Formulation Development of Therapeutic Monoclonal Antibodies Using High-Throughput Fluorescence and Static Light Scattering Techniques: Role of Conformational and Colloidal Stability

Engineered polymeric excipients for enhancing the stability of protein biologics: Poly(N-isopropylacrylamide)-poly(ethylene glycol) (PNIPAM-PEG) block copolymers

Protein therapeutics, particularly antibodies, depend on maintaining their native structures for optimal function. Hydrophobic interfaces, such as the air-water interface, can trigger protein aggregation and denaturation. While completely avoiding such interfacial exposures during manufacturing and storage is impractical, minimizing them is crucial for enhancing protein drug stability and extending shelf life. In the biologics industry, surfactants like polysorbates are commonly used as additives (excipients) to mitigate these undesirable interfacial exposures. However, polysorbates, the most prevalent choice, have recognized limitations in terms of polydispersity, purity, and stability, prompting the exploration of alternative excipients. The present study identifies poly(N-isopropylacrylamide)-poly(ethylene glycol) (PNIPAM-PEG) block copolymers as a promising alternative to polysorbates. Due to its stronger affinity for the air-water interface, PNIPAM-PEG significantly outperforms polysorbates in enhancing protein stability. This claim is supported by results from multiple tests. Accelerated dynamic light scattering (DLS) experiments demonstrate PNIPAM-PEG's exceptional efficacy in preserving IgG stability against surface-induced aggregation, surpassing conventional polysorbate excipients (Tween 80 and Tween 20) under high-temperature conditions. Additionally, circular dichroism (CD) spectroscopy results reveal conformational alterations associated with aggregation, with PNIPAM-PEG consistently demonstrates a greater protective effect by mitigating negative shifts at λ ≅ 220 nm, indicative of changes in secondary structure. Overall, this study positions PNIPAM-PEG as a promising excipient for antibody therapeutics, facilitating the development of more stable and effective biopharmaceuticals.

Synergistic Effect of Cyclodextrins and Electrolytes at High Concentrations on Protein Aggregation Inhibition

The stabilization of protein therapeutics against aggregation is crucial for maintaining their efficacy and safety. This study investigated the synergistic effects of cyclodextrins (CDs) and electrolytes at high concentrations on the stabilization of immunoglobulin G (IgG), insulin, and adeno-associated virus (AAV) vectors. The effects of 2-hydroxypropyl-β-cyclodextrin (HP-β-CD) combined with various electrolytes were evaluated using human plasma-derived IgG as a model protein. The HP-β-CD and L(+)-arginine hydrochloride combination synergistically increased the onset temperature of protein aggregation and inhibited the formation of soluble and insoluble aggregates during long-term storage. Notably, this synergistic effect was not observed when sucrose was used instead of HP-β-CD. Similar synergistic effects were observed with insulin and AAV vectors. The findings suggest that the stabilization mechanism could potentially involve enhanced interactions between HP-β-CD and IgG, preventing protein-protein interactions. However, the combination did not synergistically improve the solubility of free aromatic amino acids, including tyrosine and tryptophan. This study highlights the potential of using the combination of CDs and electrolytes as a promising formulation strategy for stabilizing complex protein therapeutics. However, further studies are needed to elucidate the underlying mechanisms and generalize the approach to other proteins with varying physicochemical properties.

A First Insight into the Developability of an Immunoglobulin G3: A Combined Computational and Experimental Approach

Immunoglobulin G 3 (IgG3) monoclonal antibodies (mAbs) are high-value scaffolds for developing novel therapies. Despite their wide-ranging therapeutic potential, IgG3 physicochemical properties and developability characteristics remain largely under-characterized. Protein-protein interactions elevate solution viscosity in high-concentration formulations, impacting physicochemical stability, manufacturability, and the injectability of mAbs. Therefore, in this manuscript, the key molecular descriptors and biophysical properties of a model anti-IL-8 IgG1 and its IgG3 ortholog are characterized. A computational and experimental framework was applied to measure molecular descriptors impacting their downstream developability. Findings from this approach underpin a detailed understanding of the molecular characteristics of IgG3 mAbs as potential therapeutic entities. This work is the first report examining the manufacturability of IgG3 for high-concentration mAb formulations. While poorer conformational and colloidal stability and elevated solution viscosity were observed for IgG3, future efforts controlling surface potential through sequence-engineering of solvent-accessible patches can be used to improve biophysical parameters that dictate mAb developability.

