Is Lyophilization Key for Transportation and Storage of Biopharmaceutical Drug Products in Space?

Long-lasting space missions as well as space tourism are technically possible today and economically in reach. It is a matter of time until the use of biopharmaceutical drug products in space will be common practice. Until drug product manufacturing in space is possible, the products need to be brought to space with rockets, which means that stable and light-weight products are preferred. Lyophilization is a promising approach to reduce weight during transportation and achieve storage stability at room temperature without cold-chain demands. This implies that recycled water in space needs to be used for reconstitution which poses a microbiological challenge and should be considered during formulation development. Furthermore, administration of the injectable drugs in space has an impact on the chosen packaging material which needs to be considered during drug product development.

High throughput multidimensional liquid chromatography approach for online protein removal and characterization of polysorbates and poloxamer in monoclonal antibody formulations

The majority of commercially available monoclonal antibody (mAb) formulations are stabilized with one of three non-ionic surfactants: polysorbate 20 (PS20), polysorbate 80 (PS80), or poloxamer 188 (P188). All three surfactants are susceptible to degradation, which can result in functionality loss and subsequent protein aggregation or free fatty acid particle formation. Consequently, quantitative, and qualitative analysis of surfactants is an integral part of formulation development, stability, and batch release testing. Due to the heterogeneous nature of both polysorbates and poloxamer, online isolation of all the compounds from the protein and other excipients that may disturb the subsequent liquid chromatography with charged aerosol detection (LC-CAD) analysis poses a challenge. Herein, we present an analytical method employing LC-CAD, utilizing a combination of anion and cation exchange columns to completely remove proteins online before infusing the isolated surfactant onto a reversed-phase column. The method allows high throughput analysis of polysorbates within 8 minutes and poloxamer 188 within 12 minutes, providing a separation of the surfactant species of polysorbates (unesterified species, lower esters, and higher esters) and poloxamer 188 (early eluters and main species). Accuracy and precision assessed according to the International Council for harmonisation (ICH) guideline were 96 - 109 % and ≤1 % relative standard deviation respectively for all three surfactants in samples containing up to 110 mg/mL mAb. Subsequently, the method was effectively applied to quantify polysorbate 20 and polysorbate 80 in nine commercial drug products with mAb concentration of up to 180 mg/mL.

Three-Dimensional Homodyne Light Detection (3D-HLD) for High-Throughput Submicron Particle Analysis in (Highly Concentrated) Protein Biopharmaceuticals, Viral Vectors, and LNPs

During biopharmaceutical development, particle monitoring and characterization are crucial. Notably, particles can be impurities considered as critical quality attribute, or active pharmaceutical ingredient (e.g., viral vectors) or drug delivery system (e.g., lipid nanoparticles) itself. Three-dimensional homodyne light detection (3D-HLD) is a novel technique that can characterize particles in the ∼0.2 µm to 2.0 µm size range. We evaluated 3D-HLD for the analysis of high concentration protein formulations (up to 200 mg/mL), where formulation refractive index and background noise became limiting factors with increasing protein concentration. Sample viscosity however did not impact 3D-HLD results, in contrast to comparative analyses with NTA and MRPS. We also applied 3D-HLD in high-throughput screenings at high protein concentration or of lipid nanoparticle and viral vector formulations, where impurities were analyzed in the presence of a small (<0.2 µm) particulate active pharmaceutical ingredient. 3D-HLD turned out to be in good agreement with or a good complement to other state-of-the-art particle characterization techniques, including BMI, MRPS, and DLS. The main application of 3D-HLD is high-throughput particle analysis at low sample volume. Follow-up investigation of the optimized particle sizing approach and of detection settings could further improve the understanding of the method and potentially increase ease of operation.

A model-based optimization strategy to achieve fast and robust freeze-drying cycles

Freeze-drying is a time and cost-intensive process. The primary drying phase is the main target in a process optimization exercise. Biopharmaceuticals require an amorphous matrix for stabilization, which may collapse during primary drying if the critical temperature of the formulation is exceeded. The risk of product collapse should be minimized during a process optimization to accomplish a robust process, while achieving an economical process time. Mechanistic models facilitate the search for an optimal primary drying protocol. We propose a novel two-stage shelf temperature optimization approach to maximize sublimation during the primary drying phase, without risking product collapse. The approach includes experiments to obtain high-resolution variability data of process parameters such as the heat transfer coefficient, vial dimensions and dried layer resistance. These process parameters variability data are incorporated into an uncertainty analysis to estimate the risk of failure of the protocol. This optimization approach enables to identify primary drying protocols that are faster and more robust than a classical approach. The methodology was experimentally verified using two formulations which allow for either aggressive or conservative freeze-drying of biopharmaceuticals.

