs. time. Aggregation was monitored for a series of temperatures and initial dimer (ID) levels for starting conditions that were primarily (> 97%) monomer, and under initial-rate conditions (limited to low monomer conversion-less than 20% monomer mass loss), as these conditions are of most to interest to many pharmaceutical and biotechnology applications. SEC results show that modest decreases of ID levels can greatly reduce monomer loss rates, but do not affect the effective activation energy for aggregation. The normalized aggregation rates determined from LS were typically ∼ 1 order of magnitude higher than the corresponding rates from SEC. Furthermore, LS signals vs. time became variable and highly nonlinear with decreasing ID level, temperature, and/or total protein concentration. Temperature-cycling LS experiments showed this corresponded to conditions where dimer/oligomer "seeding" was suppressed, and high levels of reversible oligomers ("prenuclei") were formed prior to "nucleation" and growth of stable aggregates. In those conditions, aggregation rates inferred from LS and SEC are greatly different, as the techniques monitor different stages of the aggregation process. Overall, the results illustrate an approach for interrogating non-native protein aggregation pathways, and potential pitfalls if one relies on a single method to monitor aggregation-this holds more generally than the particular methods here.

Modification of the kinetic stability of immunoglobulin G by solvent additives

Biophysical properties of antibody-based biopharmaceuticals are a critical part of their release criteria. In this context, finding the appropriate formulation is equally important as optimizing their intrinsic biophysical properties through protein engineering, and both are mutually dependent. Most previous studies have empirically tested the impact of additives on measures of colloidal stability, while mechanistic aspects have usually been limited to only the thermodynamic stability of the protein. Here we emphasize the kinetic impact of additives on the irreversible denaturation steps of immunoglobulins G (IgG) and their antigen-binding fragments (Fabs), as these are the key committed steps preceding aggregation, and thus especially informative in elucidating the molecular parameters of activity loss. We examined the effects of ten additives on the conformational kinetic stability by differential scanning calorimetry (DSC), using a recently developed three-step model containing both reversible and irreversible steps. The data highlight and help to rationalize different effects of the additives on the properties of full-length IgG, analyzed by onset and aggregation temperatures as well as by kinetic parameters derived from our model. Our results further help to explain the observation that stabilizing mutations in the antigen-binding fragment (Fab) significantly affect the kinetic parameters of its thermal denaturation, but not the aggregation properties of the full-length IgGs. We show that the proper analysis of DSC scans for full-length IgGs and their corresponding Fabs not only helps in ranking their stability in different formats and formulations, but provides important mechanistic insights for improving the conformational kinetic stability of IgGs.

Analysis of IgG kinetic stability by differential scanning calorimetry, probe fluorescence and light scattering

Monoclonal antibodies of the immunoglobulin G (IgG) type have become mainstream therapeutics for the treatment of many life-threatening diseases. For their successful application in the clinic and a favorable cost-benefit ratio, the design and formulation of these therapeutic molecules must guarantee long-term stability for an extended period of time. Accelerated stability studies, e.g., by employing thermal denaturation, have the great potential for enabling high-throughput screening campaigns to find optimal molecular variants and formulations in a short time. Surprisingly, no validated quantitative analysis of these accelerated studies has been performed yet, which clearly limits their application for predicting IgG stability. Therefore, we have established a quantitative approach for the assessment of the kinetic stability over a broad range of temperatures. To this end, differential scanning calorimetry (DSC) experiments were performed with a model IgG, testing chaotropic formulations and an extended temperature range, and they were subsequently analyzed by our recently developed three-step sequential model of IgG denaturation, consisting of one reversible and two irreversible steps. A critical comparison of the predictions from this model with data obtained by an orthogonal fluorescence probe method, based on 8-anilinonaphthalene-1-sulfonate binding to partially unfolded states, resulted in very good agreement. In summary, our study highlights the validity of this easy-to-perform analysis for reliably assessing the kinetic stability of IgGs, which can support accelerated formulation development of monoclonal antibodies by ranking different formulations as well as by improving colloidal stability models.

