Control of viscosity in biopharmaceutical protein formulations

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

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

Ultrasonic Sensor: A Fast and Non-Destructive System to Measure the Viscosity and Density of Molecular Fluids

This study presents the design and development of an ultrasonic sensor as a fundamental tool for characterizing the properties of fluids and biofluids. The analysis primarily focuses on measuring the electrical parameters of the system, which correlate with the density and viscosity of the solutions, in sample volumes of microliters and with high temporal resolution (up to 1 data point per second). The use of this sensor allows the fast and non-destructive evaluation of the viscosity and density of fluids deposited on its free surface. The measurements are based on obtaining the impedance versus frequency curve and the phase difference curve (between current and voltage) versus frequency. In this way, characteristic parameters of the transducer, such as the resonance frequency, phase, minimum impedance, and the quality factor of the resonant system, can characterize variations in density and viscosity in the fluid under study. The results obtained revealed the sensor's ability to identify two parameters sensitive to viscosity and two parameters sensitive to density. As a proof of concept, the unfolding of the bovine albumin protein was studied, resulting in a curve that reflects its unfolding kinetics in the presence of urea.

The search for novel proline analogs for viscosity reduction and stabilization of highly concentrated monoclonal antibody solutions

Administration of monoclonal antibodies (mAbs) is currently focused on subcutaneous injection associated with increased patient adherence and reduced treatment cost, leading to sustainable healthcare. The main bottleneck is low volume that can be injected, requiring highly concentrated mAb solutions. The latter results in increased solution viscosity with pronounced mAb aggregation propensity because of intensive protein-protein interactions. Small molecule excipients have been proposed to restrict the protein-protein interactions, contributing to reduced viscosity. The aim of the study was to discover novel compounds that reduce the viscosity of highly concentrated mAb solution. First, the chemical space of proline analogs was explored and 35 compounds were determined. Viscosity measurements revealed that 18 proline analogs reduced the mAb solution viscosity similar to or more than proline. The compounds forming both electrostatic and hydrophobic interactions with mAb reduced the viscosity of the formulation more efficiently without detrimentally effecting mAb physical stability. A correlation between the level of interaction and viscosity-reducing effect was confirmed with molecular dynamic simulations. Structure rigidity of the compounds and aromaticity contributed to their viscosity-reducing effect, dependent on molecule size. The study results highlight the novel proline analogs as an effective approach in viscosity reduction in development of biopharmaceuticals for subcutaneous administration.

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

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

Aerosolization Performance of Immunoglobulin G by Jet and Mesh Nebulizers

Recently, many preclinical and clinical studies have been conducted on the delivery of therapeutic antibodies to the lungs using nebulizers, but standard treatment guidelines have not yet been established. Our objective was to compare nebulization performance according to the low temperature and concentration of immunoglobulin G (IgG) solutions in different types of nebulizers, and to evaluate the stability of IgG aerosols and the amount delivered to the lungs. The output rate of the mesh nebulizers decreased according to the low temperature and high concentration of IgG solution, whereas the jet nebulizer was unaffected by the temperature and concentration of IgG. An impedance change of the piezoelectric vibrating element in the mesh nebulizers was observed because of the lower temperature and higher viscosity of IgG solution. This affected the resonance frequency of the piezoelectric element and lowered the output rate of the mesh nebulizers. Aggregation assays using a fluorescent probe revealed aggregates in IgG aerosols from all nebulizers. The delivered dose of IgG to the lungs in mice was highest at 95 ng/mL in the jet nebulizer with the smallest droplet size. Evaluation of the performance of IgG solution delivered to the lungs by three types of nebulizers could provide valuable parameter information for determination on dose of therapeutic antibody by nebulizers.

Accelerating therapeutic protein design with computational approaches toward the clinical stage

Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.