Osmotic properties of T cells determined by flow imaging microscopy in comparison to electrical sensing zone analysis

To develop cryopreservation methods for cell-based medicinal products it is important to understand osmotic responses of cells upon immersion into solutions with cryoprotective agents (CPAs) and during freezing. The aim of this study was to assess the osmotic response of T cells by using flow imaging microscopy (FIM) as a novel cell-sizing technique, and to corroborate the findings with electrical impedance measurements conducted on a Coulter counter. Jurkat cells were used as a potential model cell line for primary T cells. Cell volume responses were used to derive important cell parameters for cryopreservation such as the osmotically inactive cell volume Vb and the membrane permeability towards water and various CPAs. Unlike Coulter counter measurement, FIM, combined with Trypan blue staining can differentiate between viable and dead cells, which yields a more accurate estimation of Vb. Membrane permeabilities to water, dimethyl sulfoxide (Me2SO) and glycerol were measured for Jurkat cells at different temperatures. The permeation of Me2SO into the cells was faster in comparison to glycerol. CPA permeation decreased with decreasing temperature following Arrhenius behavior. Moreover, membrane permeability to water decreased in the presence of CPAs. Vb of Jurkat cells was found to be 49% of the isotonic volume and comparable to that of primary T cells. FIM proved to be a valuable tool to determine the membrane permeability parameters of mammalian cells to water and cryoprotective agents, which in turn can be used to rationally design CPA loading procedures for cryopreservation.

Evaluating the chaos game representation of proteins for applications in machine learning models: prediction of antibody affinity and specificity as a case study

CONTEXT

Machine learning techniques are becoming increasingly important in the selection and optimization of therapeutic molecules, as well as for the selection of formulation components and the prediction of long-term stability. Compared to first-principle models, machine learning techniques are easier to implement, and can identify correlations that would be hard to describe at a mechanistic level, but strongly rely on high-quality input training data. Here, we evaluate the potential of the "chaos game" representation to provide input data for machine learning models. The chaos game is an algorithm originally developed for the production of fractal structures, and later on applied also to the representation of biological sequences, such as genes and proteins. Our results show that the combination of the chaos game representation with convolutional neural networks results in comparable accuracy to other machine learning approaches, thus indicating that chaos game representations could be a valid alternative to existing featurization strategies for machine learning models of biological sequences.

METHODS

We implement the chaos game in Python 3.8.10, and use it to produce fractal as well as novel expanding representations of protein sequences. We then feed the resulting images to a convolutional neural network, built in Python 3.8.10, using TensorFlow 2.9.1, Keras 2.9.0, and the scikit-learn 1.1.1 packages. We select as case study a recently published dataset for the antibody emibetuzumab, with the objective of co-optimizing antibodies variants with both high affinity and low non-specific binding.

Possibilities and limitations of α-relaxation data of amorphous freeze-dried cakes to predict long term IgG1 antibody stability

The value of correlating global α-relaxations with long term protein stability after freeze-drying is inconsistently reported. This study aims to clarify whether and to what extend the long term stability of a freeze-dried protein formulation can be predicted with this method. For this purpose, the α-relaxation parameter τβ [h] of freshly prepared freeze-dried products is obtained by isothermal microcalorimetry. The concept is, that molecular movements in the amorphous matrix are strongly reduced in cakes with longer relaxation time and the product should therefore be more resistant against aggregation. To increase τβ in comparison to a conventional freeze-drying cycle, aggressive drying cycles including structural collapse of the product as well as tempering protocols after freeze-drying are applied. The τβ values are correlated with the aggregation rate of a freeze-dried IgG1 monoclonal antibody measured with high performance size exclusion chromatography. The antibody was used in its market formulation and 6 further compositions. A weak correlation between α-relaxation times and IgG1 aggregation was found. A higher mobility level through increased residual moisture helped to improve the correlation.

