Concentration-dependent changes in apparent diffusion coefficients as indicator for colloidal stability of protein solutions

Nonlinear model of infection wavy oscillation of COVID-19 in Japan based on diffusion kinetics

The infectious propagation of SARS-CoV-2 is continuing worldwide, and specifically, Japan is facing severe circumstances. Medical resource maintenance and action limitations remain the central measures. An analysis of long-term follow-up reports in Japan shows that the infection number follows a unique wavy oscillation, increasing and decreasing over time. However, only a few studies explain the infection wavy oscillation. This study introduces a novel nonlinear mathematical model of the new infection wavy oscillation by applying the macromolecule diffusion theory. In this model, the diffusion coefficient that depends on population density gives nonlinearity in infection propagation. As a result, our model accurately simulated infection wavy oscillations, and the infection wavy oscillation frequency and amplitude were closely linked with the recovery rate of infected individuals. In conclusion, our model provides a novel nonlinear contact infection analysis framework.

Protein-protein interactions at high concentrations: Effects of ArgHCl and NaCl on the stability, viscosity and aggregation mechanisms of protein solution

The aim of this work was to use the diffusion coefficient ration (D_m/D_line) as a parameter to characterize the stability of protein at high concentration, to compare the effects of ArgHCl and NaCl on the interaction of highly concentrated proteins under different pH conditions, and to explore the correlation with protein stability. For this purpose, a high-concentration bovine serum albumin solution (BSA) was selected as the model system, and the diffusion coefficient, aggregation degree, conformational stability, and solution viscosity of the protein were studied by dynamic light scattering (DLS) and spectral detection techniques. The result showed that there was a significant correlation between the D_m/D_line and the protein aggregation. The D_m/D_line of the protein was minimum at pH 7.4, which corresponded to the maximum degree of aggregation and the highest solution viscosity. At pH 7.4, the hydrophobic interactions and the increased conformational stability of ArgHCl maximized the stability of the protein and reduced the viscosity of the solution by 69.3%. At pH 3.0, the strong charge shielding effect of ArgHCl and NaCl and the decreased conformational stability induced protein aggregation and the gel formation. These findings provided valuable insights into the mechanism of protein aggregation and the diffusion coefficient ration (D_m/D_line) could be a potential tool for the pre-formulation studies.

Evaluation of biological activities, structural and conformational properties of bovine beta- and alpha-trypsin isoforms in aqueous-organic media

The study of the biological activity of trypsin isoforms in aqueous-organic media is of great interest to various fields of knowledge and biochemistry applications. Thus enzymatic, structural, and energetic properties of bovine β- and α-trypsin isoforms were compared in aqueous-organic media using 30 mg of each isoform. The results showed that the changes induced on the structure and activity of the same trypsin isoform occur at different concentrations. Better results for activity (ionic strength of 0.11 mol·L^-1, at 37 °C and pH 8.0) were found in 0-40% of ethanolic media in which the activity for β-trypsin was about 60% higher than ɑ-trypsin. The ethanolic system does not cause significant changes in the level of secondary structure but the β-trypsin isoform undergoes a major rearrangement. The use of until 60% (v/v) ethanol showed that β-trypsin presents a denaturation process 17% more cooperative. The organic solvent causes redistribution in the supramolecular arrangement of both isoforms: all concentrations used induced the β-trypsin molecules to rearrange into agglomerates. The ɑ-trypsin rearranges into agglomerates up to 60% (v/v) of ethanol and aggregates at 80% (v/v) of ethanol. Both isoforms keep the enzymatic activity up to 60% (v/v) of ethanol.

Microwell Plate-Based Dynamic Light Scattering as a High-Throughput Characterization Tool in Biopharmaceutical Development

High-throughput light scattering instruments are widely used in screening of biopharmaceutical formulations and can be easily incorporated into processes by utilizing multi-well plate formats. High-throughput plate readers are helpful tools to assess the aggregation tendency and colloidal stability of biological drug candidates based on the diffusion self-interaction parameter (k_D). However, plate readers evoke issues about the precision and variability of determined data. In this article, we report about the statistical evaluation of intra- and inter-plate variability (384-well plates) for the k_D analysis of protein and peptide solutions. ANOVA revealed no significant differences between the runs. In conclusion, the reliability and precision of k_D was dependent on the plate position of the sample replicates and k_D value. Positive k_D values (57.0 mL/g, coefficients of variation (CV) 8.9%) showed a lower variability compared to negative k_D values (−14.8 mL/g, CV 13.4%). The variability of k_D was not reduced using more data points (120 vs. 30). A k_D analysis exclusively based on center wells showed a lower CV (<2%) compared to edge wells (5–12%) or a combination of edge and center wells (2–5%). We present plate designs for k_D analysis within the early formulation development, screening up to 20 formulations consuming less than 50 mg of active pharmaceutical ingredient (API).