Stability of Protein Pharmaceuticals: Recent Advances

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

Nanobodies to multiple spike variants and inhalation of nanobody-containing aerosols neutralize SARS-CoV-2 in cell culture and hamsters

The ongoing threat of COVID-19 has highlighted the need for effective prophylaxis and convenient therapies, especially for outpatient settings. We have previously developed highly potent single-domain (VHH) antibodies, also known as nanobodies, that target the Receptor Binding Domain (RBD) of the SARS-CoV-2 Spike protein and neutralize the Wuhan strain of the virus. In this study, we present a new generation of anti-RBD nanobodies with superior properties. The primary representative of this group, Re32D03, neutralizes Alpha to Delta as well as Omicron BA.2.75; other members neutralize, in addition, Omicron BA.1, BA.2, BA.4/5, and XBB.1. Crystal structures of RBD-nanobody complexes reveal how ACE2-binding is blocked and also explain the nanobodies' tolerance to immune escape mutations. Through the cryo-EM structure of the Ma16B06-BA.1 Spike complex, we demonstrated how a single nanobody molecule can neutralize a trimeric spike. We also describe a method for large-scale production of these nanobodies in Pichia pastoris, and for formulating them into aerosols. Exposing hamsters to these aerosols, before or even 24 h after infection with SARS-CoV-2, significantly reduced virus load, weight loss and pathogenicity. These results show the potential of aerosolized nanobodies for prophylaxis and therapy of coronavirus infections.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

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.

Rapid Estimation of Size-Based Heterogeneity in Monoclonal Antibodies by Machine Learning-Enhanced Dynamic Light Scattering

Aggregation of monoclonal antibody therapeutics is a serious concern that is believed to impact product safety and efficacy. There is a need for analytical approaches that enable rapid estimation of mAb aggregates. Dynamic light scattering (DLS) is a well-established technique for estimating the average size of protein aggregates or for evaluating sample stability. It is usually used to measure the size and size distribution over a wide range of nano- to micro-sized particles using time-dependent fluctuations in the intensity of scattered light arising from the Brownian motion of particles. In this study, we present a novel DLS-based approach that allows us to quantify the relative percentage of multimers (monomer, dimer, trimer, and tetramer) in a monoclonal antibody (mAb) therapeutic product. The proposed approach uses a machine learning (ML) algorithm and regression to model the system and predict the amount of relevant species such as monomer, dimer, trimer, and tetramer of a mAb in the size range of 10-100 nm. The proposed DLS-ML technique compares favorably to all potential alternatives with respect to the key method attributes, including per sample cost of analysis, per sample time of data acquisition along with ML-based aggregate prediction (<2 min), sample requirements (<3 μg), and user-friendliness of analysis. The proposed rapid method can serve as an orthogonal tool to size exclusion chromatography, which is the current industry workhorse for aggregate assessment.

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.

Enhanced protein aggregation suppressor activity of N-acetyl-l-arginine for agitation-induced aggregation with silicone oil and its impact on innate immune responses