Purity and DNA content of AAV capsids assessed by analytical ultracentrifugation and orthogonal biophysical techniques

Development and manufacturing adeno-associated virus (AAV)-based vectors for gene therapy requires suitable analytical methods to assess the quality of the formulations during development, as well as the quality of different batches and the consistency of the processes. Here, we compare biophysical methods to characterize purity and DNA content of viral capsids from five different serotypes (AAV2, AAV5, AAV6, AAV8, and AAV9). For this purpose, we apply multiwavelength sedimentation velocity analytical ultracentrifugation (SV-AUC) to obtain the species' contents and to derive the wavelength-specific correction factors for the respective insert-size. In an orthogonal manner we perform anion exchange chromatography (AEX) and UV-spectroscopy and the three methods yield comparable results on empty/filled capsid contents with these correction factors. Whereas AEX and UV-spectroscopy can quantify empty and filled AAVs, only SV-AUC could identify the low amounts of partially filled capsids present in the samples used in this study. Finally, we employ negative-staining transmission electron microscopy and mass photometry to support the empty/filled ratios with methods that classify individual capsids. The obtained ratios are consistent throughout the orthogonal approaches as long as no other impurities and aggregates are present. Our results show that the combination of selected orthogonal methods can deliver consistent empty/filled contents on non-standard genome sizes, as well as information on other relevant critical quality attributes, such as AAV capsid concentration, genome concentration, insert size length and sample purity to characterize and compare AAV preparations.

Characterization of Virus Particles and Submicron-Sized Particulate Impurities in Recombinant Adeno-Associated Virus Drug Product

Characterization of particulate impurities such as aggregates is necessary to develop safe and efficacious adeno-associated virus (AAV) drug products. Although aggregation of AAVs can reduce the bioavailability of the virus, only a limited number of studies focus on the analysis of aggregates. We explored three technologies for their capability to characterize AAV monomers and aggregates in the submicron (<1 µm) size range: (i) mass photometry (MP), (ii) asymmetric flow field flow fractionation coupled to a UV-detector (AF4-UV/Vis) and (iii) microfluidic resistive pulse sensing (MRPS). Although low counts for aggregates impeded a quantitative analysis, MP was affirmed as an accurate and rapid method for quantifying the genome content of empty/filled/double-filled capsids, consistent with sedimentation velocity analytical ultracentrifugation results. MRPS and AF4-UV/Vis enabled the detection and quantification of aggregate content. The developed AF4-UV/Vis method separated AAV monomers from smaller aggregates, thereby enabling a quantification of aggregates <200 nm. MRPS was experienced as a straightforward method to determine the particle concentration and size distribution between 250-2000 nm, provided that the samples do not block the microfluidic cartridge. Overall, within this study we explored the benefits and limitations of the complementary technologies for assessing aggregate content in AAV samples.

Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties

Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.

An Interlaboratory Study to Identify Potential Visible Protein-Like Particle Standards

Visible protein-like particle standards may improve visual inspection and/or appearance testing practices used in the biotechnology industry. They may improve assay performance resulting in better alignment and more standardized training among different companies. The National Institute of Standards and Technology (NIST) has conducted an interlaboratory study to test whether the standards under development mimic typical proteinaceous particles found in biotherapeutics and if they can be implemented during the visual inspection process. Fourteen organizations from industry and government have participated. A total of 20 labs from these 14 organizations participated with analysts from 6 formulation, 7 analytical, 4 quality control, and 3 manufacturing labs. The circulated samples consisted of abraded ethylene tetrafluoroethylene (ETFE) particles or photolithographic particles. The results consist of qualitative ratings, which varied substantially among organizations and within labs. Polydisperse ETFE particle suspensions, containing particles enriched in greater than 150 µm in size, were rated more favorably than the photolithographic particles by formulation and analytical scientists. The largest monodisperse photolithographic particles (approximately 300 µm in size) were favored equally compared to ETFE by all scientists. Solution modifications to decrease the settling rate or to alter optical properties of the ETFE solutions yielded lower ratings by the analysts. Both particle types received mixed ratings for their usability and for their application for visual inspection and for training purposes. Industry feedback will assist NIST in developing reference material(s) for visible protein-like particles.

