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.

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.

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.

Modulated Scanning Fluorimetry Can Quickly Assess Thermal Protein Unfolding Reversibility in Microvolume Samples.

Determining the temperature at which the thermal unfolding of a protein starts becoming irreversible is relevant for many areas of protein research. Until now, published methods cannot determine, within a reasonable time frame and with moderate sample consumption, the exposure temperature that starts causing irreversible protein unfolding. We present modulated scanning fluorimetry (MSF) and share a software (MSF Analyzer), which can be used to derive nonreversibility curves of thermal protein unfolding from a series of incremental temperature cycles performed on only 10 µL samples, consuming as low as a few micrograms of protein. Further processing of the data can yield the onset temperature that starts causing nonreversible protein unfolding. The MSF method is based on the hardware of the already existing nanoDSF technology and can be applied to dozens of samples simultaneously. Here, we use MSF to study how solution pH affects the reversibility of thermal protein unfolding of several model proteins to show that the nonreversibility onset temperature (Tnr) is a unique biophysical parameter, providing orthogonal information from thermal protein denaturation data and insights into the validity of thermal unfolding analysis in the context of equilibrium thermodynamics. We also show that MSF can be used to study enzyme stability after exposure to high temperatures. Besides, we demonstrate that protein thermal unfolding and nonreversibility can be affected in different ways upon modifications like PEG-ylation or labeling with fluorescent dyes. Finally, we show that MSF can be used to study the effect of various protein interactions on thermal protein unfolding reversibility. With the diverse examples in this work, we reveal how MSF can provide orthogonal information from thermal denaturation experiments that can bring benefits to various areas of protein research. The MSF Analyzer software is available at https://github.com/CoriolisPharmaResearch/MSFAnalyser.

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.

Challenges in the analysis of pharmaceutical lentiviral vector products by orthogonal and complementary physical (nano)particle characterization techniques.

Lentiviral vectors (LVVs) are used as a starting material to generate chimeric antigen receptor (CAR) T cells. Therefore, LVVs need to be carefully analyzed to ensure safety, quality, and potency of the final product. We evaluated orthogonal and complementary analytical techniques for their suitability to characterize particulate matter (impurities and LVVs) in pharmaceutical LVV materials at development stage derived from suspension and adherent manufacturing processes. Microfluidic resistive pulse sensing (MRPS) with additional manual data fitting enabled the assessment of mode diameters for particles in the expected LVV size range in material from adherent production. LVV material from a suspension process, however, contained substantial amounts of particulate impurities which blocked MRPS cartridges. Sedimentation-velocity analytical ultracentrifugation (SV-AUC) resolved the LVV peak in material from adherent production well, whereas in more polydisperse samples from suspension production, presence of particulate impurities masked a potential signal assignable to LVVs. In interferometric light microscopy (ILM) and nanoparticle tracking analysis (NTA), lower size detection limits close to âˆ¼ 70 nm resulted in an apparent peak in particle size distributions at the expected size for LVVs emphasizing the need to interpret these data with care. Interpretation of data from dynamic light scattering (DLS) was limited by insufficient size resolution and sample polydispersity. In conclusion, the analysis of LVV products manufactured at pharmaceutical scale with current state-of-the-art physical (nano)particle characterization techniques was challenging due to the presence of particulate impurities of heterogeneous size. Among the evaluated techniques, MRPS and SV-AUC were most promising yielding acceptable results at least for material from adherent production.

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.

Prediction of Unwanted Crystallization of Freeze-Dried Protein Formulations Using α-Relaxation Measurements.

There is a lack of methods to predict the isothermal crystallization behavior of amorphous freeze-dried formulations stored below the glass transition temperature. This study applies isothermal microcalorimetry to predict long-term crystallization during product storage time. The relaxation curve of a fresh sample recorded within 12 h after lyophilization is correlated with the long-term crystallization time at the same temperature. Storage conditions of 25 °C and 40 °C are examined and five model formulations containing either sucrose or trehalose with different concentrations of an IgG1 antibody are investigated. The amorphous formulations were created by different freeze-drying processes only differing in their freezing step (random nucleation; additional annealing step of 1.5 h and 3 h, controlled nucleation; quench cooling). Samples that crystallized during the study time of 12 months showed a promising correlation between their relaxation time and crystallization behavior upon storage. Furthermore, the study shows that polysorbate 20 strongly accelerates crystallization of sucrose and that the freezing step itself has a strong impact on the relaxation phenomena that is not levelled out by primary and secondary drying.

