Mechanistic modeling based process development for monoclonal antibody monomer-aggregate separations in multimodal cation exchange chromatography

摘要

This study demonstrates how multimodal cation exchange chromatographic systems can be successfully employed to purify an IgG4 monomer from three distinct aggregate species. In addition, the steric mass action model is shown to be capable of facilitating the development of effective bind/elute processes for aggregate removal. A variety of multimodal anion and cation exchange resin materials and conditions were initially screened for both selectivity and recovery of the product. While the multimodal anion exchangers exhibited significant recovery issues, the Capto MMC and MMC ImpRes resin systems were observed to have good recoveries and some selectivity for these challenging separations under linear gradient conditions. Mechanistic modeling was then explored as a means to expedite the development of a bind/elute process for decreasing the aggregate content of this challenging monoclonal antibody mixture. The retention behavior of the monomer and the higher molecular weight species under different linear gradient conditions were used to estimate the SMA parameters of the proteins on both the Capto MMC and MMC ImpRes systems. A range of simulations were then carried out to determine an efficient bind/elute process for the removal of higher molecular weight species while also obtaining a good yield of the monomer in both resin systems. Finally, bind/elute experiments were carried out under the suggested simulation conditions for each resin system and were shown to be in good agreement with the theoretical predictions, with purities and yields of 99% and 78.6% for Capto MMC and 99.3% and 87.9% for Capto MMC ImpRes, respectively. The simple approach described in this paper presents a rapid and useful method for model-based process development of antibody monomer-aggregate separations with multimodal cation exchange chromatography. (C) 2019 Elsevier B.V. All rights reserved.