Protein particles: What we know and what we do not know

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images

Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morphological differences, stresses that have been applied to monoclonal antibodies (mAbs) can be identified. This study aims to evaluate common biotherapeutic drug storage and shipment conditions that are known to impact protein aggregation. Two different studies were conducted to capture particle images using micro-flow imaging and to classify particles using a convolutional neural network. The first study evaluated particles produced in response to agitation, heat, and freeze-thaw stresses in one mAb formulated in five different formulations. The second study evaluated particles from two common drug containers, a high-density polyethylene bottle and a glass vial, in six mAbs exposed solely to agitation stress. An extension of this study was also conducted to evaluate the impact of sequential stress exposure compared to exposure to one stress alone, on particle morphology. Overall, the convolutional neural network was able to classify particles belonging to a particular formulation or container. These studies indicate that storage and shipping stresses can impact particle morphology according to formulation composition and mAb.

Non-Destructive Analysis of Subvisible Particles with Mie-Scattering-Based Light Sheet Technology: System Development

The characteristics of subvisible particles (SbVPs) are critical quality attributes of injectable and ophthalmic solutions in pharmaceutical manufacturing. However, current compendial SbVP testing methods, namely the light obstruction method and the microscopic particle count method, are destructive and wasteful of target samples. In this study, we present the development of a non-destructive SbVP analyzer aiming to analyze SbVPs directly in drug product (DP) containers while keeping the samples intact. Custom sample housings are developed and incorporated into the analyzer to reduce optical aberrations introduced by the curvature of typical pharmaceutical DP sample containers. The analyzer integrates a light-sheet microscope structure and models the side scattering event from a particle with Mie scattering theory with refractive indices as prior information. Equivalent spherical particle size under assigned refractive index values is estimated, and the particle concentration is determined based on the number of scattering events and the volume sampled by the light sheet. The resulting analyzer's capability and performance to non-destructively analyze SbVPs in DP containers were evaluated using a series of polystyrene bead suspensions in ISO 2R and 6R vials. Our results and analysis show the particle analyzer is capable of directly detecting SbVPs from intact DP containers, sorting SbVPs into commonly used size bins (e.g. ≥ 2 µm, ≥ 5 µm, ≥ 10 µm, and ≥ 25 µm), and reliably quantifying SbVPs in the concentration range of 4.6e2 to 5.0e5 particle/mL with a margin of ± 15 % error based on a 90 % confidence interval.

Comparison of Protein-like Model Particles Fabricated by Micro 3D Printing to Established Standard Particles

Innovative analytical instruments and development of new methods has provided a better understanding of protein particle formation in biopharmaceuticals but have also challenged the ability to obtain reproducible and reliable measurements. The need for protein-like particle standards mimicking the irregular shape, translucent nature and near-to-neutral buoyancy of protein particles remained one of the hot topics in the field of particle detection and characterization in biopharmaceutical formulations. An innovative protein-like particle model has been developed using two photo polymerization (2PP) printing allowing to fabricate irregularly shaped particles with similar properties as protein particles at precise size of 50 µm and 150 µm, representative of subvisible particles and visible particles, respectively. A study was conducted to compare the morphological, physical, and optical properties of artificially generated protein particles, polystyrene spheres, ETFE, and SU-8 particle standards, along with newly developed protein-like model particles manufactured using 2PP printing. Our results suggest that 2PP printing can be used to produce protein-like particle standards that might facilitate harmonization and standardization of subvisible and visible protein particle characterization across laboratories and organizations.

Biophysical Principles Emerging from Experiments on Protein-Protein Association and Aggregation

Protein-protein association and aggregation are fundamental processes that play critical roles in various biological phenomena, from cellular signaling to disease progression. Understanding the underlying biophysical principles governing these processes is crucial for elucidating their mechanisms and developing strategies for therapeutic intervention. In this review, we provide an overview of recent experimental studies focused on protein-protein association and aggregation. We explore the key biophysical factors that influence these processes, including protein structure, conformational dynamics, and intermolecular interactions. We discuss the effects of environmental conditions such as temperature, pH and related buffer-specific effects, and ionic strength and related ion-specific effects on protein aggregation. The effects of polymer crowders and sugars are also addressed. We list the techniques used to study aggregation. We analyze emerging trends and challenges in the field, including the development of computational models and the integration of multidisciplinary approaches for a comprehensive understanding of protein-protein association and aggregation.