Prediction and characterization of the stability enhancing effect of the Cherry-Tag™ in highly concentrated protein solutions by complex rheological measurements and MD simulations

Solution stability attributes are one of the key parameters within the production and launching phase of new biopharmaceuticals. Instabilities of active biological compounds can reduce the yield of biopharmaceutical productions, and may induce undesired reactions in patients, such as immunogenic rejections. Protein solution stability thus needs to be engineered and monitored throughout production and storage. In contrast to the gold standard of long-term storage experiments applied in industry, novel experimental and in silico molecular dynamics tools for predicting protein solution stability can be applied within several minutes or hours. Here, a rheological approach in combination with molecular dynamics simulations are presented, for determining and predicting long-term phase behavior of highly concentrated protein solutions. A diversity of liquid phase conditions, including salt type, ionic strength, pH and protein concentration are tested in a Glutathione-S-Transferase (GST) case study, in combination with the enzyme with and without solubility-enhancing Cherry-Tag™. The rheological characterization of GST and Cherry-GST solutions enabled a fast and efficient prediction of protein instabilities without the need of long-term protein phase diagrams. Finally, the strong solubility enhancing properties of the Cherry-Tag™ were revealed by investigating protein surface properties in MD simulations. The tag highly altered the overall surface charge and hydrophobicity of GST, making it less accessible to alteration by the chemical surrounding.

Relating Protein-Protein Interactions and Aggregation Rates From Low to High Concentrations

At low protein concentrations (c2), non-native protein aggregation rates are known to be sensitive to changes in conformational stability and "weak" or "colloidal" protein-protein interactions. Protein-protein interactions are also known to be strong functions of c2. In the present work, protein-protein interactions and rates of aggregation were quantified systematically for a monoclonal antibody (MAb) across a broad range of c2 at pH 5.1 and 6.5, with or without 5 wt/wt % sucrose or 100 mM NaCl present. Aggregation rates were determined from initial-rate analysis with size-exclusion chromatography, and interactions were quantified with static and dynamic laser light scattering. A number of hypotheses were tested regarding whether changes in protein-protein interactions can be predictive of changes in aggregation rates versus c2. Hypotheses were based on (i) changes in thermodynamic activity; (ii) statistical mechanical fluctuation theory; and (iii) surface-contact probabilities. Arguments based on (i) and (ii) were qualitatively inconsistent with experimental rates and scattering. Hypothesis (iii) was reasonably successful and resulted in a semiquantitative correlation between rates and protein-protein interactions across almost 2 orders of magnitude in c2. However, (iii) requires one to assume that the concentration-dependent protein-protein Kirkwood-Buff integral is a reasonable surrogate for contact probabilities.

Modulating non-native aggregation and electrostatic protein-protein interactions with computationally designed single-point mutations

Non-native protein aggregation is a ubiquitous challenge in the production, storage and administration of protein-based biotherapeutics. This study focuses on altering electrostatic protein-protein interactions as a strategy to modulate aggregation propensity in terms of temperature-dependent aggregation rates, using single-charge variants of human γ-D crystallin. Molecular models were combined to predict amino acid substitutions that would modulate protein-protein interactions with minimal effects on conformational stability. Experimental protein-protein interactions were quantified by the Kirkwood-Buff integrals (G22) from laser scattering, and G22 showed semi-quantitative agreement with model predictions. Experimental initial-rates for aggregation showed that increased (decreased) repulsive interactions led to significantly increased (decreased) aggregation resistance, even based solely on single-point mutations. However, in the case of a particular amino acid (E17), the aggregation mechanism was altered by substitution with R or K, and this greatly mitigated improvements in aggregation resistance. The results illustrate that predictions based on native protein-protein interactions can provide a useful design target for engineering aggregation resistance; however, this approach needs to be balanced with consideration of how mutations can impact aggregation mechanisms.

A comparison of biophysical characterization techniques in predicting monoclonal antibody stability

With the rapid growth of biopharmaceutical product development, knowledge of therapeutic protein stability has become increasingly important. We evaluated assays that measure solution-mediated interactions and key molecular characteristics of 9 formulated monoclonal antibody (mAb) therapeutics, to predict their stability behavior. Colloidal interactions, self-association propensity and conformational stability were measured using effective surface charge via zeta potential, diffusion interaction parameter (kD) and differential scanning calorimetry (DSC), respectively. The molecular features of all 9 mAbs were compared to their stability at accelerated (25°C and 40°C) and long-term storage conditions (2-8°C) as measured by size exclusion chromatography. At accelerated storage conditions, the majority of the mAbs in this study degraded via fragmentation rather than aggregation. Our results show that colloidal stability, self-association propensity and conformational characteristics (exposed tryptophan) provide reasonable prediction of accelerated stability, with limited predictive value at 2-8°C stability. While no correlations to stability behavior were observed with onset-of-melting temperatures or domain unfolding temperatures, by DSC, melting of the Fab domain with the CH2 domain suggests lower stability at stressed conditions. The relevance of identifying appropriate biophysical assays based on the primary degradation pathways is discussed.