Previously, N-acetyl-l-arginine (NALA) suppressed the aggregation of intravenous immunoglobulins (IVIG) more effectively and with a minimum decrease in transition temperature (T_m) than arginine monohydrochloride. In this study, we performed a comparative study with etanercept (commercial product: Enbrel®), where 25 mM arginine monohydrochloride (arginine) was added to the prefilled syringe. The biophysical properties were investigated using differential scanning calorimetry (DSC), dynamic light scattering (DLS), size-exclusion chromatography (SEC), and flow-imaging microscopy (FI). NALA retained the transition temperature of etanercept better than arginine, where arginine significantly reduced the T_m by increasing its concentration. End-over-end rotation was applied to each formulation for 5 days to accelerate protein aggregation and subvisible particle formation. Higher monomeric content was retained with NALA with a decrease in particle level. Higher aggregation onset temperature (T_agg) was detected for etanercept with NALA than arginine. The results of this comparative study were consistent with previous study, suggesting that NALA could be a better excipient for liquid protein formulations. Agitated IVIG and etanercept were injected into C57BL/6 J female mice to observe immunogenic response after 24 h. In the presence of silicone oil, NALA dramatically reduced IL-1 expression, implying that decreased aggregation was related to reduced immunogenicity of both etanercept and IVIG.

A Mechanistic Understanding of Monoclonal Antibody Interfacial Protection by Hydrolytically Degraded Polysorbate 20 and 80 under IV Bag Conditions

PURPOSE

Polysorbates (PS) contain polyoxyethylene (POE) sorbitan/isosorbide fatty acid esters that can partially hydrolyze over time in liquid drug products to generate degradants and a remaining intact PS fraction with a modified ester distribution. The degradants are composed of free fatty acids (FFAs) --primarily lauric acid for PS20 and oleic acid for PS80-- and POE head groups. We previously demonstrated that under IV bag agitation conditions, mAb1 (a surface-active IgG4) aggregation increased with increasing amounts of degradants for PS20 but not for PS80. The purpose of this work is to understand the mechanism behind this observation.

METHODS

The surface tension of the remaining intact PS fraction without degradants was modeled and compared with that of enzymatically degraded PS solutions. Next, mAb1 aggregation in saline was measured in the presence of laurate and oleate salts during static storage. Lastly, colloidal and conformational stability of mAb1 in the presence of these salts was investigated through differential scanning fluorimetry and dynamic light scattering under IV bag solution conditions.

RESULTS

The surface tension was primarily influenced by FFAs rather than the modified ester distribution of the remaining intact PS. MAb1 bulk aggregation increased in the presence of laurate but not oleate salts. Both salt types increased the melting temperature of mAb1 indicating FFA-mAb1 interactions. However, only laurate salt increased mAb1 self-association potentially explaining the higher aggregation propensity in its presence.

CONCLUSION

Our results help explain the observed differences between hydrolytically degraded PS20 and PS80 in affecting mAb1 aggregation under IV bag agitation conditions.

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

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

Fcγ Receptor-Dependent Internalization and Off-Target Cytotoxicity of Antibody-Drug Conjugate Aggregates

Purpose

Antibody-drug conjugates (ADCs), which are monoclonal antibodies (mAbs) conjugated with highly toxic payloads, achieve high tumor killing efficacy due to the specific delivery of payloads in accordance with mAbs’ function. On the other hand, the conjugation of payloads often increases the hydrophobicity of mAbs, resulting in reduced stability and increased aggregation. It is considered that mAb aggregates have potential risk for activating Fcγ receptors (FcγRs) on immune cells, and are internalized into cells via FcγRs. Based on the mechanism of action of ADCs, the internalization of ADCs into target-negative cells may cause the off-target toxicity. However, the impacts of aggregation on the safety of ADCs including off-target cytotoxicity have been unclear. In this study, we investigated the cytotoxicity of ADC aggregates in target-negative cells.

Methods

The ADC aggregates were generated by stirring stress or thermal stress. The off-target cytotoxicity of ADC aggregates was evaluated in several target-negative cell lines, and FcγR-activation properties of ADC aggregates were characterized using a reporter cell assay.

Results

Aggregation of ADCs enhanced the off-target cytotoxicity in several target-negative cell lines compared with non-stressed ADCs. Notably, ADC aggregates with FcγR-activation properties showed dramatically enhanced cytotoxicity in FcγR-expressing cells. The FcγR-mediated off-target cytotoxicity of ADC aggregates was reduced by using a FcγR-blocking antibody or Fc-engineering for silencing Fc-mediated effector functions.

Conclusions

These results indicated that FcγRs play an important role for internalization of ADC aggregates into non-target cells, and the aggregation of ADCs increases the potential risk for off-target toxicity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03158-x.

