Optimization of a platform process operating space for a monoclonal antibody susceptible to reversible and irreversible aggregation using a solution stability screening approach

Platform manufacturing processes are widely adopted to simplify and standardize the development and manufacturing of monoclonal antibodies (mAbs). However, there are mAbs that do not conform to a platform design due to instability or other protein properties leading to a negative impact on product quality or process performance (non-platform mAb). Non-platform mAbs typically require prolonged development times and significant deviations from the platform process to address these issues due to the need to sequentially optimize individual process steps. In this study, we describe an IgG2 mAb (mAb A) that is susceptible to aggregation and reversible self-association (RSA) under platform conditions. In lieu of a sequential optimization approach, we evaluated the solution stability of mAb A across the platform operating space (solution stability screen). This screening design was used to identify interacting parameters that affected the non-platform mAb stability. A subsequent response surface design was found to predict an acceptable operating space that minimized aggregate formation and RSA across the entire process. This information guided the selection of optimal parameters best suited to avoid destabilizing conditions for each process step. Substantial time savings was achieved by focusing development around these factors including protein concentration, buffer pH, salt concentration, and excipient type. In addition, this work enabled the optimization of a cation exchange chromatography step that removed aggregate without yield losses due to the presence of reversible aggregation. The final optimized process derived from this study resulted in an increase in yield of (3) over tilde0% over the original process while maintaining the same level of aggregate clearance to match product quality. Solution stability screening is readily adapted to high throughput technologies to minimize material requirements and accelerate analytical data availability. Implementation of high throughput approaches will further expedite process development and enable enhanced selection of candidate drugs by including process development objectives. (C) 2019 The Authors. Published by Elsevier B.V.