Influence of macromolecular precipitants on phase behavior of monoclonal antibodies

Spectroscopic insights into multi-phase protein crystallization in complex lysate using Raman spectroscopy and a particle-free bypass

Protein crystallization as opposed to well-established chromatography processes has the benefits to reduce production costs while reaching a comparable high purity. However, monitoring crystallization processes remains a challenge as the produced crystals may interfere with analytical measurements. Especially for capturing proteins from complex feedstock containing various impurities, establishing reliable process analytical technology (PAT) to monitor protein crystallization processes can be complicated. In heterogeneous mixtures, important product characteristics can be found by multivariate analysis and chemometrics, thus contributing to the development of a thorough process understanding. In this project, an analytical set-up is established combining offline analytics, on-line ultraviolet visible light (UV/Vis) spectroscopy, and in-line Raman spectroscopy to monitor a stirred-batch crystallization process with multiple phases and species being present. As an example process, the enzyme Lactobacillus kefir alcohol dehydrogenase (LkADH) was crystallized from clarified Escherichia coli (E. coli) lysate on a 300 mL scale in five distinct experiments, with the experimental conditions changing in terms of the initial lysate solution preparation method and precipitant concentration. Since UV/Vis spectroscopy is sensitive to particles, a cross-flow filtration (cross-flow filtration)-based bypass enabled the on-line analysis of the liquid phase providing information on the lysate composition regarding the nucleic acid to protein ratio. A principal component analysis (PCA) of in situ Raman spectra supported the identification of spectra and wavenumber ranges associated with productspecific information and revealed that the experiments followed a comparable, spectral trend when crystals were present. Based on preprocessed Raman spectra, a partial least squares (PLS) regression model was optimized to monitor the target molecule concentration in real-time. The off-line sample analysis provided information on the crystal number and crystal geometry by automated image analysis as well as the concentration of LkADH and host cell proteins (HCPs) In spite of a complex lysate suspension containing scattering crystals and various impurities, it was possible to monitor the target molecule concentration in a heterogeneous, multi-phase process using spectroscopic methods. With the presented analytical set-up of off-line, particle-sensitive on-line, and in-line analyzers, a crystallization capture process can be characterized better in terms of the geometry, yield, and purity of the crystals.

Human endoglin-CD3 bispecific T cell engager antibody induces anti-tumor effect in vivo

Rationale: Endoglin, also known as CD105, is a homo-dimeric membrane glycoprotein required for angiogenesis and serves as a marker for cancer vasculature. In this study, we constructed a bispecific T-cell engager (BiTE) antibody that targets human endoglin and CD3 (hEND-CD3/BiTE). We examined BiTE binding to endoglin-expressing cells and its effects on the cytolytic activity of T cells and cancer development.

Methods: The in vitro effects of hEND-CD3/BiTE, including binding to target cells, T-cell activation, proliferation, and cytotoxicity, were examined in endoglin-expressing 293T cells, human umbilical vascular endothelial cells, tumor-derived endothelial cells, and CD3⁺ T cells. An in vivo xenograft tumor model was established using A549 human lung cancer cells. The therapeutic efficacy of hEND-CD3/BiTE was assessed by monitoring tumor growth, angiogenesis, and mouse survival.

Results: hEND-CD3/BiTE specifically bound to endoglin-expressing cells and CD3⁺ T cells in vitro and stimulated T-cell activation, proliferation, and Th1 cytokine secretion, and promoted T-cell-mediated cytolysis of endoglin-expressing cells. The hEND-CD3/BiTE in vivo caused minimal toxicity to major organs, reduced tumor neoangiogenesis, inhibited tumor growth, and significantly improved mouse survival.

Conclusions: Our study demonstrated the therapeutic potential of hEND-CD3/BiTE and provided a novel approach to clinical cancer treatment.

On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS)

The crystallization of Anti-CD20, a full-length monoclonal antibody, has been studied in the PEG400/Na2SO4/Water system near Liquid-Liquid Phase Separation (LLPS) conditions by both sitting-drop vapour diffusion and batch methods. In order to understand the Anti-CD20 crystallization propensity in the solvent system of different compositions, we investigated some measurable parameters, normally used to assess protein conformational and colloidal stability in solution, with the aim to understand the aggregation mechanism of this complex biomacromolecule. We propose that under crystallization conditions a minor population of specifically aggregated protein molecules are present. While this minor species hardly contributes to the measured average solution behaviour, it induces and promotes crystal formation. The existence of this minor species is the result of the LLPS occurring concomitantly under crystallization conditions.