Expanding the toolbox for predictive parameters describing antibody stability considering thermodynamic and kinetic determinants

PURPOSE

Introduction of the activation energy (E_a) as a kinetic parameter to describe and discriminate monoclonal antibody (mAb) stability.

METHODS

E_a is derived from intrinsic fluorescence (IF) unfolding thermograms. An apparent irreversible three-state fit model based on the Arrhenius integral is developed to determine E_a of respective unfolding transitions. These activation energies are compared to the thermodynamic parameter of van´t Hoff enthalpies (∆H_vh). Using a set of 34 mAbs formulated in four different formulations, both the apparent thermodynamic and kinetic parameters together with apparent melting temperatures are correlated collectively with each other to storage stabilities to evaluate its predictive power with respect to long-term effects potentially reflected in shelf-life.

RESULTS

E_a allows for the discrimination of (i) different parent mAbs, (ii) different variants that originate from parent mAbs, and (iii) different formulations. Interestingly, we observed that the E_a of the CH₂ unfolding transition shows strongest correlations with monomer and aggregate content after storage at accelerated and stress conditions when collectively compared to ∆H_vh and T_m of the CH₂ transition. Moreover, the predictive parameters determined for the CH₂ domain show generally stronger correlations with monomer and aggregate content than those derived for the Fab. Qualitative assessment by ranking E_a of the Fab domain showed good agreement with monomer content in storage stabilities of individual mAb sub-sets.

CONCLUSION

E_a from IF unfolding transitions can be used in addition to other commonly used thermodynamic predictive parameters to discriminate and characterize thermal stability of different mAbs in different formulations. Hence, it shows great potential for antibody engineering and formulation scientists.

Boosting the kinetic efficiency of formate dehydrogenase by combining the effects of temperature, high pressure and co-solvent mixtures

The application of co-solvents and high pressure has been shown to be an efficient means to modify the kinetics of enzyme-catalyzed reactions without compromising enzyme stability, which is often limited by temperature modulation. In this work, the high-pressure stopped-flow methodology was applied in conjunction with fast UV/Vis detection to investigate kinetic parameters of formate dehydrogenase reaction (FDH), which is used in biotechnology for cofactor recycling systems. Complementary FTIR spectroscopic and differential scanning fluorimetric studies were performed to reveal pressure and temperature effects on the structure and stability of the FDH. In neat buffer solution, the kinetic efficiency increases by one order of magnitude by increasing the temperature from 25° to 45 °C and the pressure from ambient up to the kbar range. The addition of particular co-solvents further doubled the kinetic efficiency of the reaction, in particular the compatible osmolyte trimethylamine-N-oxide and its mixtures with the macromolecular crowding agent dextran. The thermodynamic model PC-SAFT was successfully applied within a simplified activity-based Michaelis-Menten framework to predict the effects of co-solvents on the kinetic efficiency by accounting for interactions involving substrate, co-solvent, water, and FDH. Especially mixtures of the co-solvents at high concentrations were beneficial for the kinetic efficiency and for the unfolding temperature.

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.

Neutralization of SARS-CoV-2 by highly potent, hyperthermostable, and mutation-tolerant nanobodies

Monoclonal anti-SARS-CoV-2 immunoglobulins represent a treatment option for COVID-19. However, their production in mammalian cells is not scalable to meet the global demand. Single-domain (VHH) antibodies (also called nanobodies) provide an alternative suitable for microbial production. Using alpaca immune libraries against the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein, we isolated 45 infection-blocking VHH antibodies. These include nanobodies that can withstand 95°C. The most effective VHH antibody neutralizes SARS-CoV-2 at 17-50 pM concentration (0.2-0.7 µg per liter), binds the open and closed states of the Spike, and shows a tight RBD interaction in the X-ray and cryo-EM structures. The best VHH trimers neutralize even at 40 ng per liter. We constructed nanobody tandems and identified nanobody monomers that tolerate the K417N/T, E484K, N501Y, and L452R immune-escape mutations found in the Alpha, Beta, Gamma, Epsilon, Iota, and Delta/Kappa lineages. We also demonstrate neutralization of the Beta strain at low-picomolar VHH concentrations. We further discovered VHH antibodies that enforce native folding of the RBD in the E. coli cytosol, where its folding normally fails. Such "fold-promoting" nanobodies may allow for simplified production of vaccines and their adaptation to viral escape-mutations.