Stability of Protein Pharmaceuticals: Recent Advances

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

Closed, one-stop intelligent and accurate particle characterization based on micro-Raman spectroscopy and digital microfluidics

Monoclonal antibodies are prone to form protein particles through aggregation, fragmentation, and oxidation under varying stress conditions during the manufacturing, shipping, and storage of parenteral drug products. According to pharmacopeia requirements, sub-visible particle levels need to be controlled throughout the shelf life of the product. Therefore, in addition to determining particle counts, it is crucial to accurately characterize particles in drug product to understand the stress condition of exposure and to implement appropriate mitigation actions for a specific formulation. In this study, we developed a new method for intelligent characterization of protein particles using micro-Raman spectroscopy on a digital microfluidic chip (DMF). Several microliters of protein particle solutions induced by stress degradation were loaded onto a DMF chip to generate multiple droplets for Raman spectroscopy testing. By training multiple machine learning classification models on the obtained Raman spectra of protein particles, eight types of protein particles were successfully characterized and predicted with high classification accuracy (93%-100%). The advantages of the novel particle characterization method proposed in this study include a closed system to prevent particle contamination, one-stop testing of morphological and chemical structure information, low sample volume consumption, reusable particle droplets, and simplified data analysis with high classification accuracy. It provides great potential to determine the probable root cause of the particle source or stress conditions by a single testing, so that an accurate particle control strategy can be developed and ultimately extend the product shelf-life.

Screening techniques for monitoring the sub-visible particle formation of free fatty acids in biopharmaceuticals

Free fatty acid (FFA) particles that originate from the enzymatic hydrolysis of polysorbate (PS) via co-purified host cell proteins generally appear abruptly in drug products during real-time (long-term) storage. Efforts were taken to understand the kinetics of FFA particle formation, aiming for a mitigation strategy. However, it is rather challenging particularly in the sub-visible particle (SVP) range, due to either the insufficient sensitivity of the analytical techniques used or the interference of the formulation matrices of proteinaceous drug products. In this study, we examined the feasibility of Raman microscopy, backgrounded membrane imaging (BMI) and total holographic characterization (THC) on the detection of FFA sub-visible particles (SVPs). The results indicate that THC is the most sensitive technique to track their occurrence during the course of PS hydrolysis. Moreover, with this technique we are able to distinguish different stages of FFA particle formation in the medium. In addition, a real time stability study of a biopharmaceutical was analyzed, demonstrating the viability of THC to monitor SVPs in a real sample and correlate it to the visible particles (VPs) occurrence.

Investigating Thermally Induced Aggregation of Somatropin- New Insights Using Orthogonal Techniques

Three orthogonal techniques were used to provide new insights into thermally induced aggregation of the therapeutic protein Somatropin at pH 5.8 and 7.0. The techniques were Dynamic Light Scattering (DLS), Asymmetric Flow-Field Flow-Fractionation (AF4), and the TEM-based analysis system MiniTEM™. In addition, Differential Scanning Calorimetry (DSC) was used to study the thermal unfolding and stability. DSC and DLS were used to explain the initial aggregation process and aggregation rate at the two pH values. The results suggest that electrostatic stabilization seems to be the main reason for the faster initial aggregation at pH 5.8, i.e., closer to the isoelectric point of Somatropin. AF4 and MiniTEM were used to investigate the aggregation pathway further. Combining the results allowed us to demonstrate Somatropin's thermal aggregation pathway at pH 7.0. The growth of the aggregates appears to follow two steps. Smaller elongated aggregates are formed in the first step, possibly initiated by partly unfolded species. In the second step, occurring during longer heating, the smaller aggregates assemble into larger aggregates with more complex structures.

Global Analysis of Aggregation Profiles of Three Kinds of Immuno-Oncology mAb Drug Products Using Flow Cytometry

Accurately quantifying the protein particles in both subvisible (1-100 μm) and submicron (≤1 μm) ranges remains a prominent challenge in the development and manufacturing of protein drugs. Due to the limitation of the sensitivity, resolution, or quantification level of various measurement systems, some instruments may not provide count information, while others can only count particles in a limited size range. Moreover, the reported concentrations of protein particles commonly have significant discrepancies owing to different methodological dynamic ranges and the detection efficiency of these analytical tools. Therefore, it is extremely difficult to accurately and comparably quantify protein particles within the desired size range at one time. To develop an efficient protein aggregation measurement method that can span the entire range of interest, we established, in this study, a single particle-sizing/counting method based on our highly sensitive lab-built flow cytometry (FCM) system. The performance of this method was assessed, and its capability of identifying and counting microspheres between 0.2 and 25 μm was demonstrated. It was also used to characterize and quantify both subvisible and submicron particles in three kinds of top-selling immuno-oncology antibody drugs and their lab-produced counterparts. These assessment and measurement results suggest that there may be a role for an enhanced FCM system as an efficient investigative tool for characterizing and learning the molecular aggregation behavior, stability, or safety risk of protein products.