Effect of the Tubing Material Used in Peristaltic Pumping in Tangential Flow Filtration Processes of Biopharmaceutics on Particle Formation and Flux

Tangential flow filtration (TFF) is a central step in manufacturing of biopharmaceutics. Membrane clogging leads to decreased permeate flux, longer process time and potentially complete failure of the process. The effect of peristaltic pumping with tubings made of three different materials on protein particle formation during TFF was monitored via micro flow imaging, turbidity and photo documentation. At low protein concentrations, pumping with a membrane pump resulted in a stable flux with low protein particle concentration. Using a peristaltic pump led to markedly higher protein particle formation dependent on tubing type. With increasing protein particle formation propensity of the tubing, the permeate flux rate became lower and the process took longer. The protein particles formed in the pump were captured in the cassette and accumulated on the membrane leading to blocking. Using tubing with a hydrophilic copolymer modification counteracted membrane clogging and flux decrease by reducing protein particle formation. In ultrafiltration mode the permeate flux decrease was governed by the viscosity increase rather than by the protein aggregation; but using modified tubing is still beneficial due to a lower particle burden of the product. In summary, using tubing material for peristaltic pumping in TFF processes which leads a less protein particle formation, especially tubing material with hydrophilic modification, is highly beneficial for membrane flux and particle burden of the product.

BioMThermDB 1.0: Thermophysical Database of Proteins in Solutions

We present here a freely available web-based database, called BioMThermDB 1.0, of thermophysical and dynamic properties of various proteins and their aqueous solutions. It contains the hydrodynamic radius, electrophoretic mobility, zeta potential, self-diffusion coefficient, solution viscosity, and cloud-point temperature, as well as the conditions for those determinations and details of the experimental method. It can facilitate the meta-analysis and visualization of data, can enable comparisons, and may be useful for comparing theoretical model predictions with experiments.

Application of Supervised and Unsupervised Learning Approaches for Mapping Storage Conditions of Biopharmaceutical Product-A Case Study of Human Serum Albumin

The stability of biopharmaceutical therapeutics over the storage period/shelf life has been a challenging concern for manufacturers. A noble strategy for mapping best and suitable storage conditions for recombinant human serum albumin (rHSA) in laboratory mixture was optimized using chromatographic data as per principal component analysis (PCA), and similarity was defined using hierarchical cluster analysis. In contrast, separability was defined using linear discriminant analysis (LDA) models. The quantitation was performed for rHSA peak (analyte of interest) and its degraded products, i.e., dimer, trimer, agglomerates and other degradation products. The chromatographic variables were calculated using validated stability-indicating assay method. The chromatographic data mapping was done for the above-mentioned peaks over three months at different temperatures, i.e., 20°C, 5-8°C and at room temperature (25°C). The PCA had figured out the ungrouped variable, whereas supervised mapping was done using LDA. As an outcome result of LDA, about 60% of data were correctly classified with the highest sensitivity for 25°C (Aq), 25°C and 5-8°C (Aq with 5% glucose as a stabilizer), whereas the highest specificity was observed for samples stored at 5-8°C (Aq with 5% glucose as a stabilizer).

Rheological Properties of Different Graphene Nanomaterials in Biological Media

Carbon nanomaterials have received increased attention in the last few years due to their potential applications in several areas. In medicine, for example, these nanomaterials could be used as contrast agents, drug transporters, and tissue regenerators or in gene therapy. This makes it necessary to know the behavior of carbon nanomaterials in biological media to assure good fluidity and the absence of deleterious effects on human health. In this work, the rheological characterization of different graphene nanomaterials in fetal bovine serum and other fluids, such as bovine serum albumin and water, is studied using rotational and microfluidic chip rheometry. Graphene oxide, graphene nanoplatelets, and expanded graphene oxide at concentrations between 1 and 3 mg/mL and temperatures in the 25–40 °C range were used. The suspensions were also characterized by transmission and scanning electron microscopy and atomic force microscopy, and the results show a high tendency to aggregation and reveals that there is a protein–nanomaterial interaction. Although rotational rheometry is customarily used, it cannot provide reliable measurements in low viscosity samples, showing an apparent shear thickening, whereas capillary viscometers need transparent samples; therefore, microfluidic technology appears to be a suitable method to measure low viscosity, non-transparent Newtonian fluids, as it is able to determine small variations in viscosity. No significant changes in viscosity are found within the solid concentration range studied but it decreases between 1.1 and 0.6 mPa·s when the temperature raises from 25 to 40 °C.

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

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

An evolving view on food viscosity regulating gastric emptying

Viscosity is a property of most foods. The consumption of the high-viscosity food is associated with a variety of physiological responses, one of which is their ability to regulate gastric emptying and modulate postprandial glycemic response. Gastric emptying has been proven to be a key step affecting the digestion and absorption of food, whereas, the relationship between viscosity and gastric emptying is still far away from being understood. Here, we reviewed the factors that influence food viscosity and food viscosity changes during digestion. Besides, the effect of food viscosity on gastric emptying and food-viscosity-physiological response were highlighted. Finally, "quantitative relationship" of viscosity and gastric emptying was discussed. This review can contribute to the understanding that how food viscosity affects gastric emptying, and help for developing foods that could control satiety and manage body weight for the specific populations.