Fundamentals to function: Quantitative and scalable approaches for measuring protein stability

Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.

Application of ultraviolet, visible, and infrared light imaging in protein-based biopharmaceutical formulation characterization and development studies

Imaging is increasingly more utilized as analytical technology in biopharmaceutical formulation research, with applications ranging from subvisible particle characterization to thermal stability screening and residual moisture analysis. This review offers a comprehensive overview of analytical imaging for scientists active in biopharmaceutical formulation research and development, where it presents the unique information provided by the ultraviolet (UV), visible (Vis), and infrared (IR) sections in the electromagnetic spectrum. The main body of this review consists of an outline of UV, Vis, and IR imaging techniques for several (bio)physical properties that are commonly determined during protein-based biopharmaceutical formulation characterization and development studies. The review concludes with a future perspective of applied imaging within the field of biopharmaceutical formulation research.

Pragmatic mAb lead molecule engineering from a developability perspective

As the number of antibody drugs being approved and marketed increases, our knowledge of what makes potential drug candidates a successful product has increased tremendously. One of the critical parameters that have become clear in the field is the importance of mAb "developability." Efforts are being increasingly focused on simultaneously selecting molecules that exhibit both desirable biological potencies and manufacturability attributes. In the current study mutations to improve the developability profile of a problematic antibody that inconsistently precipitates in a batch scale-dependent fashion using a standard platform purification process are described. Initial bioinformatic analysis showed the molecule has no obvious sequence or structural liabilities that might lead it to precipitate. Subsequent analysis of the molecule revealed the presence of two unusual positively charged mutations on the light chain at the interface of VH and VL domains, which were hypothesized to be the primary contributor to molecule precipitation during process development. To investigate this hypothesis, straightforward reversion to the germline of these residues was carried out. The resulting mutants have improved expression titers and recovered stability within a forced precipitation assay, without any change to biological activity. Given the time pressures of drug development in industry, process optimization of the lead molecule was carried out in parallel to the "retrospective" mutagenesis approach. Bespoke process optimization for large-scale manufacturing was successful. However, we propose that such context-dependent sequence liabilities should be included in the arsenal of in silico developability screening early in development; particularly since this specific issue can be efficiently mitigated without the requirement for extensive screening of lead molecule variants.

Machine learning reveals hidden stability code in protein native fluorescence

Conformational stability of a protein is usually obtained by spectroscopically measuring the unfolding melting temperature. However, optical spectra under native conditions are considered to contain too little resolution to probe protein stability. Here, we have built and trained a neural network model to take the temperature-dependence of intrinsic fluorescence emission under native-only conditions as inputs, and then predict the spectra at the unfolding transition and denatured state. Application to a therapeutic antibody fragment demonstrates that thermal transitions obtained from the predicted spectra correlate highly with those measured experimentally. Crucially, this work reveals that the temperature-dependence of native fluorescence spectra contains a high-degree of previously hidden information relating native ensemble features to stability. This could lead to rapid screening of therapeutic protein variants and formulations based on spectroscopic measurements under non-denaturing temperatures only.