Mechanism of Protein-PDMS Visible Particles Formation in Liquid Vial Monoclonal Antibody Formulation

Visible particles (VPs) formation in liquid monoclonal antibody formulations is a critical quality issue. Formulations that include poloxamer 188 (PX188) as a surfactant are prone to the formation of VPs comprising aggregated complexes of protein and polydimethylsiloxane (PDMS; silicone oil) derived from primary containers. However, the mechanisms through which these VPs form are complicated and remain to be fully elucidated. This study demonstrates for the first time the dominant spot and pathway of protein-PDMS VP formation in a particular liquid vial formulation. Specifically, when a vial sealed with a PDMS-coated stopper is stored in an upright position under conditions whereby the antibody solution has become well-adhered to the stopper and an air phase exists in the vicinity, protein-PDMS aggregates form on the stopper and are then desorbed into the drug solution to be detected as VPs. Here, we evaluated the effects of several factors on VP formation: adhesion of the drug solution to the stopper, storage orientation, silicone coating on the stopper, vial material, and hydrophobicity of PX188. Remarkably, we found that changing any one of the factors could significantly affect VP formation. Our findings are instructive for better understanding the mechanisms of VP formation in vial products and can provide strategies for VP mitigation in biotherapeutics.

Evaluation of a Self-Supervised Machine Learning Method for Screening of Particulate Samples: A Case Study in Liquid Formulations

Imaging is commonly used as a characterization method in the pharmaceuticals industry, including for quantifying subvisible particles in solid and liquid formulations. Extracting information beyond particle size, such as classifying morphological subpopulations, requires some type of image analysis method. Suggested methods to classify particles have been based on pre-determined morphological features or use supervised training of convolutional neural networks to learn image representations in relation to ground truth labels. Complications arising from highly complex morphologies, unforeseen classes, and time-consuming preparation of ground truth labels, are some of the challenges faced by these methods. In this work, we evaluate the application of a self-supervised contrastive learning method in studying particle images from therapeutic solutions. Unlike with supervised training, this approach does not require ground truth labels and representations are learned by comparing particle images and their augmentations. This method provides a fast and easily implementable tool of coarse screening for morphological attribute assessment. Furthermore, our analysis shows that in cases with relatively balanced datasets, a small subset of an image dataset is sufficient to train a convolutional neural network encoder capable of extracting useful image representations. It is also demonstrated that particle classes typically observed in protein solutions administered by pre-filled syringes emerge as separated clusters in the encoder's embedding space, facilitating performing tasks such as training weakly-supervised classifiers or identifying the presence of new subpopulations.

An Intra-Company Analysis of Inherent Particles in Biologicals Shapes the Protein Particle Mitigation Strategy Across Development Stages

To better understand protein aggregation and inherent particle formation in the biologics pipeline at Novartis, a cross-functional team collected and analyzed historical protein particle issues. Inherent particle occurrences from the past 10 years were systematically captured in a protein particle database. Where the root cause was identified, a number of product attributes (such as development stage, process step, or protein format) were trended. Several key themes were revealed: 1) there was a higher propensity for inherent particle formation with non-mAbs than with mAbs; 2) the majority of particles were detected following manufacturing at scale, and were not predicted by the small-scale studies; 3) most issues were related to visible particles, followed by subvisible particles; 4) 50% of the issues were manufacturing related. These learnings became the foundation of a particle mitigation strategy across development and technical transfer, and resulted in a set of preventive actions. Overall, this study provides further insight into a recognized industry challenge and hopes to inspire the biopharmaceutical industry to transparently share their experiences with inherent particles formation.

Biophysical studies of amorphous protein aggregation and in vivo immunogenicity

Amorphous protein aggregates are oligomers that lack specific, high-order structures. Soluble amorphous aggregates are smaller than ~1 µm. Despite their lack of high-order structure, amorphous protein aggregates exhibit specific biophysical properties such as reversibility of formation, density, conformation, and biochemical stability. Our mutational analysis using a Solubility Controlling Peptide (SCP) tag strongly suggests that amorphous aggregation of small globular proteins can significantly increase in vivo immune response and that the magnitude of enhanced immune responses depends on the aggregates' biophysical and biochemical properties. We propose that SCP tags might help develop subunit (protein) adjuvant-free (immunostimulant-free) vaccines by controlling the aggregation propensity of target proteins.

