A multi-scale numerical approach to study monoclonal antibodies in solution

Viscosity of high concentration protein formulations of monoclonal antibodies of the IgG1 and IgG4 subclass – Prediction of viscosity through protein–protein interaction measurements

High-concentration protein formulations: How high is high?

Opalescence of an IgG2 monoclonal antibody solution as it relates to liquid–liquid phase separation

Ultrasonic rheology of a monoclonal antibody (IgG2) solution: Implications for physical stability of proteins in high concentration formulations

Comparison of Submicron Particle Counting Methods with a Heat Stressed Monoclonal Antibody: Effect of Electrolytes and Implications on Sample Preparation

Anti-C5a monoclonal antibody reduces cardiopulmonary bypass and cardioplegia-induced coronary endothelial dysfunction

Caffeine as a Viscosity Reducer for Highly Concentrated Monoclonal Antibody Solutions.

There is an increased interest from industry, academia and regulators for protein aggregates, subvisible and visible particles due to possible biological consequences, such as immunogenicity, altered bioactivity and modified pharmacokinetic profiles. Aggregates, subvisible and visible particles are important product instabilities, which might be present in every formulation of biotherapeutic products like monoclonal antibody solutions. Especially, the presence of subvisible particles in biotherapeutic products is currently a hot topic and it constantly gains more importance. The ultimate goal of this thesis is to develop tools and techniques in order to be able to characterize well-defined size fractions of proteinaceous subvisible particles with various desired oxidation profiles using in vivo transgenic mouse model. Up to now only a few articles were published and the available data from in vitro and in vivo experiments on aggregates and subvisible particles is often conflicting and fragmented, which impedes the development of sound conclusions. Moreover, complex mixtures of monomers, aggregates, particles and other degradants were used to draw conclusions. Only estimated values of protein particle density were used up to now in published studies although it is required to know the density of the measured particles in order to accurately calculate their dimensions and mass. The first aim of this thesis was therefore to develop a method to measure experimentally the protein particle density without extrapolation (Chapter 1). The density for commercially available standard beads (polystyrene, polymethacrylate and melamine) and a large bench of stressed proteinaceous samples was determined with the use of the resonant mass measurement instrument (RMM, Archimedes) and its ability to measure the buoyant mass of individual particles. Various fluids with increasing densities were implemented in order to determine the neutral buoyant mass where the particle density equals the fluid density. Chapter 2 reports the development of a process to isolate well-defined subvisible fractions using differential centrifugation for a model IgG1 antibody. The process to separate four fractions in the submicron and micrometer size range was developed and successfully optimized through the use of a design of experiments. The centrifugation technique was compared to an already published fractionation method using a preparative fluorescence-activated cell sorter. Efficiency, advantages and drawbacks for both methods were compared and discussed (Chapter 2). Oxidation profile of aggregates and subvisible particles seem to be an important attribute regarding induced biological consequences. That is why the next goal was to develop a method for selective oxidation of methionine and tryptophan residues in a model mAb in order to be able to delineate the effects and the contribution of individual protein modifications in the primary structure. This included a large set of experiments where different reaction conditions such as temperature of incubation, reaction time, type and concentration of oxidant (t-BHP, H2O2, AAPH) were evaluated in presence (or not) of a large excess of anti-oxidant (free amino acids) in order to protect the corresponding amino acid in a model antibody of the IgG1 subtype (Chapter 3). To complete the work, unfractionated materials and well-defined size fractions (with well-established oxidation profile) were prepared using the established tools (Chapter 1-3). Those samples were deeply characterized and injected subcutaneously into wild type and transgenic mice for immunization. Anti-drug antibody levels were measured following ELISA in order to assess the immunogenic potential of those preparations (Chapter 4).

Clearance of Murine Leukaemia Virus from Monoclonal Antibody Solution by a Hydrophilic PVDF Microporous Membrane Filter

Utilizing a hydrophobic primary container surface to reduce the formation of subvisible particles in monoclonal antibody solution caused by fluid shear

The long-term behavior and safety performance of hydraulic concrete structures are influenced by chemo-mechanical deterioration due to leaching and frost. The single-scale experimental investigations on the certain deterioration phenomenon of concrete structure submitted to leaching or frost have been performed. In this work, the multi-scale numerical simulation approach is introduced to analyze the deterioration phenomena due to leaching or/and frost in hydraulic concrete and the structural responses to the above deterioration phenomena. The three-dimensional (3D) multi-scale modeling and homogenization methods of hydraulic concrete submitted to leaching or/and frost are developed. The effect analysis of leaching or/and frost on the mechanical properties of hydraulic concrete is implemented. First, according to the multi-scale and multi-phase characteristics of hydraulic concrete as composite material, the scale separation standard of hydraulic concrete is given. The hydration model and random aggregate model are introduced to reconstruct the representative volume element model of hydraulic concrete with different scales, namely micro-scale (cement paste), meso-scale (mortar), macro-scale (concrete). The numerical homogenization method is presented to determine the mechanical properties of the hydraulic concrete. Second, the methods are developed to implement the 3D multi-scale simulation for random leaching process and thermo-mechanical coupling frost damage process of hydraulic concrete. Regarding seepage leaching as the leading role, a numerical method investigating the combined effect of leaching and frost on the mechanical properties of hydraulic concrete is proposed. Finally, the water-saturated hydraulic concrete is taken as an example. The deterioration phenomena due to leaching or/and frost in selected concrete are analyzed. The structural responses to the above deterioration phenomena are identified. It is indicated that the proposed multi-scale progressive analysis approach can capture the potential deterioration phenomena of hydraulic concrete. The variation mechanism of concrete structural behavior can be given a deeper insight. It can be seen that the nonlinear superimposed effect of leaching and frost can easily cause serious damage of water-saturated hydraulic concrete.

