Multiscale Modeling of Monoclonal Antibodies in High Concentration Formulations

ABSTRACT

Although monoclonal antibodies (mAbs) are some of the most profitable and promising pharmaceuticals for targeted therapies, physical instabilities at high concentrations including aggregation, high viscosity, and phase separation cause problems for their manufacture, delivery to patients, and long-term stability. In this work, we present a multiscale methodology which uses all-atom modeling and experimental second osmotic virial coefficients to develop coarse-grained models for Monte Carlo simulations of hundreds of mAbs with Angstrom-level resolution. In this multiscale modeling approach, the major assumption is that mAb domains are held fixed so that their atomistic interactions with implicit solvent can be precomputed and therefore increase simulation efficiency by a few orders of magnitude. Although domains within the mAbs are rigid, the coarse-grained model includes the flexibility of the hinge region, which is often neglected but here shown to play an important role at mAb concentrations up to 150 g/L. This approach is also amenable to modeling excipients, co-formulations, and surface interactions and is made available in the open-source code FEASST. Simulations were validated against experimental measurements and used to predict the physical stability of mAbs. These results highlight the potential for this multiscale approach to pre-screen pharmaceutical candidate mAbs in early-stage development to avoid high-concentration physical instabilities that can plague later-stage development.

BIOGRAPHY

Harold W. Hatch. After earning a B.S. in Chemical Engineering from Tulane University while working with Henry Ashbaugh, and a Ph.D. from Princeton University Department of Chemical and Biological Engineering under the mentorship of Pablo Debenedetti and Frank Stillinger, Harold received a 2013 NRC postdoctoral fellowship at the National Institute of Standards and Technology (NIST) advised by Vincent Shen. Harold has a permanent position at NIST with an interest in applying specialized molecular simulation techniques to study phase equilibrium, adsorption, self-assembly, and aggregation in biological materials, colloids, polymers, ionic liquids, and other fluids using the FEASST open-source Monte Carlo software.