Prediction of Self-Association and Solution Behavior of Monoclonal Antibodies Using the QCM-D Metric of Loosely Interacting Layer

Abstract

Despite the increasing availability and success of monoclonal antibodies (mAb), early identification of candidate molecules with desirable developability attributes remains challenging due to self-association and poor solution behavior. Measuring these phenomena experimentally using the available methods is complicated in mAbs development. Quartz crystal microbalance with dissipation monitoring (QCM-D) detects a loosely interacting layer on top of the irreversibly adsorbed layer of molecules, providing information about the mAbs interaction. This work aimed to explore whether the characteristics of this layer can be used as a reliable self-association metric. QCM-D experiments showed a large frequency shift (Δf) associated with loosely interacting layers for omalizumab but a small or absent layer for tocilizumab. Accordingly, the viscosity of omalizumab increased exponentially at high concentrations compared to tocilizumab. Testing eight mAbs with different self-association behaviors revealed a strong rank order correlation between the mostly used metric of self-association, i.e., diffusion interaction parameter (kD-DLS), and Δf, indicating Δf’s potential for predicting mAb solution behavior. The study also highlighted the robustness of the metric to impurities and temperature variations compared to the sensitive kD-DLS. Overall, we demonstrate that the loosely interacting layer provides valuable information about mAb self-association, predicting the colloidal stability and solution behavior in therapeutic development.