Using a quartz crystal microbalance with dissipation monitoring (QCM-D), the complex high-frequency viscosity,  = η' - iη'', of concentrated solutions of a monoclonal antibody (mAb) was studied with respect to its dependence on temperature, T, and concentration, c. Lysozyme and bovine serum albumin (BSA) served as reference materials. Viscoelasticity was found for the mAb solution, while the reference materials behaved like Newtonian liquids. The QCM-D probes the solution's dynamics on the time scale of a few tens of nanoseconds. The processes of relaxation accessed with the QCM-D are not amenable to standard viscometry. The inverse loss tangent at 15 MHz (equal to η''/η' at 15 MHz, quantifying the elastic contribution to the oscillatory stress) was between 0.1 and 0.5 for the concentrated mAb solutions. It decreased with increasing temperature and decreasing pH. Activation energies of viscous flow, Ea,η, were derived from the functions η'(T). Ea,η was found to be higher for the mAb solutions than for water. No such increase was found for the reference materials. This difference evidences protein-protein interactions (PPIs) between the mAb molecules, which do not exist in the same way for lysozyme and BSA. The excipients citrate and arginine did not noticeably affect the mAb's high-frequency viscosity as determined with the QCM-D.

Solutions of monoclonal antibodies (mAbs) can show increased viscosity at high concentration, which can be a disadvantage during protein purification, filling, and administration. The viscosity is determined by protein-protein-interactions, which are influenced by the antibody’s sequence as well as solution conditions, like pH, buffer type, or the presence of salts and other excipients. To predict viscosity, experimental parameters, like the diffusion interaction parameter (kD), or computational tools harnessing information derived from primary sequence, are often used, but a reliable predictive tool is still missing. We present a modeling approach employing artificial neural networks (ANNs) using experimental factors combined with simulation-derived parameters plus viscosity data from 27 highly concentrated (180 mg/mL) mAbs. These ANNs can be used to predict if mAbs exhibit problematic viscosity at distinct concentrations or to model viscosity-concentration-curves.

Under buffer SFM observation of immunospecies adsorbed on a cyano grafted silicon substrate

Understanding protein-protein interactions and formation of reversible oligomers (clusters) in concentrated monoclonal antibody (mAb) solutions is necessary for designing stable, low viscosity (η) concentrated formulations for processing and subcutaneous injection. Here we characterize the strength (K) of short-range anisotropic attractions (SRA) for 75-200 mg/mL mAb2 solutions at different pH and cosolute conditions by analyzing structure factors (Seff(q)) from small-angle X-ray scattering (SAXS) using coarse-grained molecular dynamics simulations. Best fit simulations additionally provide cluster size distributions, fractal dimensions, cluster occluded volume, and mAb coordination numbers. These equilibrium properties are utilized in a model to account for increases in viscosity caused by occluded volume in the clusters (packing effects) and dissipation of stress across lubricated fractal clusters. Seff(q) is highly sensitive to K at 75 mg/mL where mAbs can mutually align to form SRA contacts but becomes less sensitive at 200 mg/mL as steric repulsion due to packing becomes dominant. In contrast, η at 200 mg/mL is highly sensitive to SRA and the average cluster size from SAXS/simulation, which is observed to track the cluster relaxation time from shear thinning. By analyzing the distribution of sub-bead hot spots on the 3D mAb surface, we identify a strongly attractive hydrophobic patch in the complementarity determining region (CDR) at pH 4.5 that contributes to the high K and consequently large cluster sizes and high η. Adding NaCl screens electrostatic interactions and increases the impact of hydrophobic attraction on cluster size and raises η, whereas nonspecific binding of Arg attenuates all SRA, reducing η. The hydrophobic patch is absent at higher pH values, leading to smaller K, smaller clusters, and lower η. This work constitutes a first attempt to use SAXS and CG modeling to link both structural and rheological properties of concentrated mAb solutions to the energetics of specific hydrophobic patches on mAb surfaces. As such, our work opens an avenue for future research, including the possibility of designing coarse-grained models with physically meaningful interacting hot spots.