Machine Learning Analysis Provides Insight into Mechanisms of Protein Particle Formation Inside Containers During Mechanical Agitation

Container choice can influence particle generation within protein formulations. Incompatibility between proteins and containers can manifest as increased particle concentrations, shifts in particle size distributions and changes in particle morphology distributions. In this study, flow imaging microscopy (FIM) combined with machine learning-based goodness-of-fit hypothesis testing algorithms were used in accelerated stability studies to investigate the impact of containers on particle formation. Containers in four major container categories subdivided into eleven container types were filled with monoclonal antibody formulations and agitated with and without headspace, producing subvisible particles. Digital images of the particles were recorded using flow imaging microscopy and analyzed with machine learning algorithms. Particle morphology distributions depended on container category and type, revealing differences that would not have been obvious by analysis of particle concentrations or container surface characteristics alone. Additionally, the algorithm was used to compare morphologies of particles generated in containers against those generated using isolated stresses at air-liquid and container-air-liquid interfaces. These comparisons showed that the morphology distributions of particles formed during agitation most closely resemble distributions that result from exposure of proteins to moving triple interface lines at points where container-air-liquid interfaces intersect. The approach described here can be used to identify dominant causes of particle generation due to protein-container interactions.

Inhaled antibodies: Quality and performance considerations

The use of antibodies in the treatment of lung diseases is of increasing interest especially as the search for COVID-19 therapies has unfolded. Historically, the use of antibody therapy was based on multiple targets including receptors involved in local hyper-reactivity in asthma, viruses and micro-organisms involved in a variety of pulmonary infectious disease. Generally, protein therapeutics pose challenges with respect to formulation and delivery to retain activity and assure therapy. The specificity of antibodies amplifies the need for attention to molecular integrity not only in formulation but also during aerosol delivery for pulmonary administration. Drug product development can be viewed from considerations of route of administration, dosage form, quality, and performance measures. Nebulizers and dry powder inhalers have been used to deliver protein therapeutics and each has its advantages that should be matched to the needs of the drug and the disease. This review offers insight into quality and performance barriers and the opportunities that arise from meeting them effectively.

An Interlaboratory Comparison on the Characterization of a Sub-micrometer Polydisperse Particle Dispersion

The measurement of polydisperse protein aggregates and particles in biotherapeutics remains a challenge, especially for particles with diameters of ≈ 1 µm and below (sub-micrometer). This paper describes an interlaboratory comparison with the goal of assessing the measurement variability for the characterization of a sub-micrometer polydisperse particle dispersion composed of five sub-populations of poly(methyl methacrylate) (PMMA) and silica beads. The study included 20 participating laboratories from industry, academia, and government, and a variety of state-of-the-art particle-counting instruments. The received datasets were organized by instrument class to enable comparison of intralaboratory and interlaboratory performance. The main findings included high variability between datasets from different laboratories, with coefficients of variation from 13 % to 189 %. Intralaboratory variability was, on average, 37 % of the interlaboratory variability for an instrument class and particle sub-population. Drop-offs at either end of the size range and poor agreement on maximum counts of particle sub-populations were noted. The mean distributions from an instrument class, however, showed the size-coverage range for that class. The study shows that a polydisperse sample can be used to assess performance capabilities of an instrument set-up (including hardware, software, and user settings) and provides guidance for the development of polydisperse reference materials.

A General Small-Angle X-ray Scattering-Based Screening Protocol for Studying Physical Stability of Protein Formulations

A fundamental step in developing a protein drug is the selection of a stable storage formulation that ensures efficacy of the drug and inhibits physiochemical degradation or aggregation. Here, we designed and evaluated a general workflow for screening of protein formulations based on small-angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling, temperature control, and fast data analysis and provides protein particle interaction information. SAXS, together with different methods including turbidity analysis, dynamic light scattering (DLS), and SDS-PAGE measurements, were used to obtain different parameters to provide high throughput screenings. Using a set of model proteins and biopharmaceuticals, we show that SAXS is complementary to dynamic light scattering (DLS), which is widely used in biopharmaceutical research and industry. We found that, compared to DLS, SAXS can provide a more sensitive measure for protein particle interactions, such as protein aggregation and repulsion. Moreover, we show that SAXS is compatible with a broader range of buffers, excipients, and protein concentrations and that in situ SAXS provides a sensitive measure for long-term protein stability. This workflow can enable future high-throughput analysis of proteins and biopharmaceuticals and can be integrated with well-established complementary physicochemical analysis pipelines in (biopharmaceutical) research and industry.