Stability liabilities of biotherapeutic proteins: Early assessment as mitigation strategy

Identification of molecular liabilities and implementation of mitigation strategies are key aspects that need to be considered by pharmaceutical companies developing therapeutic proteins. In the field of monoclonal antibodies, an efficient and streamlined process known as developability assessment is used for the selection of the "fittest" candidate. Other protein modalities, have in most cases only a limited number of possible candidates, requiring a paradigm change to a concept of candidate enabling. The assessment of liabilities at early project phases with the possibility to re-engineer candidates becomes essential for the success of these projects. Each protein possesses a unique stability profile resulting from the interplay of conformational, colloidal, chemical and physical stability attributes. All of these attributes strongly depend on external factors. Conformational and colloidal stability profiles of three non-immunoglobulin domain based proteins, namely Carbonic anhydrase, Ovalbumin and Thyroglobulin, and of two monoclonal antibodies were assessed in dependence of solution pH, ionic strength and varying buffering agents. The impact of screened external factors on proteins' stability attributes varied significantly, indicating presence of molecule specific liabilities. Screening of such a broad space of conditions at early project phases is only feasible using low-material consuming, high-throughput analytical methods as exemplified in this study.

Apparent protein cloud point temperature determination using a low volume high-throughput cryogenic device in combination with automated imaging

Short-term parameters correlating to long-term protein stability, such as the protein cloud point temperature (T_cloud), are of interest to improve efficiency during protein product development. Such efficiency is reached if short-term parameters are obtained in a low volume and high-throughput (HT) manner. This study presents a low volume HT detection method for (sub-zero) T_cloud determination of lysozyme, as such an experimental method is not available yet. The setup consists of a cryogenic device with an automated imaging system. Measurement reproducibility (median absolute deviation of 0.2 °C) and literature-based parameter validation (Pearson correlation coefficient of 0.996) were shown by a robustness and validation study. The subsequent case study demonstrated a partial correlation between the obtained apparent T_cloud parameter and long-term protein stability as a function of lysozyme concentration, ion type, ionic strength, and freeze/thaw stress. The presented experimental setup demonstrates its ability to advance short-term strategies for efficient protein formulation development.

Improved Dynamic Light Scattering using an adaptive and statistically driven time resolved treatment of correlation data

Dynamic Light Scattering (DLS) is a ubiquitous and non-invasive measurement for the characterization of nano- and micro-scale particles in dispersion. The sixth power relationship between scattered intensity and particle radius is simultaneously a primary advantage whilst rendering the technique sensitive to unwanted size fractions from unclean lab-ware, dust and aggregated & dynamically aggregating sample, for example. This can make sample preparation iterative, challenging and time consuming and often requires the use of data filtering methods that leave an inaccurate estimate of the steady state size fraction and may provide no knowledge to the user of the presence of the transient fractions. A revolutionary new approach to DLS measurement and data analysis is presented whereby the statistical variance of a series of individually analysed, extremely short sub-measurements is used to classify data as steady-state or transient. Crucially, all sub-measurements are reported, and no data are rejected, providing a precise and accurate measurement of both the steady state and transient size fractions. We demonstrate that this approach deals intrinsically and seamlessly with the transition from a stable dispersion to the partially- and fully-aggregated cases and results in an attendant improvement in DLS precision due to the shorter sub measurement length and the classification process used.

Redesigning food protein formulations with empirical phase diagrams: A case study on glycerol-poor and glycerol-free formulations

Redesigning existing food protein formulations is necessary in situations where food authorities propose dose adjustments or removal of currently employed additives. Redesigning formulations involves evaluating substitute additives to obtain similar long-term physical stability as the original formulation. Such formulation screening experiments benefit from comprehensive data visualization, understanding the effects of substitute additives on long-term physical stability, and identification of short-term optimization targets. This work employs empirical phase diagrams to reach these benefits by combining multidimensional long-term protein physical stability data with short-term empirical protein properties. A case study was performed where multidimensional protein phase diagrams (1152 formulations) allowed for identification of stabilizing effects as a result of pH, methionine, sugars, salt, and minimized glycerol content. Corresponding empirical protein property diagrams (144 formulations) resulted in the identification of normalized surface tension as a short-term empirical protein property to reach long-term physical stability presumably similar to the original product, namely via preferential hydration. Additionally, changes in pH and salt were identified as environmental optimization targets to reach stability via repulsive electrostatic forces. This case study shows the applicability of the empirical phase diagram method to rationally perform formulation redesign screenings, while simultaneously expanding knowledge on protein long-term physical stability.

Science and art of protein formulation development

Protein pharmaceuticals have become a significant class of marketed drug products and are expected to grow steadily over the next decade. Development of a commercial protein product is, however, a rather complex process. A critical step in this process is formulation development, enabling the final product configuration. A number of challenges still exist in the formulation development process. This review is intended to discuss these challenges, to illustrate the basic formulation development processes, and to compare the options and strategies in practical formulation development.