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 τß [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 τß 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 τß 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.

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.

SV-AUC as a stability-indicating method for the characterization of mRNA-LNPs.

During the SARS-CoV2 pandemic mRNA vaccines in the form of lipid nanoparticles (LNPs) containing the mRNA, have set the stage for a new area of vaccines. Analytical methods to quantify changes in size and structure of LNPs are crucial, as changes in these parameters could have implications for potency. We investigated the application of sedimentation velocity analytical ultracentrifugation (SV-AUC) as quantitative stability-indicating method to detect structural changes of mRNA-LNP vaccines upon relevant stress factors (freeze/thaw, heat and mechanical stress), in comparison to qualitative dynamic light scattering (DLS) analysis. DLS was capable to qualitatively determine size and homogeneity of mRNA-LNPs with sufficient precision. Stress factors, in particular freeze/thaw and mechanical stress, led to increased particle size and content of larger species in DLS and SV-AUC. Changes upon heat stress at 50 °C were only detected as increased flotation rates by SV-AUC. In addition, SV-AUC was able to observe changes in particle density, which cannot be detected by DLS. In conclusion, SV-AUC can be used as a highly valuable quantitative stability-indicating method for characterization of LNPs.

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.

Genome length determination in adeno-associated virus vectors with mass photometry.

Recombinant adeno-associated viruses (rAAVs) are attractive therapeutic viral vectors for gene delivery. To ensure the efficacy and safety of rAAV-based therapies, comprehensive characterization of the adeno-associated virus (AAV) capsids is essential. Mass photometry (MP) provides the advantage of short analysis times, low sample consumption, and high accuracy of molecular mass determination. Despite having just recently emerged, MP has already been used to characterize AAV genome content and quantify filled/empty capsid ratios. In this study, we explored three approaches for the application of MP to assess genome length in AAVs. In approach 1, genome length in intact AAVs was approximated with good precision (coefficient of variation [%CV] < 2.6%) and accuracy (±5%) by using a straightforward protein-based calibration. In approach 2, genome length was determined even more accurately (±1%, %CV < 2.9%) considering calibration with a set of additional AAVs of different genome length. In approach 3, genome length was assessed after genome release from the capsid by heating in 1% sodium dodecyl sulfate followed by surfactant removal with precision of %CV < 0.7% and accuracy of ±5%. In conclusion, the three developed MP-based approaches are fast, precise, and accurate methods for genome length determination in AAVs, differing in their calibration materials and efforts.

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.

Systematic Studies on Stabilization of AAV Vector Formulations by Lyophilization.

Adeno-associated virus (AAV) vectors have evolved as one of the most promising delivery systems for gene therapy. The current standard for AAV vector storage is deep-freezing below -60 °C. While this allows for long-term vector storage without loss of activity, it is inconvenient and involves high costs and logistical challenges. Therefore, there is a need for AAV formulations, such as freeze-dried formulations, that allow for long-term storage at 2-8 °C. A major challenge in developing a lyophilization process for complex biological structures like an AAV vector is to minimize the stress on the capsid during the lyophilization cycle. Here, we evaluated different conditions for freeze-drying of AAV8 vectors and found that undesirable instability can be significantly reduced if secondary drying is performed at lower temperatures, kept as short as possible, and the residual moisture is kept between 1.5 and 2%. In a next step, we explored formulations with different salt concentration or excipient compositions and found that a combination of 10 mM phosphate buffer, 5.67% (150 mM) trehalose, 5% hydroxyectoine and 0.1% poloxamer with a residual moisture of approx. 1.5% provided stable long-term storage at 2-8 °C and for at least 4 weeks at 25 °C. These results pave the way for future optimizations of freeze-drying processes for AAV vector-based gene therapy products.

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.