Aggregation of Antibody Drug Conjugates at Room Temperature: SAXS and Light Scattering Evidence for Colloidal Instability of a Specific Subpopulation

Coupling a hydrophobic drug onto monoclonal antibodies via lysine residues is a common route to prepare antibody-drug conjugates (ADC), a promising class of biotherapeutics. But a few chemical modifications on protein surface often increase aggregation propensity, without a clear understanding of the aggregation mechanisms at stake (loss of colloidal stability, self-assemblies, denaturation, etc.), and the statistical nature of conjugation introduces polydispersity in the ADC population, which raises questions on whether the whole ADC population becomes unstable. To characterize the average interactions between ADC, we monitored small-angle X-ray scattering in solutions of monoclonal IgG1 human antibody drug conjugate, with average degree of conjugation of 0, 2, or 3 drug molecules per protein. To characterize stability, we studied the kinetics of aggregation at room temperature. The intrinsic Fuchs stability ratio of the ADC was estimated from the variation over time of scattered light intensity and hydrodynamic radius, in buffers of varying pH, and at diverse sucrose (0% or 10%) and NaCl (0 or 100 mM) concentrations. We show that stable ADC stock solutions became unstable upon pH shift, well below the pH of maximum average attraction between IgGs. Data indicate that aggregation can be ascribed to a fraction of ADC population usually representing less than 30 mol % of the sample. In contrast to the case of (monodisperse) monoclonal antibodies, our results suggest that a poor correlation between stability and average interaction parameters should be expected as a corollary of dispersity of ADC conjugation. In practice, the most unstable fraction of the ADC population can be removed by filtration, which affects remarkably the apparent stability of the samples. Finally, the lack of correlation between the kinetic stability and variations of the average inter-ADC interactions is tentatively attributed to the uneven nature of charge distributions and the presence of patches on the drug-modified antibodies.

Boosting antibody developability through rational sequence optimization

The application of monoclonal antibodies as commercial therapeutics poses substantial demands on stability and properties of an antibody. Therapeutic molecules that exhibit favorable properties increase the success rate in development. However, it is not yet fully understood how the protein sequences of an antibody translates into favorable in vitro molecule properties. In this work, computational design strategies based on heuristic sequence analysis were used to systematically modify an antibody that exhibited a tendency to precipitation in vitro. The resulting series of closely related antibodies showed improved stability as assessed by biophysical methods and long-term stability experiments. As a notable observation, expression levels also improved in comparison with the wild-type candidate. The methods employed to optimize the protein sequences, as well as the biophysical data used to determine the effect on stability under conditions commonly used in the formulation of therapeutic proteins, are described. Together, the experimental and computational data led to consistent conclusions regarding the effect of the introduced mutations. Our approach exemplifies how computational methods can be used to guide antibody optimization for increased stability.

Mapping the Aggregation Kinetics of a Therapeutic Antibody Fragment

The analytical characterization of biopharmaceuticals is a fundamental step in the early stages of development and prediction of their behavior in bioprocesses. Protein aggregation in particular is a common issue as it affects all stages of product development. In the present work, we investigate the stability and the aggregation kinetics of A33Fab, a therapeutically relevant humanized antibody fragment at a wide range of pH, ionic strength, and temperature. We show that the propensity of A33Fab to aggregate under thermally accelerated conditions is pH and ionic-strength dependent with a stronger destabilizing effect of ionic strength at low pH. In the absence of added salts, A33Fab molecules appear to be protected from aggregation due to electrostatic colloidal repulsion at low pH. Analysis by transmission electron microscopy identified significantly different aggregate species formed at low and high pH. The correlations between apparent midpoints of thermal transitions (Tm,app values), or unfolded mole fractions, and aggregation rates are reported here to be significant only at the elevated incubation temperature of 65 °C, where aggregation from the unfolded state predominates. At all other conditions, particularly at 4-45 °C, aggregation of A33 Fab was predominantly from a native-like state, and the kinetics obeyed Arrhenius behavior. Despite this, the rank order of aggregation rates observed at 45 °C, 23 and 4 °C still did not correlate well to each other, indicating that forced degradation at elevated temperatures was not a good screen for predicting behavior at low temperature.

