A comparison of biophysical characterization techniques in predicting monoclonal antibody stability

Abstract

With the rapid growth of biopharmaceutical product development, knowledge of therapeutic protein stability has become increasingly important. We evaluated assays that measure solution-mediated interactions and key molecular characteristics of 9 formulated monoclonal antibody (mAb) therapeutics, to predict their stability behavior. Colloidal interactions, self-association propensity and conformational stability were measured using effective surface charge via zeta potential, diffusion interaction parameter (k D ) and differential scanning calorimetry (DSC), respectively. The molecular features of all 9 mAbs were compared to their stability at accelerated (25 C and 40 C) and long-term storage conditions (2-8 C) as measured by size exclusion chromatography. At accelerated storage conditions, the majority of the mAbs in this study degraded via fragmentation rather than aggregation. Our results show that colloidal stability, self-association propensity and conformational characteristics (exposed tryptophan) provide reasonable prediction of accelerated stability, with limited predictive value at 2-8 C stability. While no correlations to stability behavior were observed with onset-of-melting temperatures or domain unfolding temperatures, by DSC, melting of the Fab domain with the C H 2 domain suggests lower stability at stressed conditions. The relevance of identifying appropriate biophysical assays based on the primary degradation pathways is discussed.

Effect of Polysorbate 20 and Polysorbate 80 on the Higher-Order Structure of a Monoclonal Antibody and Its Fab and Fc Fragments Probed Using 2D Nuclear Magnetic Resonance Spectroscopy

“…These results imply that despite exhibiting lower T onset for conformational changes at pH 5.8, Fab aggregates less at pH 5.8 compared to pH 8.0, indicating that the colloidal stability is playing a major role in Fab aggregation. These results are quite consistent with recent studies which indicated that the colloidal stability can account for the lack of a clear relationship between the conformational stability and aggregation of mAbs 49,50 .…”

“…Similar results have been observed in two other published studies. In the first study on the aggregation behavior of ten different IgG1 antibodies 49 , there was no absolute trend between the conformational stability and aggregation of the IgG1 molecules, implying that colloidal stability plays a major role in IgG1 aggregation. In the second study 50 , changing the solution pH from 6.5 to 4.5 reduced the thermal stability of IgG1; however, less protein aggregation was observed at pH 4.5, because of the increased colloidal stability of the protein.…”

Considerations for the Design of Antibody-Based Therapeutics

“…300 Several methods exist for assessing the conformational stability and aggregation propensity of drug candidates, as well as related properties such as colloidal stability and self-association. 132,312,313 Stress tests attempt to quickly predict the long-term stability of proteins by exposing them to conditions that allow for exploration of nonnative conformations. In principle, aggregation can be accelerated by increasing the free energy of the native state, decreasing the free energy of the unfolded state, or adding energy to the system to overcome kinetic barriers between states.…”

“…Recently, the ability of thermal unfolding assays to predict physical stability has been questioned, with properties such as self-association, colloidal stability, and chemical denaturation stability being proposed as superior predictive parameters than melting temperature. 313,315 Tryptophan fluorescence is another property potentially correlated to total monomer loss (fragmentation plus aggregation) rather than aggregation alone. 313 The presence of aggregationprone regions may also be predicted using sequence-based computational modeling approaches.…”

“…313,315 Tryptophan fluorescence is another property potentially correlated to total monomer loss (fragmentation plus aggregation) rather than aggregation alone. 313 The presence of aggregationprone regions may also be predicted using sequence-based computational modeling approaches. 316 Although in silico methods may be helpful in guiding lead selection, they are unlikely to replace in vitro stability tests that experimentally evaluate the presence of problematic aggregation pathways.…”