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

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

Protein formulation through automated screening of pH and buffer conditions, using the Robotein® high throughput facility

Among various factors, the direct environment (e.g. pH, buffer components, salts, additives, etc.…) is known to have a crucial effect on both the stability and activity of proteins. In particular, proper buffer and pH conditions can improve their stability and function significantly during purification, storage and handling, which is highly relevant for both academic and industrial applications. It can also promote data reproducibility, support the interpretation of experimental results and, finally, contribute to our general understanding of the biophysical properties of proteins. In this study, we have developed a high throughput screen of 158 different buffers/pH conditions in which we evaluated: (i) the protein stability, using differential scanning fluorimetry and (ii) the protein function, using either enzymatic assays or binding activity measurements, both in an automated manner. The modular setup of the screen allows for easy implementation of other characterization methods and parameters, as well as additional test conditions. The buffer/pH screen was validated with five different proteins used as models, i.e. two active-site serine β-lactamases, two metallo-β-lactamases (one of which is only active as a tetramer) and a single-domain dromedary antibody fragment (V_HH or nanobody). The formulation screen allowed automated and fast determination of optimum buffer and pH profiles for the tested proteins. Besides the determination of the optimum buffer and pH, the collection of pH profiles of many different proteins may also allow to delineate general concepts to understand and predict the relationship between pH and protein properties.

Structural and functional comparison of SARS-CoV-2-spike receptor binding domain produced in Pichia pastoris and mammalian cells

The yeast Pichia pastoris is a cost-effective and easily scalable system for recombinant protein production. In this work we compared the conformation of the receptor binding domain (RBD) from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Spike protein expressed in P. pastoris and in the well established HEK-293T mammalian cell system. RBD obtained from both yeast and mammalian cells was properly folded, as indicated by UV-absorption, circular dichroism and tryptophan fluorescence. They also had similar stability, as indicated by temperature-induced unfolding (observed Tm were 50 °C and 52 °C for RBD produced in P. pastoris and HEK-293T cells, respectively). Moreover, the stability of both variants was similarly reduced when the ionic strength was increased, in agreement with a computational analysis predicting that a set of ionic interactions may stabilize RBD structure. Further characterization by high-performance liquid chromatography, size-exclusion chromatography and mass spectrometry revealed a higher heterogeneity of RBD expressed in P. pastoris relative to that produced in HEK-293T cells, which disappeared after enzymatic removal of glycans. The production of RBD in P. pastoris was scaled-up in a bioreactor, with yields above 45 mg/L of 90% pure protein, thus potentially allowing large scale immunizations to produce neutralizing antibodies, as well as the large scale production of serological tests for SARS-CoV-2.

Advancements in the co-formulation of biologic therapeutics

Biologic therapeutics are the medicines of the future and are destined to transform the approaches by which the causes and symptoms of diseases are cured and alleviated. These approaches will be accelerated through the development of novel strategies that target multiple pharmacologically active sites using a combination of different biologics, or mixtures of biologics and small molecule therapeutics. However, for this potential to be realised, advancements in co-formulation strategies for biologic therapeutics must be established. This review describes the current and emerging developments within this field and highlights the challenges and potential solutions, that will pave-the-way towards their clinical translation.

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.

Contribution of Intrinsic Fluorescence to the Design of a New 3D-Printed Implant for Releasing SDABS

Single-domain antibodies (sdAbs) offer great features such as increased stability but are hampered by a limited serum half-life. Many strategies have been developed to improve the sdAb half-life, such as protein engineering and controlled release systems (CRS). In our study, we designed a new product that combined a hydrogel with a 3D-printed implant. The results demonstrate the implant’s ability to sustain sdAb release up to 13 days through a reduced initial burst release followed by a continuous release. Furthermore, formulation screening helped to identify the best sdAb formulation conditions and improved our understanding of our CRS. Through the screening step, we gained knowledge about the influence of the choice of polymer and about potential interactions between the sdAb and the polymer. To conclude, this feasibility study confirmed the ability of our CRS to extend sdAb release and established the fundamental role of formulation screening for maximizing knowledge about our CRS.