Graphical Abstract

Utility of Three Flow Imaging Microscopy Instruments for Image Analysis in Evaluating four Types of Subvisible Particle in Biopharmaceuticals

Subvisible particles (SVPs) are a critical quality attribute of parenteral and ophthalmic products. United States Pharmacopeia recommends the characterizations of SVPs which are classified into intrinsic, extrinsic, and inherent particles. Flow imaging microscopy (FIM) is useful as an orthogonal method in both the quantification and classification of SVPs because FIM instruments provide particle images. In addition to the conventionally used FlowCam (Yokogawa Fluid Imaging Technologies) and Micro-Flow Imaging (Bio-Techne) instruments, the iSpect DIA-10 (Shimadzu) instrument has recently been released. The three instruments have similar detection principles but different optical settings and image processing, which may lead to different results of the quantification and classification of SVPs based on the information from particle images. The present study compares four types of SVP (protein aggregates, silicone oil droplets, and surrogates for solid free-fatty-acid particles, milled-lipid particles, and sprayed-lipid particles) to compare the results of size distributions and classification abilities obtained using morphological features and a deep-learning approach. Although the three FIM instruments were effective in classifying the four types of SVP through convolutional neural network analysis, there was no agreement on the size distribution for the same protein aggregate solution, suggesting that using the classifiers of the FIM instruments could result in different evaluations of SVPs in the field of biopharmaceuticals.

Imaging Flow Cytometry for Sizing and Counting of Subvisible Particles in Biotherapeutics

Imaging flow cytometry (IFC), a technique originally designed for cellular imaging, is featured by the parallel acquisition in brightfield (BF), fluorescence (FL), and side scattering channels. Introduced to the field of subvisible particle analysis in biopharmaceuticals roughly ten years ago, it has the potential to yield additional information, e.g., on particle origin. Here, we present an extensive, systematic development of masks for IFC image analysis to optimize the accuracy of size determination of polystyrene beads and pharmaceutically relevant particles (protein, silicone oil) in BF and FL channels. Based on the developed masks, particle sizing and counting by IFC are compared to flow imaging microscopy (FIM). Mask verification based on fluorescent polystyrene particles revealed good agreement between sizes obtained from IFC and FIM. In the evaluation of counting accuracy, IFC reported lower concentrations for polystyrene particle standards than FIM. For the analysis of fluorescently stained silicone oil and protein particles however, IFC FL imaging reported higher particle concentrations in the low micrometer size range. Overall, we identified IFC as suitable tool to generate supportive data for particle characterization purposes or trouble shooting activities, but not as routine quantitative technique, e.g., for subvisible particle analysis during drug product development or quality control.

Combining Machine Learning and Backgrounded Membrane Imaging: A Case Study in Comparing and Classifying Different Types of Biopharmaceutically Relevant Particles

This study investigates how backgrounded membrane imaging (BMI) can be used in combination with convolutional neural networks (CNNs) in order to quantitatively and qualitatively study subvisible particles in both protein biopharmaceuticals and samples containing synthetic model particles. BMI requires low sample volumes and avoids many technical complications associated with imaging particles in solution, e.g., air bubble interference, low refractive index contrast between solution and particles of interest, etc. Hence, BMI is an attractive technique for characterizing particles at various stages of drug product development. However, to date, the morphological information encoded in brightfield BMI images has scarcely been utilized. Here we show that CNN based methods can be useful in extracting morphological information from (label-free) brightfield BMI particle images. Images of particles from biopharmaceutical products and from laboratory prepared samples were analyzed with two types of CNN based approaches: traditional supervised classifiers and a recently proposed fingerprinting analysis method. We demonstrate that the CNN based methods are able to efficiently leverage BMI data to distinguish between particles comprised of different proteins, various fatty acids (representing polysorbate degradation related particles), and protein surrogates (NIST ETFE reference material) only based on BMI images. The utility of using the fingerprinting method for comparing morphological differences and similarities of particles formed in distinct drug products and/or laboratory prepared samples is further demonstrated and discussed through three case studies.

Ongoing Challenges to Develop High Concentration Monoclonal Antibody-based Formulations for Subcutaneous Administration: Quo Vadis?