Fate of Antibody and Polysorbate Particles in a Human Serum Model

Monoclonal antibodies (mAbs) and excipients can degrade owing to different stress factors they encounter during their life cycle or after administration in human body. This can result in the formation of aggregates and particulates. As particles can evoke an immune response in patients, it becomes increasingly important to monitor their fate after administration. In this study, we used a protein-free serum model to assess the fate of mAb and polysorbate (PS) particles under physiologic conditions. Commonly encountered stress conditions such as pH, temperature, extrusion, and shaking were chosen to generate mAb particles. Alkaline hydrolysis was used to generate PS particles. The fate of aggregates and particles was evaluated in serum and histidine buffer. We observed that depending on the nature of stress and the environment particles are subjected to, the fate of particles can differ substantially. The mAb aggregates generated by pH stress, showed reduction in HMWS from 26% to 6% over 14days in human serum filtrate. PS particles dissolved at 37°C but remained unaltered in Histidine at 5°C. Our results reinforce the need to track the fate of particles generated during drug product development upon exposure to physiologic conditions.

Protein Structural Denaturation Evaluated by MCR-ALS of Protein Microarray FTIR Spectra

The loss of native structure is common in proteins. Among others, aggregation is one structural modification of particular importance as it is a major concern for the efficiency and safety of biotherapeutic proteins. Yet, recognizing the structural features associated with intermolecular bridging in a high-throughput manner remains a challenge. We combined here the use of protein microarrays spotted at a density of ca 2500 samples per cm² and Fourier transform infrared (FTIR) imaging to analyze structural modifications in a set of 85 proteins characterized by widely different secondary structure contents, submitted or not to mild denaturing conditions. Multivariate curve resolution alternating least squares (MCR-ALS) was used to model a new spectral component appearing in the protein set subject to denaturing conditions. In the native protein set, 6 components were found to be sufficient to obtain good modeling of the spectra. Furthermore, their shape allowed them to be assigned to α-helix, β-sheet, and other structures. Their content in each protein was correlated with the known secondary structure, confirming these assignments. In the denatured proteins, a new component was necessary and modeled by MCR-ALS. This new component could be assigned to the intermolecular β-sheet, bridging protein molecules. MCR-ALS, therefore, unveiled a potential spectroscopic marker of protein aggregation and allowed a semiquantitative evaluation of its content. Insight into other structural rearrangements was also obtained.

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.

Particle Detection and Characterization for Biopharmaceutical Applications: Current Principles of Established and Alternative Techniques

Detection and characterization of particles in the visible and subvisible size range is critical in many fields of industrial research. Commercial particle analysis systems have proliferated over the last decade. Despite that growth, most systems continue to be based on well-established principles, and only a handful of new approaches have emerged. Identifying the right particle-analysis approach remains a challenge in research and development. The choice depends on each individual application, the sample, and the information the operator needs to obtain. In biopharmaceutical applications, particle analysis decisions must take product safety, product quality, and regulatory requirements into account. Biopharmaceutical process samples and formulations are dynamic, polydisperse, and very susceptible to chemical and physical degradation: improperly handled product can degrade, becoming inactive or in specific cases immunogenic. This article reviews current methods for detecting, analyzing, and characterizing particles in the biopharmaceutical context. The first part of our article represents an overview about current particle detection and characterization principles, which are in part the base of the emerging techniques. It is very important to understand the measuring principle, in order to be adequately able to judge the outcome of the used assay. Typical principles used in all application fields, including particle–light interactions, the Coulter principle, suspended microchannel resonators, sedimentation processes, and further separation principles, are summarized to illustrate their potentials and limitations considering the investigated samples. In the second part, we describe potential technical approaches for biopharmaceutical particle analysis as some promising techniques, such as nanoparticle tracking analysis (NTA), micro flow imaging (MFI), tunable resistive pulse sensing (TRPS), flow cytometry, and the space- and time-resolved extinction profile (STEP^®) technology.