High Performance Size Exclusion Chromatography and High-Throughput Dynamic Light Scattering as Orthogonal Methods to Screen for Aggregation and Stability of Monoclonal Antibody Drug Products

The presence of aggregates in monoclonal antibody (mAb) drug product (DP) formulations can present product quality challenges. Here we show that use of High Performance Size Exclusion Chromatography (HP-SEC), in conjunction with high-throughput dynamic light scattering (HT-DLS) analyses of mAb DPs can be a useful strategy to determine monomer content and the presence of aggregates under simulated stress conditions. This analytical approach was used to evaluate four commercially available mAb DPs under different conditions i.e.; original formulations, diluted, and thermo-mechanical stressed condition. Due to particle size limitations of HP-SEC columns, resulting in particles accumulating in the column frits prior to reaching the detector for analysis, there is a possibility that large mAb aggregates may not be detected. Both HP-SEC and HT-DLS were able to detect and resolve the mAb monomer (~10-12 nm) of the DPs in their recommended storage conditions. However, the ability to detect large aggregates (>40 nm) by both analytical methods differed, and HT-DLS was able to detect aggregates between 60 nm and 1400 nm under stress conditions. Our data indicates that HP-SEC, in conjunction with HT-DLS, may be beneficial to detect both mAb DP monomer content and multiple aggregate species (1-1000 nm) in the submicron size range.

Effect of Linker-Drug Properties and Conjugation Site on the Physical Stability of ADCs

The physical stability of antibody drug conjugates is dictated by the properties of the antibody, linker-drug, and conjugation site. Two linker-drugs were chosen that are different in terms of hydrophobicity and polar surface area to evaluate the effect of linker-drug properties on antibody-drug conjugate (ADC) behavior. Site-specific and non-site-specific conjugation was used to investigate the role of conjugation site in conformational and colloidal stability. Finally, 2 antibodies were selected to determine if the observed results were antibody-specific. The conformational stability is affected, with the highest degree of destabilization observed when conjugation results in the removal of interchain disulfide bonds. Although conformational destabilization occurred in the domain in which conjugation occurred and domains distinct from the conjugation site, no correlation could be drawn between linker-drug properties and conformational stability. Evaluation of aggregation by size exclusion HPLC confirmed a relationship between linker-drug hydrophobicity and aggregation propensity under thermal stress in all ADCs tested. The extent of aggregation was far greater in the conjugates generated with a more hydrophobic antibody, illustrating that the properties of both the antibody and linker-drug contribute to aggregation. These studies emphasize that the distinct properties of the molecule as a whole warrant a case-by-case evaluation of each ADC.

Nano differential scanning fluorimetry for comparability studies of therapeutic proteins

Differential scanning calorimetry (DSC) has been extensively used in the biopharmaceutical industry to characterize protein thermal stability and domain folding integrity. Recently, nano differential scanning fluorimetry (nanoDSF) has emerged as a powerful tool for thermal stability analysis and studies of protein domain unfolding. Due to increased interests in the qualification of characterization methods, we are in this study presenting the qualification results for the comparability studies of thermal stability analysis using nanoDSF. The results show that nanoDSF is able to detect thermal transition signals for mAbs, BiTE® molecules, and cytokines at a wide concentration range with high precision, clearly indicating that nanoDSF is suitable for characterization including comparability studies of therapeutic proteins. Compared to the current recognized industry standard DSC, the nanoDSF method enables thermal stability analysis over a much wider concentration range, consumes considerably less materials, and provides significantly higher throughput.

Germinality does not necessarily define mAb expression and thermal stability

The production potential of recombinant monoclonal antibody (mAb) expressing cell lines depends, among other factors, on the intrinsic antibody structure determined by the amino acid sequence. In this study, we investigated the influence of somatic mutations in the V(D)J sequence of four individual, mature model mAbs on the expression potential. Therefore, we defined four couples, each consisting of one naturally occurring mAb (2G12, Ustekinumab, 4B3, and 2F5) and the corresponding germline-derived cognate mAb (353/11, 554/12, 136/63, and 236/14). For all eight mAb variants, recombinant Chinese hamster ovary (CHO) cell lines were developed with mAbs expressed from a defined chromosomal locus. The presented workflow investigates critical parameters including productivity, intra- and extracellular product profile, XBP1 splicing, thermal stability, and in silico hydrophobicity. Significant differences in productivity were even observed between the germline-derived mAbs which did not undergo somatic mutagenesis. Accordingly, back-to-germline mutations of mature mAbs are not necessarily reflecting improved expression and stability but indicate opportunities and limits of mAb engineering. From our studies, we conclude that germinalization represents a potential to improve mAb properties depending on the antibody’s germline family, highlighting the fact that mAbs should be treated individually.

