Mesoscale Modeling of Monoclonal Antibody Aggregation: Computational Approach to Low-Viscosity Therapeutic Formulations

One long-standing challenge in subcutaneous delivery of therapeutic Monoclonal antibodies (mAbs) is the high concentration necessary for efficacy in one injection. This high concentration, along with colloidal-scale interactions between mAbs, can lead to the formation of large aggregates that drive up viscosity dramatically, making pressure-driven injection intractable. While many efforts are underway to link multi-scale experimental data with computational modeling—from ab initio to continuum behavior—critical gaps persist at the colloidal scale, which serves as a key bridge between molecular and continuum models. Our group advances this effort by developing colloidal-scale models to capture more accurate monoclonal antibody (mAb) aggregation. We employ colloidal-scale modeling of mAbs in a large-scale dynamic simulation to study aggregation and to predict and engineer bulk rheological properties of mAb solutions. Using LAMMPS, we model individual proteins as patchy colloids and link their assembly morphology and structure to interaction strength and surface patch patterns. We analyze microscopic structural changes during aggregation by tracking particle positions, coordination numbers, static structure factors, and bond dynamics, and correlate these with the resulting mesoscale organization and macroscopic properties such as viscosity. These predictions offer potential therapeutic strategies to steer assembled structures towards specific morphologies.