Monoclonal Antibody Coformulations Reveal Three Interaction Patterns Governing Stability

Abstract Coformulated monoclonal antibodies (mAbs) offer a promising next-generation therapeutic strategy by combining multiple antibodies in a single drug product to enhance efficacy and improve patient compliance. However, ensuring the quality and stability of individual components in combination remains a key challenge. Here, we systematically characterized ten IgG1 mAbs (eight low-viscosity and two high-viscosity mAbs at 150 mg/mL) and all 45 possible 1:1 binary coformulations. Viscosity measurements revealed three distinct cross-interaction patterns: (1) minimal cross-interaction, where coformulation viscosity fell between those of the parental mAbs; (2) attractive cross-interaction, characterized by viscosity above both parental mAbs; and (3) repulsive cross-interaction, characterized by viscosity below both parental mAbs. Among the two high-viscosity mAbs, one exhibited reduced viscosity when coformulated with low-viscosity mAbs, whereas the other exhibited increased viscosity. Diffusion interaction parameter (kD) measurements showed partial correspondence with the observed interaction patterns, although kD did not consistently align with the viscosity trends across all coformulation pairs. In parallel, conformational stability was assessed using thermal unfolding parameters, including onset temperature (Tonset) and the first unfolding transition temperature (Tm1). Most coformulations exhibited thermal unfolding parameters intermediate between those of their parental mAbs, often shifting toward the less conformationally stable parent, indicating that conformational stability was generally retained following coformulation. This study represents one of the most comprehensive investigations of antibody coformulations to date and, to our knowledge, is the first to report repulsive interactions, particularly in the context of high-concentration viscosity. These findings highlight fundamental protein−protein interaction patterns that govern antibody coformulations, expand the knowledge base for the development of stable next-generation antibody combination therapies, and provide a rich experimental dataset to guide future computational modeling of mAb−mAb coformulation behavior.