Rapid sample-saving biophysical characterisation and long-term storage stability of liquid interferon alpha2a formulations: Is there a correlation?

Nano Differential Scanning Fluorimetry as a Rapid Stability Assessment Tool in the Nanoformulation of Proteins

The development and production of innovative protein-based therapeutics is a complex and challenging avenue. External conditions such as buffers, solvents, pH, salts, polymers, surfactants, and nanoparticles may affect the stability and integrity of proteins during formulation. In this study, poly (ethylene imine) (PEI) functionalized mesoporous silica nanoparticles (MSNs) were used as a carrier for the model protein bovine serum albumin (BSA). To protect the protein inside MSNs after loading, polymeric encapsulation with poly (sodium 4-styrenesulfonate) (NaPSS) was used to seal the pores. Nano differential scanning fluorimetry (NanoDSF) was used to assess protein thermal stability during the formulation process. The MSN-PEI carrier matrix or conditions used did not destabilize the protein during loading, but the coating polymer NaPSS was incompatible with the NanoDSF technique due to autofluorescence. Thus, another pH-responsive polymer, spermine-modified acetylated dextran (SpAcDEX), was applied as a second coating after NaPSS. It possessed low autofluorescence and was successfully evaluated with the NanoDSF method. Circular dichroism (CD) spectroscopy was used to determine protein integrity in the case of interfering polymers such as NaPSS. Despite this limitation, NanoDSF was found to be a feasible and rapid tool to monitor protein stability during all steps needed to create a viable nanocarrier system for protein delivery.

Insights into the Stabilization of Interferon Alpha by Two Surfactants Revealed by STD-NMR Spectroscopy

Surfactants are commonly used in biopharmaceutical formulations to stabilize proteins against aggregation. However, the choice of a suitable surfactant for a particular protein is decided mostly empirically, and their mechanism of action on molecular level is largely unknown. Here we show that a straightforward label-free method, saturation transfer difference (STD) nuclear magnetic resonance (NMR) spectroscopy, can be used to detect protein-surfactant interactions in formulations of a model protein, interferon alpha. We find that polysorbate 20 binds with its fatty acid to interferon, and that the binding is stronger at pH closer to the isoelectric point of the protein. In contrast, we did not detect interactions between poloxamer 407 and interferon alpha. Neither of the two surfactants affected the tertiary structure and the thermal stability of the protein as evident from circular dichroism and nanoDSF measurements. Interestingly, both surfactants inhibited the formation of subvisible particles during long-term storage, but only polysorbate 20 reduced the amount of small soluble aggregates detected by size-exclusion chromatography. This proof-of-principle study demonstrates how STD-NMR can be employed to quickly assess surfactant-protein interactions and support the choice of surfactant in protein formulation.

Electrostatics Drive Oligomerization and Aggregation of Human Interferon Alpha-2a

Aggregation is a common phenomenon in the field of protein therapeutics and can lead to function loss or immunogenic patient responses. Two strategies are currently used to reduce aggregation: (1) finding a suitable formulation, which is labor-intensive and requires large protein quantities, or (2) engineering the protein, which requires extensive knowledge about the protein aggregation pathway. We present a biophysical characterization of the oligomerization and aggregation processes by Interferon alpha-2a (IFNα-2a), a protein drug with antiviral and immunomodulatory properties. This study combines experimental high throughput screening with detailed investigations by small-angle X-ray scattering and analytical ultracentrifugation. Metropolis Monte Carlo simulations are used to gain insight into the underlying intermolecular interactions. IFNα-2a forms soluble oligomers that are controlled by a fast pH and concentration-dependent equilibrium. Close to the isoelectric point of 6, IFNα-2a forms insoluble aggregates which can be prevented by adding salt. We show that monomer attraction is driven mainly by molecular anisotropic dipole–dipole interactions that increase with increasing pH. Repulsion is due to monopole–monopole interactions and depends on the charge of IFNα-2a. The study highlights how combining multiple methods helps to systematically dissect the molecular mechanisms driving oligomer formation and to design ultimately efficient strategies for preventing detrimental protein aggregation.

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.

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).

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.