Physicochemical and Antioxidative Characteristics of Potato Protein Isolate Hydrolysate

This study investigated the physicochemical characteristics of potato protein isolate hydrolysate (PPIH) and its antioxidant activity. Potato protein isolate (PPI) was hydrolyzed into PPIH by the proteases bromelain, Neutrase, and Flavourzyme. Compared with PPI, the resulting PPIH had a lower molecular weight (MW, from 103.5 to 422.7 Da) and smaller particle size (<50 nm), as well as a higher solubility rate (>70%) under acidic conditions (pH 3–6). PPIH presented good solubility (73%) across the tested pH range of 3–6. As the pH was increased, the zeta potential of PPIH decreased from −7.4 to −21.6. Using the 2,2′-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid (ABTS) radical-scavenging assay, we determined that the half-maximal effective concentration (EC₅₀) values of ascorbic acid, PPIH, and PPI were 0.01, 0.89, and >2.33 mg/mL, respectively. Furthermore, PPIH (50 μg/mL) protected C2C12 cells from H₂O₂ oxidation significantly better than PPI (10.5% higher viability rate; p < 0.01). These findings demonstrated the possible use of PPIH as an antioxidant in medical applications.

First-order nucleation and subsequent growth promote liquid-liquid phase separation of a model IgG1 mAb

Although protein aggregation is commonly encountered during the manufacturing and storage of bio-therapeutics, the actual aggregation mechanism remains unclear, and little has been reported about the protein aggregation kinetics from time zero under particular solution conditions. In this study, we used real-time dynamic light scattering (DLS) to continuously monitor the time-dependent evolution of the Z-average hydrodynamic radius of a model IgG1 (JM2) immediately after the JM2 solution was subjected to various low temperatures (0-4 °C). We observed that JM2 aggregated to form nuclei first, and then it subsequently grew to small liquid droplets via a two-step, first-order, reversible process without causing irreversible structural changes: a slow first step defined as the "nucleation" step, wherein nuclei formed slowly until reaching a transitional time point (t_onset), and a much faster second step initiated after t_onset and the nucleus size of the protein increased rapidly, which eventually caused liquid droplet formation and liquid-liquid phase separation (LLPS). The "nucleation" rate constant (K_nucleation) and particle growth rate constant (K_growth), as well as t_onset, were found to be temperature, pH and concentration dependent. The aggregation of JM2 could be universally described by these two-step first-order kinetics: under conditions where JM2 aggregated very slowly, the second step was not observed within the experimental time scale, while under conditions where JM2 aggregated very rapidly, the first step could not be recorded. We believe that these three parameters, K_nucleation, K_growth, and t_onset, can be used to quantify and compare the aggregation kinetics of JM2 under different solution and temperature conditions and, furthermore, serve as a theoretical base to account for the key characteristics of the aggregation kinetics of JM2 and other protein therapeutics under conditions of interest.

[Resonance light scattering spectroscopy can directly characterize protein solubility]

OBJECTIVE

To develop a fast, sensitive and cost-effective method based on resonance light scattering (RLS) for characterization of protein solubility to facilitate detection of changes in solubility of mutant proteins.

METHODS

We examined the response curve of RLS intensities to the protein concentrations in synchronous scanning mode. The curve intersection points were searched to predict the maximal concentrations of the protein in dispersion state, which defined the solubility of the protein in this given state. Bovine serum albumin (BSA, 0-50 g/L) was used as the model to investigate the influences of pH values (6.5, 7.0, and 7.4) and salt concentrations (0.05, 0.10, 0.15, and 0.20 mol/L) on the determined solubility. The solubility of glutathione S-transferase isoenzymes alpha (GSTA, 0-27.0 g/L) and Mμ (GSTM, 0-20.0 g/L) were estimated for comparison. The RLS-based method was used to determine the solubility of uricase (MGU, 0-0.4 g/L) to provide assistance in improving the solubility of its mutants.

RESULTS

We identified two intersection points in the RLS response curves of the tested proteins, among which the lower one represented an approximation of the maximal concentration (or the solubility of the protein) in single molecular dispersion, and the higher one the saturated concentration of the protein in multiple molecular aggregation. In HEPES buffer, the two intersection points of BSA (isoelectric point 4.6) both increased with the increase of pH (6.5-7.4), and their values were ~1.2 g/L and ~33 g/L at pH 7.4, respectively; the latter concentration approached the solubility of commercial BSA in the same buffer at the same pH. The addition of NaCl reduced the values of the two intersection points, and increasing salt ion concentration decreased the values of the lower intersection points. Further characterizations of GSTA and GSTM showed that the low concentration intersection points of the two proteins were ~0.7 g/L and ~0.8 g/L, and their high concentration intersection points were ~10 g/L and ~11 g/L, respectively, both lower than those of BSA, indicating the feasibility of the direct characterization of protein solubility by RLS. The two concentration intersection points of MGU were 0.24 g/L and 0.30 g/L, respectively, and the low concentration intersection point of its selected mutant was increased by 2 times.