Arginine dipeptides affect insulin aggregation in a pH- and ionic strength-dependent manner

Solutions containing arginine or mixtures of arginine and other amino acids are commonly used for protein liquid formulations to overcome problems such as high viscosities, aggregation, and phase separation. The aim of this work is to examine whether the stabilizing properties of arginine can be improved by incorporating the amino acid into a dipeptide. A series of arginine-containing dipeptides have been tested for their ability to suppress insulin aggregation over a range of pH and ionic strength. The aggregation is monitored at room temperature using a combination of turbidimetry and light scattering for solutions at pH 5.5 or 3.7, whereas thermal-induced aggregation is measured at pH 7.5. In addition, intrinsic fluorescence has been used to quantify additive binding to insulin. The dipeptide diArg is the most effective additive in solutions at pH 5.5 and 3.7, whereas the dipeptide Arg-Phe almost completely eliminates thermally-induced aggregation of insulin at pH 7.5 up to temperature of 90°C. Insulin has been chosen as a model system because the molecular forces controlling its aggregation are well known. From this understanding, we are able to provide a molecular basis for how the various dipeptides affect insulin aggregation.

Antimicrobial preservatives induce aggregation of interferon alpha-2a: the order in which preservatives induce protein aggregation is independent of the protein

Antimicrobial preservatives (APs) are included in liquid multi-dose protein formulations to combat the growth of microbes and bacteria. These compounds have been shown to cause protein aggregation, which leads to serious immunogenic and toxic side-effects in patients. Our earlier work on a model protein cytochrome c (Cyt c) demonstrated that APs cause protein aggregation in a specific manner. The aim of this study is to validate the conclusions obtained from our model protein studies on a pharmaceutical protein. Interferon α-2a (IFNA2) is available as a therapeutic treatment for numerous immune-compromised disorders including leukemia and hepatitis C, and APs have been used in its multi-dose formulation. Similar to Cyt c, APs induced IFNA2 aggregation, demonstrated by the loss of soluble monomer and increase in solution turbidity. The extent of IFNA2 aggregation increased with the increase in AP concentration. IFNA2 aggregation also depended on the nature of AP, and followed the order m-cresol>phenol>benzyl alcohol>phenoxyethanol. This specific order exactly matched with that observed for the model protein Cyt c. These and previously published results on antibodies and other recombinant proteins suggest that the general mechanism by which APs induce protein aggregation may be independent of the protein.

Role of benzyl alcohol in the unfolding and aggregation of interferon α-2a

Benzyl alcohol (BA) is the most widely used antimicrobial preservative in multidose protein formulations, and has been shown to cause protein aggregation. Our previous work on a model protein cytochrome c demonstrated that this phenomenon occurs via partial unfolding. Here, we examine the validity of these results by investigating the effect of BA on a pharmaceutically relevant protein, interferon α-2a (IFNA2). IFNA2 therapeutic formulations available on the pharmaceutical market contain BA as a preservative. Isothermal aggregation kinetics and temperature scanning demonstrated that BA induced IFNA2 aggregation in a concentration-dependent manner. With increasing concentration of BA, the apparent aggregation temperature of IFNA2 linearly decreased. Denaturant melts measured using protein intrinsic fluorescence and that of the 1-anilinonaphthalene-8-sulfonic acid dye indicated that IFNA2 stability decreased with increasing BA concentration, populating a partially unfolded intermediate. Changes in nuclear magnetic resonance chemical shifts and hydrogen exchange rates identified the structural nature of this intermediate, which correlated with an aggregation "hot-spot" predicted by computational methods. These results indicate that BA induces IFNA2 aggregation by partial unfolding rather than global unfolding of the entire protein, and is consistent with our earlier conclusions from model protein studies.

Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts

Defining a suitable product presentation with an acceptable stability profile over its intended shelf-life is one of the principal challenges in bioproduct development. Accelerated stability studies are routinely used as a tool to better understand long-term stability. Data analysis often employs an overall mass action kinetics description for the degradation and the Arrhenius relationship to capture the temperature dependence of the observed rate constant. To improve predictive accuracy and precision, the current work proposes a least-squares estimation approach with a single nonlinear covariate and uses a polynomial to describe the change in a product attribute with respect to time. The approach, which will be referred to as Arrhenius time-scaled (ATS) least squares, enables accurate, precise predictions to be achieved for degradation profiles commonly encountered during bioproduct development. A Monte Carlo study is conducted to compare the proposed approach with the common method of least-squares estimation on the logarithmic form of the Arrhenius equation and nonlinear estimation of a first-order model. The ATS least squares method accommodates a range of degradation profiles, provides a simple and intuitive approach for data presentation, and can be implemented with ease.