Biophysical Characterization of Binary Therapeutic Monoclonal Antibody Mixtures

Coformulations containing two therapeutic monoclonal antibodies (mAbs) could offer various benefits like enhanced therapeutic efficacy and better patient compliance. However, there are very few published studies on coformulations and binary mixtures of mAbs. It remains unclear to what extent mAbs with different physicochemical properties can be combined in solution without detrimental effects on protein stability. Here, we present a study including six model mAbs of the IgG1 subclass that are commercially available. In silico and biophysical characterization shows that the proteins have different physicochemical properties. Thus, their combinations represent various scenarios for coformulation development. We prepared all possible binary mixtures of the six mAbs and determined several biophysical parameters that are assessed during early-stage protein drug product development. The measured biophysical parameters are indicative of the conformational protein stability (inflection points of the thermal protein unfolding transitions) and the colloidal protein stability (aggregation onset temperatures and interaction parameter k_D from dynamic light scattering). Remarkably, all 15 binary mAb mixtures do not exhibit biophysical parameters that indicate inferior conformational or colloidal stability compared to the least stable mAb in the mixture. Our findings suggest that the coformulation of some therapeutic monoclonal antibodies of the IgG1 subclass could be possible in a straightforward way as severe detrimental effects on the stability of these proteins in binary mixtures were not observed.

Binding of excipients is a poor predictor for aggregation kinetics of biopharmaceutical proteins

One of the major challenges in formulation development of biopharmaceuticals is improving long-term storage stability, which is often achieved by addition of excipients to the final formulation. Finding the optimal excipient for a given protein is usually done using a trial-and-error approach, due to the lack of general understanding of how excipients work for a particular protein. Previously, preferential interactions (binding or exclusion) of excipients with proteins were postulated as a mechanism explaining diversity in the stabilisation effects. Weak preferential binding is however difficult to quantify experimentally, and the question remains whether the formulation process should seek excipients which preferentially bind with proteins, or not. Here, we apply solution NMR spectroscopy to comprehensively evaluate protein-excipient interactions between therapeutically relevant proteins and commonly used excipients. Additionally, we evaluate the effect of excipients on thermal and colloidal protein stability, on aggregation kinetics and protein storage stability at elevated temperatures. We show that there is a weak negative correlation between the strength of protein-excipient interactions and effect on enhancing protein thermal stability. We found that the overall protein-excipient binding per se can be a poor criterion for choosing excipients enhancing formulation stability. Experiments on a diverse set of excipients and test proteins reveal that while excipients affect all of the different aspects of protein stability, the effects are very much protein specific, and care must be taken to avoid apparent generalisations if a smaller dataset is being used.

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

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

Advancing Therapeutic Protein Discovery and Development through Comprehensive Computational and Biophysical Characterization

Therapeutic protein candidates should exhibit favorable properties that render them suitable to become drugs. Nevertheless, there are no well-established guidelines for the efficient selection of proteinaceous molecules with desired features during early stage development. Such guidelines can emerge only from a large body of published research that employs orthogonal techniques to characterize therapeutic proteins in different formulations. In this work, we share a study on a diverse group of proteins, including their primary sequences, purity data, and computational and biophysical characterization at different pH and ionic strength. We report weak linear correlations between many of the biophysical parameters. We suggest that a stability comparison of diverse therapeutic protein candidates should be based on a computational and biophysical characterization in multiple formulation conditions, as the latter can largely determine whether a protein is above or below a certain stability threshold. We use the presented data set to calculate several stability risk scores obtained with an increasing level of analytical effort and show how they correlate with protein aggregation during storage. Our work highlights the importance of developing combined risk scores that can be used for early stage developability assessment. We suggest that such scores can have high prediction accuracy only when they are based on protein stability characterization in different solution conditions.

Coupling Multi-Angle Light Scattering to Reverse-Phase Ultra-High-Pressure Chromatography (RP-UPLC-MALS) for the characterization monoclonal antibodies

Multi-angle light scattering coupled with size-exclusion chromatography (SEC-MALS) is a standard approach for protein characterization. Recently MALS detection has been coupled with ion-exchange chromatography (IEX) which demonstrated the feasibility and high value of MALS in combination with non-sized-based fractionation methods. In this study we coupled reverse-phase ultra-high pressure liquid chromatography (RP-UPLC) with a low-dispersion MALS detector for the characterization of intact monoclonal antibody (mAbs) and their fragments. We confirmed a constant refractive index increment value for mAbs in RP gradients, in good agreement with the values in literature for other classes of proteins. We showed that the impurities eluting from a RP column can often be related to aggregated species and we confirmed that in most cases those oligomers are present also in SEC-MALS. Yet, in few cases small aggregates fractions in RP-UPLC are an artifact. In fact, proteins presenting thermal and physical stability not suitable for the harsh condition applied during the RP separation of mAbs (i.e. organic solvents at high temperature) can aggregate. Further, we applied RP-UPLC-MALS during a long term stability studies. The different principle of separation used in RP-UPLC- MALS provides an additional critical level of protein characterization compared to SEC-MALS and IEX-MALS.

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.