Novel non-linear curve fitting to resolve protein unfolding transitions in intrinsic fluorescence differential scanning fluorimetry

In biotherapeutic protein research, an estimation of the studied protein's thermal stability is one of the important steps that determine developability as a function of solvent conditions. Differential Scanning Fluorimetry (DSF) can be applied to measure thermal stability. Label-free DSF measures amino acid fluorescence as a function of temperature, where conformational changes induce observable peak deformation, yielding apparent melting temperatures. The estimation of the stability parameters can be hindered in the case of multidomain, multimeric or aggregating proteins when multiple transitions partially coincide. These overlapping protein unfolding transitions are hard to evaluate by the conventional methodology, as peak maxima are shifted by convolution. We show how non-linear curve fitting of intrinsic fluorescence DSF can deconvolute highly overlapping transitions in formulation screening in a semi-automated process. The proposed methodology relies on synchronous, constrained fits of the fluorescence intensity, ratio and their derivatives, by combining linear baselines with generalized logistic transition functions. The proposed algorithm is applied to data from three proteins; a single transition, a double separated transition and a double overlapping transition. Extracted thermal stability parameters; apparent melting temperatures T_m,1, T_m,2 and melting onset temperature T_onset are obtained and compared with reference software analysis. The fits show R² = 0.94 for single and R² = 0.88 for separated transitions. Obtaining values and trends for T_onset in a well-described and automated way, will aid protein scientist to better evaluate the thermal stability of proteins.

Conjugation of Emtansine Onto Trastuzumab Promotes Aggregation of the Antibody-Drug Conjugate by Reducing Repulsive Electrostatic Interactions and Increasing Hydrophobic Interactions

The impact of drug conjugation on intra- and intermolecular interactions of trastuzumab (TmAb) was determined by comparing the conformational and colloidal stabilities of TmAb and trastuzumab emtansine (T-DM1). In low ionic strength formulations, drug conjugation to native lysine residues of TmAb significantly reduced the repulsive electrostatic interactions between T-DM1 molecules. When these electrostatic interactions were screened in solutions with high ionic strength, intermolecular interactions between T-DM1 molecules were found to be more attractive than those between TmAb molecules. Drug conjugation lowered the colloidal stability of T-DM1 compared to TmAb, making T-DM1 more susceptible to agitation-induced aggregation. The presence of polysorbate-20 in the formulations inhibited aggregation of TmAb and T-DM1 induced by the hydrophobic air-water interface. Furthermore, the effect of increased hydrophobic interactions between T-DM1 molecules was studied by monitoring aggregation in TmAb and T-DM1 solutions that were incubated at 4°C, 25°C, and 50°C. Conjugating DM1 to TmAb increased the hydrophobicity of the molecule, and faster aggregation of T-DM1 at 50°C could be attributed to a temperature-dependent increase in hydrophobic interactions between T-DM1 molecules.

An Evaluation of the Potential of NMR Spectroscopy and Computational Modelling Methods to Inform Biopharmaceutical Formulations

Protein-based therapeutics are considered to be one of the most important classes of pharmaceuticals on the market. The growing need to prolong stability of high protein concentrations in liquid form has proven to be challenging. Therefore, significant effort is being made to design formulations which can enable the storage of these highly concentrated protein therapies for up to 2 years. Currently, the excipient selection approach involves empirical high-throughput screening, but does not reveal details on aggregation mechanisms or the molecular-level effects of the formulations under storage conditions. Computational modelling approaches have the potential to elucidate such mechanisms, and rapidly screen in silico prior to experimental testing. Nuclear Magnetic Resonance (NMR) spectroscopy can also provide complementary insights into excipient–protein interactions. This review will highlight the underpinning principles of molecular modelling and NMR spectroscopy. It will also discuss the advancements in the applications of computational and NMR approaches in investigating excipient–protein interactions.