Viscoelastic characterization of high concentration antibody formulations using quartz crystal microbalance with dissipation monitoring.

With increasing protein concentrations, therapeutic protein formulations are increasingly demonstrating significant deviations from ideal dilute solution behavior due to protein-protein interactions. These interactions lead to unique biophysical challenges in the administration of biopharmaceuticals including high apparent viscosity and viscoelasticity as well as challenges in maintaining the physical stability of proteins in solution. Here, we describe a straightforward analytical method to calculate the complex modulus and viscosity of high concentration protein solutions from measurements made using quartz crystal microbalance with dissipation monitoring (QCM-D). Further, this methodology was used to investigate the dependence of the storage and loss moduli (G' and G'', respectively) of a humanized monoclonal antibody solution on solution pH. Unlike recent reports, the effect of protein deposition onto the surface of the quartz sensor crystal was measured and explicitly accounted for during analysis when determining the solution's complex modulus. It was found that the ratio G''/G' was significantly greater than unity for all solutions investigated, but demonstrated a distinct maximum at pH 5.5 indicating that the solution exhibited the greatest liquid-like behavior at this pH. In addition, measurements were made at higher frequencies, which were found to be more sensitive to the changes in pH than those made at lower frequencies. It was also found that the viscoelastic ratio was relatively insensitive to the frequency of measurement at lower pH, but showed greater dependence on frequency as pH increased. The characterization of the rheological properties of high concentration antibody solutions provides insight into protein-protein interactions, and the methodology presented here demonstrates a straightforward way to determine the viscoelastic properties using ultrasonic rheology without the drawbacks of numerical fitting.