Dynamics of proteins in solution

The dynamics of proteins in solution includes a variety of processes, such as backbone and side-chain fluctuations, interdomain motions, as well as global rotational and translational (i.e. center of mass) diffusion. Since protein dynamics is related to protein function and essential transport processes, a detailed mechanistic understanding and monitoring of protein dynamics in solution is highly desirable. The hierarchical character of protein dynamics requires experimental tools addressing a broad range of time- and length scales. We discuss how different techniques contribute to a comprehensive picture of protein dynamics, and focus in particular on results from neutron spectroscopy. We outline the underlying principles and review available instrumentation as well as related analysis frameworks.

The Investigation of Protein Diffusion via H-Cell Microfluidics

In this study, we developed a microfluidics method, using a so-called H-cell microfluidics device, for the determination of protein diffusion coefficients at different concentrations, pHs, ionic strengths, and solvent viscosities. Protein transfer takes place in the H-cell channels between two laminarly flowing streams with each containing a different initial protein concentration. The protein diffusion coefficients are calculated based on the measured protein mass transfer, the channel dimensions, and the contact time between the two streams. The diffusion rates of lysozyme, cytochrome c, myoglobin, ovalbumin, bovine serum albumin, and etanercept were investigated. The accuracy of the presented methodology was demonstrated by comparing the measured diffusion coefficients with literature values measured under similar solvent conditions using other techniques. At low pH and ionic strength, the measured lysozyme diffusion coefficient increased with the protein concentration gradient, suggesting stronger and more frequent intermolecular interactions. At comparable concentration gradients, the measured lysozyme diffusion coefficient decreased drastically as a function of increasing ionic strength (from zero onwards) and increasing medium viscosity. Additionally, a particle tracing numerical simulation was performed to achieve a better understanding of the macromolecular displacement in the H-cell microchannels. It was found that particle transfer between the two channels tends to speed up at low ionic strength and high concentration gradient. This confirms the corresponding experimental observation of protein diffusion measured via the H-cell microfluidics.

Correlating multidimensional short-term empirical protein properties to long-term protein physical stability data via empirical phase diagrams

Identification of long-term stable biopharmaceutical formulations is essential for biopharmaceutical product development. Reduction of the number of long-term storage experiments and a well-defined formulation search space requires knowledge-based formulation screenings and a detailed protein phase behavior understanding. To achieve this, short-term analytical techniques can serve as predictors for long-term protein phase behavior. Protein phase behavior studies that investigate this concept commonly display shortcomings such as limited and small datasets, sample adjustments, or simplistic data analysis. To overcome these shortcomings, 150 unique lysozyme solutions were analyzed using six different short-term analytical techniques. Lysozyme's structural properties, conformational stability, colloidal stability, surface charge, and surface hydrophobicity were obtained directly after formulation preparation. Employing the empirical phase diagram method, this short-term data was correlated to long-term physical stability data obtained during 40 days of storage. Short-term protein properties showed partial correlation to long-term phase behavior. Structural differences, changing surface properties, colloidal stability, and conformation stability as a function of formulation conditions were observed. This study contributes to long-term protein phase behavior research by presenting a systematic, data-dependent, and multidimensional data evaluation workflow to create a comprehensive overview of short-term protein analytics in relation to long-term protein phase behavior.

Application of Empirical Phase Diagrams for Multidimensional Data Visualization of High-Throughput Microbatch Crystallization Experiments

Protein phase diagrams are a tool to investigate the cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphologic features, such as crystal size, as well as kinetic features, such as crystal growth time. Commonly used data visualization techniques include individual line graphs or phase diagrams based on symbols. These techniques have limitations in terms of handling large data sets, comprehensiveness or completeness. To eliminate these limitations, morphologic and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram method. Morphologic features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength, and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the empirical phase diagram method can support high-throughput crystallization experiments in its data amount as well as its data complexity.

Characterization of highly concentrated antibody solution - A toolbox for the description of protein long-term solution stability

High protein titers are gaining importance in biopharmaceutical industry. A major challenge in the development of highly concentrated mAb solutions is their long-term stability and often incalculable viscosity. The complexity of the molecule itself, as well as the various molecular interactions, make it difficult to describe their solution behavior. To study the formulation stability, long- and short-range interactions and the formation of complex network structures have to be taken into account. For a better understanding of highly concentrated solutions, we combined established and novel analytical tools to characterize the effect of solution properties on the stability of highly concentrated mAb formulations. In this study, monoclonal antibody solutions in a concentration range of 50-200 mg/ml at pH 5-9 with and without glycine, PEG4000, and Na2SO4 were analyzed. To determine the monomer content, analytical size-exclusion chromatography runs were performed. ζ-potential measurements were conducted to analyze the electrophoretic properties in different solutions. The melting and aggregation temperatures were determined with the help of fluorescence and static light scattering measurements. Additionally, rheological measurements were conducted to study the solution viscosity and viscoelastic behavior of the mAb solutions. The so-determined analytical parameters were scored and merged in an analytical toolbox. The resulting scoring was then successfully correlated with long-term storage (40 d of incubation) experiments. Our results indicate that the sensitivity of complex rheological measurements, in combination with the applied techniques, allows reliable statements to be made with respect to the effect of solution properties, such as protein concentration, ionic strength, and pH shift, on the strength of protein-protein interaction and solution colloidal stability.