CONCLUSIONS

RLS allows direct characterization of the solubility of macromolecular proteins. This method, which is simple and sensitive and needs only a small amount of proteins, has a unique advantage for rapid comparison of solubility of low-abundance protein mutants.

Characterization of Protein Aggregation Using Hydrogel-Encapsulated nIR Fluorescent Nanoparticle Sensors

The monitoring of biopharmaceutical critical quality attributes in-process, at both the process development and manufacturing stages, is necessary for the implementation of process analytical technology and quality-by-design principles. Among these attributes, it is important to monitor and control protein aggregation during the manufacturing of biological therapeutics to prevent adverse immunogenic responses and minimize negative impacts on drug deliverability. In this work, we explore hydrogel-encapsulated, label-free fluorescent nanosensors for the characterization of protein aggregation. A mathematical model is used to describe the diffusion and binding of a series of stressed pharmaceutical samples to such sensors, describing their dynamic response. We use mathematical modeling to map the influence of hydrogel properties on the separation performance, given the composition of UV-stressed IgG₁ samples. Using this modified model, the compositions of light-stressed IgG₁ samples were fit to experimental data and correlated with size-exclusion chromatography data. The results demonstrate the ability to detect the presence of high-molecular-weight protein species at a concentration as low as 1%. This work represents a significant step toward the development and deployment of rapid process analytical technologies for biopharmaceutical characterization.

The role of the medium in the effective-sphere interpretation of holographic particle characterization data

The in-line hologram of a micrometer-scale colloidal sphere can be analyzed with the Lorenz-Mie theory of light scattering to obtain precise measurements of the sphere's diameter and refractive index. The same technique also can be used to characterize porous and irregularly shaped colloidal particles provided that the extracted parameters are interpreted with effective-medium theory to represent the properties of an equivalent effective sphere. Here, we demonstrate that the effective-sphere model consistently accounts for changes in the refractive index of the medium as it fills the pores of porous particles and therefore yields quantitative information about such particles' structure and composition. In addition to the sample-averaged porosity, holographic perfusion porosimetry gauges the polydispersity of the porosity. We demonstrate these capabilities through measurements on mesoporous spheres, fractal protein aggregates and irregular nanoparticle agglomerates, all of which are noteworthy for their industrial significance.

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.

Detection and Sizing of Submicron Particles in Biologics With Interferometric Scattering Microscopy

We demonstrate the application of interferometric scattering microscopy (IFS) for characterizing submicron particles in stir-stressed monoclonal antibody. IFS uses a layered silicon sensor and modified optical microscope to rapidly visualize and determine the particle size distribution (PSD) of submicron particles based on their scattering intensity, which is directly proportional to particle mass. Limits for particle size and optimal solution concentration were established for IFS characterization of submicron particles. We critically compare IFS data with dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) and find IFS is superior to NTA and DLS for determining the realistic shape of the number-based PSD, whereas NTA and DLS provide superior information about absolute particle size. Together, IFS, NTA, and DLS provide complementary information on submicron particles and enable quantitative characterization of the PSD of submicron aggregates. Finally, we explore quantifying particle size with IFS by developing a calibration curve for particle scattering intensity based on correlative scanning electron microscopy imaging. We found that only a subset of isotropic-shaped particles followed the expected proportionality between IFS intensity and particle mass. Overall, this study demonstrates IFS is a simple approach for detecting and quantifying submicron aggregate PSD in protein-based therapeutics.

Separation, Characterization and Discriminant Analysis of Subvisible Particles in Biologics Formulations

Background:

The presence of subvisible particles (SVPs) in parenteral formulations of biologics is a major challenge in the development of therapeutic protein formulations. Distinction between proteinaceous and non-proteinaceous SVPs is vital in monitoring formulation stability.

Methods:

The current compendial method based on light obscuration (LO) has limitations in the analysis of translucent/low refractive index particles. A number of attempts have been made to develop an unambiguous method to characterize SVPs, albeit with limited success.