Although many subcutaneously (s.c.) delivered, high-concentration antibody formulations (HCAF) have received regulatory approval and are widely used commercially, formulation scientists are still presented with many ongoing challenges during HCAF development with new mAb and mAb-based candidates. Depending on the specific physicochemical and biological properties of a particular mAb-based molecule, such challenges vary from pharmaceutical attributes e.g., stability, viscosity, manufacturability, to clinical performance e.g., bioavailability, immunogenicity, and finally to patient experience e.g., preference for s.c. vs. intravenous delivery and/or preferred interactions with health-care professionals. This commentary focuses on one key formulation obstacle encountered during HCAF development: how to maximize the dose of the drug? We examine methodologies for increasing the protein concentration, increasing the volume delivered, or combining both approaches together. We discuss commonly encountered hurdles, i.e., physical protein instability and solution volume limitations, and we provide recommendations to formulation scientists to facilitate their development of s.c. administered HCAF with new mAb-based product candidates.

Calorimetric Investigation of the Relaxation Phenomena in Amorphous Lyophilized Solids

Studying the thermal history and relaxation of solid amorphous drug product matrices by calorimetry is a well-known approach, particularly in the context of correlating the matrix parameters with the long-term stability of freeze-dried protein drug products. Such calorimetric investigations are even more relevant today, as the application of new process techniques in freeze-drying (which strongly influence the thermal history of the products) has recently gained more interest. To revive the application of calorimetric methods, the widely scattered knowledge on this matter is condensed into a review and completed with new experimental data. The calorimetric methods are applied to recent techniques in lyophilization, such as controlled nucleation and aggressive/collapse drying. Phenomena such as pre-Tg events in differential scanning calorimetry and aging shoulders in isothermal microcalorimetry are critically reviewed and supplemented with data of freeze-dried products that have not been characterized with these methods before.

Minimizing Oxidation of Freeze-Dried Monoclonal Antibodies in Polymeric Vials Using a Smart Packaging Approach

Primary containers made of cyclic olefin polymer (COP) have recently gained attention since they may overcome several risks and shortcomings of glass containers as they exhibit a high break resistance, biocompatibility, and homogeneous heat transfer during lyophilization. On the downside, COP is more permeable for gases, which can lead to an ingress of oxygen into the container over time. Since oxidation is an important degradation pathway for monoclonal antibodies (mAbs), the continuous migration of oxygen into drug product containers should be avoided overall. To date, no long-term stability studies regarding lyophilizates in polymer vials have been published, potentially because of the unbearable gas permeability. In this study, we demonstrate that after lyophilization in COP vials and storage of these vials in aluminum pouches together with combined oxygen and moisture absorbers (“smart packaging”), oxidation of two lyophilized therapeutic antibodies was as low as in glass vials due to the deoxygenated environment in the pouch. Nevertheless, active removal of oxygen from the primary container below the initial level over time during storage in such “smart” secondary packaging was not achieved. Furthermore, residual moisture was controlled. Overall, the smart packaging reveals a promising approach for long-term stability of biopharmaceuticals; in addition to COP’s known benefits, stable, low oxygen and moisture levels as well as the protection from light and cushioning against mechanical shock by the secondary packaging preserve the sensitive products very well.

Towards quantification and differentiation of protein aggregates and silicone oil droplets in the low micrometer and submicrometer size range by using oil-immersion flow imaging microscopy and convolutional neural networks

Biopharmaceutical product characterization benefits from the quantification and differentiation of unwanted protein aggregates and silicone oil droplets to support risk assessment and control strategies as part of the development. Flow imaging microscopy is successfully applied to differentiate the two impurities in the size range larger than about 5 µm based on their morphological appearance. In our study we applied the combination of oil-immersion flow imaging microscopy and convolutional neural networks to extend the size range below 5 µm. It allowed to differentiate and quantify heat stressed therapeutic monoclonal antibody aggregates from artificially generated silicone oil droplets with misclassification rates of about 10% in the size range between 0.3 and 5 µm. By comparing the misclassifications across the tested size range, particles in the low submicron size range were particularly difficult to differentiate as their morphological appearance becomes very similar.