Time-Dependent Multi-Light-Source Image Classification Combined With Automated Multidimensional Protein Phase Diagram Construction for Protein Phase Behavior Analysis

Image-based protein phase diagram analysis is key for understanding and exploiting protein phase behavior in the biopharmaceutical field. However, required data analysis has become a notorious time-consuming task since high-throughput screening approaches were implemented. A variety of computational tools have been developed to support analysis, but these tools primarily use end point visible light images. This study investigates the combined effect of end point and time-dependent image features obtained from cross-polarized and ultraviolet light features, supplementary to visible light, on protein phase diagram image classification. In addition, external validation was performed to evaluate the classification algorithm's applicability to support protein phase diagram scoring. The predicted protein phase behavior classes were subsequently used to automatically construct multidimensional protein phase diagrams to prevent image information loss without complicating the used image classification algorithm. Combining end point and time-dependent features from 3 light sources resulted in a balanced accuracy of 86.4 ± 4.3%, which is comparable to or better than more complex classifiers reported in literature. External validation resulted in a correct formulation classification rate of 91.7%. Subsequent automated construction of the multidimensional protein phase diagrams, using predicted classes, allowed visualization of details such as crystallization rate and protein phase behavior type coexistence.

Optimization of Vapor Diffusion Conditions for Anti-CD20 Crystallization and Scale-Up to Meso Batch

The crystal form is one of the preferred formulations for biotherapeutics, especially thanks to its ability to ensure high stability of the active ingredient. In addition, crystallization allows the recovery of a very pure drug, thus facilitating the manufacturing process. However, in many cases, crystallization is not trivial, and other formulations, such as the concentrate solution, represent the only choice. This is the case of anti-cluster of differentiation 20 (anti-CD20), which is one of the most sold antibodies for therapeutic uses. Here, we propose a set of optimized crystallization conditions for producing anti-CD20 needle-shaped crystals within 24 h in a very reproducible manner with high yield. High crystallization yield was obtained with high reproducibility using both hanging drop vapor diffusion and meso batch, which is a major step forward toward further scaling up the crystallization of anti-CD20. The influence of anti-CD20 storage conditions and the effect of different ions on the crystallization processes were also assessed. The crystal quality and the high yield allowed the first crystallographic investigation on anti-CD20, which positively confirmed the presence of the antibody in the crystals.

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

The colloidal stability of a protein solution during downstream processing, formulation, and storage is a key issue for the biopharmaceutical production process. Thus, knowledge about colloidal solution characteristics, such as the tendency to form aggregates or high viscosity, at various processing conditions is of interest. This work correlates changes in the apparent diffusion coefficient as a parameter of protein interactions with observed protein aggregation and dynamic viscosity of the respective protein samples. For this purpose, the diffusion coefficient, the protein phase behavior, and the dynamic viscosity in various systems containing the model proteins α-lactalbumin, lysozyme, and glucose oxidase were studied. Each of these experiments revealed a wide range of variations in protein interactions depending on protein type, protein concentration, pH, and the NaCl concentration. All these variations showed to be mirrored by changes in the apparent diffusion coefficient in the respective samples. Whereas stable samples with relatively low viscosity showed an almost linear dependence, the deviation from the concentration-dependent linearity indicated both an increase in the sample viscosity and probability of protein aggregation. This deviation of the apparent diffusion coefficient from concentration-dependent linearity was independent of protein type and solution properties for this study. Thus, this single parameter shows the potential to act as a prognostic tool for colloidal stability of protein solutions.

From osmotic second virial coefficient (B22 ) to phase behavior of a monoclonal antibody

Antibodies are complex macromolecules and their phase behavior as well as interactions within different solvents and precipitants are still not understood. To shed some light into the processes on a molecular dimension, the occurring self-interactions between antibody molecules were analyzed by means of the osmotic second virial coefficient (B22 ). The determined B22 follows qualitatively the phenomenological Hofmeister series describing the aggregation probability of antibodies for the various solvent compositions. However, a direct correlation between crystallization probability and B22 in form of a crystallization slot does not seem to be feasible for antibodies since the phase behavior is strongly dependent on their anisotropy. Kinetic parameters have to be taken into account due to the molecular size and complexity of the molecules. This is confirmed by a comparison of experimental data with a theoretical phase diagram. On the other hand the solubility is thermodynamically driven and therefore the B22 could be used to establish a universal solubility line for the monoclonal antibody mAb04c and different solvent compositions by using thermodynamic models.