Results:

Herein, we describe a robust method that characterizes and distinguishes both potentially proteinaceous and non-proteinaceous SVPs in protein formulations using Microflow imaging (MFI) in conjunction with the MVAS software (MFI View Analysis Suite), developed by ProteinSimple. The method utilizes two Intensity parameters and a morphological filter that successfully distinguishes proteinaceous SVPs from non-proteinaceous SVPs and mixed aggregates.

Conclusion:

he MFI generated raw data of a protein sample is processed through Lumetics LINK software that applies an in-house developed filter to separate proteinaceous from the rest of the particulates.

Light-scattering detection within the difficult size range of protein particle measurement using flow cytometry

The phenomenon of protein aggregation is a prominent challenge that impacts biopharmaceutical development at every stage. It may have a number of deleterious effects on protein drugs, including the loss of efficacy, induction of immunogenicity, altered pharmacokinetics and reduced shelf life. At present, multiple methods are available for counting and sizing particles over a broad range of sizes. However, there remains a conundrum in the measurement of particles in the submicrometer range, from 100 nm to 2 μm. In this study, the capability of our new laboratory built FCM system to detect model polystyrene (PS) and silica (SiO₂) submicrometer microspheres was evaluated and benchmarked against flow field-flow fractionation (FFF). The FCM system showed its advantages on sensitivity, selectivity, reproducibility and speed. The laboratory-built FCM system can readily analyze model PS and SiO₂ microspheres down to 200 nm, covering much of the difficult range from 100 nm to 2 μm. Our data also showed that this machine was able to monitor the distribution of antibody aggregates ranged between 200 nm and 10 μm, suggesting its usability for characterizing protein aggregation in future.

Antibody adsorption on the surface of water studied by neutron reflection

Surface and interfacial adsorption of antibody molecules could cause structural unfolding and desorbed molecules could trigger solution aggregation, resulting in the compromise of physical stability. Although antibody adsorption is important and its relevance to many mechanistic processes has been proposed, few techniques can offer direct structural information about antibody adsorption under different conditions. The main aim of this study was to demonstrate the power of neutron reflection to unravel the amount and structural conformation of the adsorbed antibody layers at the air/water interface with and without surfactant, using a monoclonal antibody 'COE-3' as the model. By selecting isotopic contrasts from different ratios of H₂O and D₂O, the adsorbed amount, thickness and extent of the immersion of the antibody layer could be determined unambiguously. Upon mixing with the commonly-used non-ionic surfactant Polysorbate 80 (Tween 80), the surfactant in the mixed layer could be distinguished from antibody by using both hydrogenated and deuterated surfactants. Neutron reflection measurements from the co-adsorbed layers in null reflecting water revealed that, although the surfactant started to remove antibody from the surface at 1/100 critical micelle concentration (CMC) of the surfactant, complete removal was not achieved until above 1/10 CMC. The neutron study also revealed that antibody molecules retained their globular structure when either adsorbed by themselves or co-adsorbed with the surfactant under the conditions studied.

Evaluation of Microflow Digital Imaging Particle Analysis for Sub-Visible Particles Formulated with an Opaque Vaccine Adjuvant

Microflow digital imaging (MDI) has become a widely accepted method for assessing sub-visible particles in pharmaceutical formulations however, to date; no data have been presented on the utility of this methodology when formulations include opaque vaccine adjuvants. This study evaluates the ability of MDI to assess sub-visible particles under these conditions. A Fluid Imaging Technologies Inc. FlowCAM^® instrument was used to assess a number of sub-visible particle types in solution with increasing concentrations of AddaVax^™, a nanoscale squalene-based adjuvant. With the objective (10X) used and the limitations of the sensor resolution, the instrument was incapable of distinguishing between sub-visible particles and AddaVax^™ droplets at particle sizes less than 5 μm. The instrument was capable of imaging all particle types assessed (polystyrene beads, borosilicate glass, cellulose, polyethylene protein aggregate mimics, and lysozyme protein aggregates) at sizes greater than 5 μm in concentrations of AddaVax^™ up to 50% (vol:vol). Reduced edge gradients and a decrease in measured particle sizes were noted as adjuvant concentrations increased. No significant changes in particle counts were observed for polystyrene particle standards and lysozyme protein aggregates, however significant reductions in particle counts were observed for borosilicate (80% of original) and cellulose (92% of original) particles. This reduction in particle counts may be due to the opaque adjuvant masking translucent particles present in borosilicate and cellulose samples. Although the results suggest that the utility of MDI for assessing sub-visible particles in high concentrations of adjuvant may be highly dependent on particle morphology, we believe that further investigation of this methodology to assess sub-visible particles in challenging formulations is warranted.