Discovery of compounds with viscosity-reducing effects on biopharmaceutical formulations with monoclonal antibodies

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Computational screening yielded 44 new viscosity-reducing agents on two model mAbs.

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Dual excipients for viscosity reduction and solution buffering were discovered.

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Compounds with three or more charges reduce the viscosity of model mAb formulations.

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Filtering based on physicochemical properties can be applied to other mAb formulations.

For the development of concentrated monoclonal antibody formulations for subcutaneous administration, the main challenge is the high viscosity of the solutions. To compensate for this, viscosity reducing agents are commonly used as excipients. Here, we applied two computational chemistry approaches to discover new viscosity-reducing agents: fingerprint similarity searching, and physicochemical property filtering. In total, 94 compounds were selected and experimentally evaluated on two model monoclonal antibodies, which led to the discovery of 44 new viscosity-reducing agents. Analysis of the results showed that using a simple filter that selects only compounds with three or more charge groups is a good ‘rule of thumb’ for selecting potential viscosity-reducing agents for two model monoclonal antibody formulations.

Towards an improved prediction of concentrated antibody solution viscosity using the Huggins coefficient

The viscosity of a monoclonal antibody solution must be monitored and controlled as it can adversely affect product processing, packaging and administration. Engineering low viscosity mAb formulations is challenging as prohibitive amounts of material are required for concentrated solution analysis, and it is difficult to predict viscosity from parameters obtained through low-volume, high-throughput measurements such as the interaction parameter, k_D, and the second osmotic virial coefficient, B₂₂. As a measure encompassing the effect of intermolecular interactions on dilute solution viscosity, the Huggins coefficient, k_h, is a promising candidate as a parameter measureable at low concentrations, but indicative of concentrated solution viscosity. In this study, a differential viscometry technique is developed to measure the intrinsic viscosity, [η], and the Huggins coefficient, k_h, of protein solutions. To understand the effect of colloidal protein-protein interactions on the viscosity of concentrated protein formulations, the viscometric parameters are compared to k_D and B₂₂ of two mAbs, tuning the contributions of repulsive and attractive forces to the net protein-protein interaction by adjusting solution pH and ionic strength. We find a strong correlation between the concentrated protein solution viscosity and the k_h but this was not observed for the k_D or the b₂₂, which have been previously used as indicators of high concentration viscosity. Trends observed in [η] and k_h values as a function of pH and ionic strength are rationalised in terms of protein-protein interactions.

Towards in silico Process Modeling for Vaccines

Chemical, manufacturing, and control development timelines occupy a significant part of vaccine end-to-end development. In the on-going race for accelerating timelines, in silico process development constitutes a viable strategy that can be achieved through an artificial intelligence (AI)-driven or a mechanistically oriented approach. In this opinion, we focus on the mechanistic option and report on the modeling competencies required to achieve it. By inspecting the most frequent vaccine process units, we identify fluid mechanics, thermodynamics and transport phenomena, intracellular modeling, hybrid modeling and data science, and model-based design of experiments as the pillars for vaccine development. In addition, we craft a generic pathway for accommodating the modeling competencies into an in silico process development strategy.

Case Study in the Design of a Surrogate Solution for Use in Biopharmaceutical Drug Product Process Development

The use of an aqueous-based surrogate solution in at-scale process development for biopharmaceutical drug products enables significant reduction in the usage of costly drug substance and improves confidence in initial drug product production runs performed using active biotherapeutic. Strategies for the formulation design of a surrogate solution that is representative of the unit operations in a typical drug product manufacturing process for a biopharmaceutical are presented herein, and a case study for the development of a surrogate solution for an example protein drug product is discussed. The surrogate was shown to have similar physical attributes to the drug product, including viscosity, surface tension, and density. The surrogate was used in at-scale process development of compounding, filling, and lyophilization operations in a single technical run, and the performance was shown to be similar to that of the drug product solution, providing a cost-effective and readily available option for process development while minimizing operator exposure to potentially hazardous drug solution and limiting drug wastage.