Assessment of self-association of monoclonal antibody molecules by analysis of the protein layer detected at the proximity of a solid surface

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Despite the increasing availability of monoclonal antibody (mAb) drugs and their proven success in treatment of rheumatoid arthritis, multiple sclerosis, asthma, atopic dermatitis, and many other diseases, the early identification of the protein candidate molecules with desirable manufacturability, stability and delivery attributes remains a big challenge. Self-association and poor solution behavior, manifested in high viscosity/opalescence at relevant concentrations or in phase separation and stability issues, are major limiting factors in development of mAb therapeutics. Solution behavior is believed to be governed by protein self-association, however, measurement of these associations experimentally and prediction of the solution behavior are challenging using the current methods. The objective in this application is to develop a versatile method that directly measures the protein self-association under relevant conditions and is predictive of the important attributes in drug development and formulation. This proposal is significant because it increases the potential to identify the candidates with weak solution behavior and susceptibility to aggregation which, in turn, can lead to enhanced efficiency in development of much needed mAb therapeutics. In addition, having reliable predictive methods at the early stages of drug discovery and development would eliminate the early, unwarranted removal of therapeutically promising mAb drug candidates from development pipelines.