Protein aggregation in therapeutic antibody products can potentially jeopardize product shelf life, efficacy, and patient safety. In order to prevent undesired protein aggregation, the colloidal stability of protein therapeutics is optimized over the course of drug product formulation screening. However, direct characterization of aggregation propensity over long-term stability studies during formulation development can be time-consuming and labor-intensive. Therefore, it is advantageous to expedite stability studies through initial assessment of underlying protein biophysical parameters that relate to aggregation propensity, and the application of said values within corresponding predictive models. In this study, 27 commercial monoclonal antibodies (mAbs) consisting of immunoglobulin 1, 2, and 4 subclasses with isoelectric point values between 7 and 9 were formulated into 5 different aqueous buffers and assessed for colloidal stability over 12 weeks at 45 Celsius (long-term forced degradation conditions). Additionally, protein-protein interaction was evaluated through measurement of biophysical parameters (i.e. diffusion interaction parameter (kD); Kirkwood Buff Integral (-G22)), and effective solution charge (z*). Biophysical parameters and solution charge were shown to statistically correlate with the aggregation propensity of all antibody-buffer combinations. It was observed that buffers with low pH/ionic strength (i.e. sodium acetate; L-histidine hydrochloride) resulted in higher (positive) values for kD, -G22, and z*; ultimately, this translated to reduced protein aggregation, which was attributed to predominant electrostatic repulsive forces between the solvated protein species. Finally, with the implementation of a predictive model using maximum entropy theory principles, the probability of protein aggregation could be estimated through measurement of kD, G22, and z* to facilitate preformulation and formulation development workflows and minimize user reliance on broad long-term stability studies.

Utilization of predictive models to assess therapeutic antibody aggregation

ACS Fall 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.