Forced degradation of cell-based medicinal products guided by flow imaging microscopy: Explorative studies with Jurkat cells

Cell-based medicinal products (CBMPs) offer ground-breaking opportunities to treat diseases with limited or no therapeutic options. However, the intrinsic complexity of CBMPs results in great challenges with respect to analytical characterization and stability assessment. In our study, we submitted Jurkat cell suspensions to forced degradation studies mimicking conditions to which CBMPs might be exposed from procurement of cells to administration of the product. Flow imaging microscopy assisted by machine learning was applied for determination of cell viability and concentration, and quantification of debris particles. Additionally, orthogonal cell characterization techniques were used. Thawing of cells at 5 °C was detrimental to cell viability and resulted in high numbers of debris particles, in contrast to thawing at 37 °C or 20 °C which resulted in better stability. After freezing of cell suspensions at -18 °C in presence of dimethyl sulfoxide (DMSO), a DMSO concentration of 2.5% (v/v) showed low stabilizing properties, whereas 5% or 10% was protective. Horizontal shaking of cell suspensions did not affect cell viability, but led to a reduction in cell concentration. Fetal bovine serum (10% [v/v]) protected the cells during shaking. In conclusion, forced degradation studies with application of orthogonal analytical characterization methods allow for CBMP stability assessment and formulation screening.

Comparison of Different Liquid Chromatography-Based Purification Strategies for Adeno-Associated Virus Vectors

Recombinant adeno-associated virus (rAAV) vectors have evolved as one of the most promising technologies for gene therapy due to their good safety profile, high transduction efficacy, and long-term gene expression in nondividing cells. rAAV-based gene therapy holds great promise for treating genetic disorders like inherited blindness, muscular atrophy, or bleeding disorders. There is a high demand for efficient and scalable production and purification methods for rAAVs. This is particularly true for the downstream purification methods. The current standard methods are based on multiple steps of gradient ultracentrifugation, which allow for the purification and enrichment of full rAAV particles, but the scale up of this method is challenging. Here, we explored fast, scalable, and universal liquid chromatography-based strategies for the purification of rAAVs. In contrast to the hydrophobic interaction chromatography (HIC), where a substantial amount of AAV was lost, the cation exchange chromatography (CEX) was performed robustly for multiple tested serotypes and resulted in a mixture of full and empty rAAVs with a good purity profile. For the used affinity chromatography (AC), a serotype dependence was observed. Anion exchange chromatography (AEX) worked well for the AAV8 serotype and achieved high levels of purification and a baseline separation of full and empty rAAVs. Depending on the AAV serotype, a combination of CEX and AEX or AC and AEX is recommended and holds promise for future translational projects that require highly pure and full particle-enriched rAAVs.

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.

Oil-Immersion Flow Imaging Microscopy for Quantification and Morphological Characterization of Submicron Particles in Biopharmaceuticals

Flow imaging microscopy (FIM) is widely used to analyze subvisible particles starting from 2 μm in biopharmaceuticals. Recently, an oil-immersion FIM system emerged, the FlowCam Nano, designed to enable the characterization of particle sizes even below 2 μm. The aim of our study was to evaluate oil-immersion FIM (by using FlowCam Nano) in comparison to microfluidic resistive pulse sensing and resonant mass measurement for sizing and counting of particles in the submicron range. Polystyrene beads, a heat-stressed monoclonal antibody formulation and a silicone oil emulsion, were measured to assess the performance on biopharmaceutical relevant samples, as well as the ability to distinguish particle types based on instrument-derived morphological parameters. The determination of particle sizes and morphologies suffers from inaccuracies due to a low image contrast of small particles and light-scattering effects. The ill-defined measured volume impairs an accurate concentration determination. Nevertheless, FlowCam Nano in its current design complements the limited toolbox of submicron particle analysis of biopharmaceuticals by providing particle images in a size range that was previously not accessible with commercial FIM instruments.

Taking Subvisible Particle Quantitation to the Limit: Uncertainties and Statistical Challenges With Ophthalmic Products for Intravitreal Injection

Subvisible particles are a critical quality attribute of pharmaceutical products. The reliability of particle quantitation increases with the number of particles in the analyzed sample volume. However, for analyses of low-volume drug products, such as ophthalmic products for intravitreal injection or biopharmaceuticals in general, sample volumes as small as possible should be used to avoid pooling and consequently, the contamination with foreign particles. The aim of our study was to evaluate the variability of particle concentrations obtained by light obscuration measurements to define the minimum required analyzed sample volume to achieve statistically meaningful results by using conditions that are practically feasible. Statistical evaluation suggests that for particle concentrations close to a predefined limit, large sample volumes (a multiple of typical intravitreal product volumes) would be required for a high probability to correctly classify samples with respect to the predefined limit. Below a minimum analyzed volume, even a measurement result of 0 particles does not allow to conclude compliance with the respective particle concentration limit with sufficient certainty. A small analyzed volume could be justified as long as the measurement uncertainty remains acceptable compared with the predefined limit.

