Developability assessment (DA) of a monoclonal antibody (mAb) drug candidate involves a battery of experiments to measure its safety, efficacy, and manufacturability. Experiments for measuring these require large amounts of material, which is often scarcely available at the discovery stages. A resource-sparing approach will therefore seek to reduce the number of experiments needed and utilize computation, whenever feasible. Here, we strived to identify a key experimental property that connects multiple biophysical attributes of an antibody solution and developed computational models to predict it. Standardized biophysical experiments were performed on high concentration platform formulations of 16 development stage mAbs along with molecular modeling and statistical data analyses. In this dataset, Diffusion interaction parameter (kD) was found to be a key biophysical property that connects conformational flexibility of an antibody molecule with its colloidal and rheological behaviors in a given formulation. kD showed statistically significant pairwise correlations (p-values &lt; 0.005) with the experimental measures of thermal stability, viscosity, isoelectric point, and solubility of the antibody molecules. We hypothesized that these macroscopic correlations originate from molecular-level sequence-structural relationships of the mAbs. Consistently, kD also showed statistically significant pairwise correlations (p-values &lt; 0.005) with pI, net charge, charge on the Fv region, and zeta potential values calculated using full-length homology models of the mAbs in this dataset. The correlations of kD with measured biophysical properties and computed molecular descriptors were further refined by multivariate analyses and equations were developed to predict it. These empirical equations can potentially be utilized to enable rapid resource-sparing DAs of biologic drug candidates. This analysis also deepens our understanding of antibody solutions by suggesting that colloidal descriptions, which assume antibody molecules as rigid, may be inadequate to fully explain their solution behaviors, because thermal stability is an important contributor towards solute: solute and solute: solvent interactions.

<i>In silico</i> prediction of diffusion interaction parameter (kD), a key determinant of antibody solution behaviors

255th National Meeting (2018)

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

In silico prediction of diffusion interaction parameter (kD), a key determinant of antibody solution behaviors