What Makes Polysorbate Functional? Impact of Polysorbate 80 Grade and Quality on IgG Stability During Mechanical Stress

Polysorbate 80 (PS80) is a commonly used surfactant in therapeutic protein formulations to mitigate adsorption and interface-induced protein aggregation. Several PS80 grades and qualities are available on the market for parenteral application. The role of PS80 grade on protein stability remains debatable, and the impact of (partially) degraded PS on protein aggregation is not yet well understood. In our study, a monoclonal antibody (IgG) was subjected to 3 different mechanical stress conditions in the presence of multicompendial (MC) and Chinese pharmacopeia (ChP) grade PS80. Furthermore, IgG formulations were spiked with (partly) hydrolyzed PS80 to investigate the effect of PS80 degradants on protein stability. PS80 functionality was assessed by measuring the extent of protein aggregation and particle formation induced during mechanical stress by using size-exclusion chromatography, dynamic light scattering, backgrounded membrane imaging, and flow imaging microscopy. No distinguishable differences in PS80 functionality between MC and ChP grade were observed in the 3 stress tests. However, with increasing degree of PS80 hydrolysis, higher counts of subvisible particles were measured after stress. Furthermore, higher levels of PS80 degradants at a constant PS80 concentration may destabilize the IgG. In conclusion, MC and ChP grade PS80 are equally protective, but PS80 degradants compromise IgG stability.

Laser-induced breakdown detection of temperature-ramp generated aggregates of therapeutic monoclonal antibody

The detection and characterization of protein aggregation is essential during development and quality control of therapeutic proteins, as aggregates are typically inactive and may trigger anti-drug-antibody formation in patients. Especially large multi-domain molecules, such as the important class of therapeutic monoclonal antibodies (mAbs), can form various aggregates that differ in size and morphology. Although particle analysis advanced over the recent years, new techniques and orthogonal methods are highly valued. To our knowledge, the physical principle of laser-induced breakdown detection (LIBD) was not yet applied to sense aggregates in therapeutic protein formulations. We established a LIBD setup to monitor the temperature-induced aggregation of a mAb. The obtained temperature of aggregation was in good agreement with the results from previously published temperature-ramped turbidity and dynamic light scattering measurements. This study demonstrates the promising applicability of LIBD to investigate aggregates from therapeutic proteins. The technique is also adaptive to online detection and size determination, and offers interesting opportunities for morphologic characterization of protein particles and impurities, which will be part of future studies.

High-throughput melting-temperature analysis of a monoclonal antibody by differential scanning fluorimetry in the presence of surfactants

Differential scanning fluorimetry (DSF) is successfully used as a high-throughput screening method for the analysis of the protein melting temperature (T(m)) in the development of therapeutic monoclonal antibody (MAb) formulations. Typically, surfactants are utilized in MAb formulations as a stabilizer, but the commonly applied polarity-sensitive dye SYPRO® Orange shows bright fluorescence in the presence of micelles, concealing the signal of protein unfolding. Studying various MAb formulations containing polysorbate 20, polysorbate 80, or poloxamer 188 (PX 188), the molecular rotor probe 4-(dicyanovinyl)julolidine (DCVJ) was investigated. Although limited to higher MAb concentrations, DCVJ enabled the determination of T(m) in many formulations where SYPRO® Orange failed. It is important to note that careful background correction of placebo formulations is essential for the precise determination of T(m) and especially T(m onset). Thermal shifts of T(m1) (lowest observed thermal transition) indicating stabilizing or destabilizing effects of pH or excipient were in good agreement across all tested formulations and correlated well with differential scanning calorimetry measurements. Additionally, the micellization temperature of PX 188 was confirmed, which leads to a nonproteinous transition. With this new method, it is possible to apply DSF during the development of therapeutic proteins in surfactant-containing formulations.