mAbs (Jan 2020)

Optimization and kinetic modeling of interchain disulfide bond reoxidation of monoclonal antibodies in bioprocesses

  • Peifeng Tang,
  • Zhijun Tan,
  • Vivekh Ehamparanathan,
  • Tingwei Ren,
  • Laurel Hoffman,
  • Cheng Du,
  • Yuanli Song,
  • Li Tao,
  • Angela Lewandowski,
  • Sanchayita Ghose,
  • Zheng Jian Li,
  • Shijie Liu

DOI
https://doi.org/10.1080/19420862.2020.1829336
Journal volume & issue
Vol. 12, no. 1

Abstract

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Disulfide bonds play a crucial role in folding and structural stabilization of monoclonal antibodies (mAbs). Disulfide bond reduction may happen during the mAb manufacturing process, resulting in low molecular weight species and possible failure to meet product specifications. Although many mitigation strategies have been developed to prevent disulfide reduction, to the best of our knowledge, reforming disulfide bonds from the reduced antibody in manufacturing has not previously been reported. Here, we explored a novel rescue strategy in the downstream process to repair the broken disulfide bonds via in-vitro redox reactions on Protein A resin. Redox conditions including redox pair (cysteine/cystine ratio), pH, temperature, and reaction time were examined to achieve high antibody purity and a high reaction rate. Under the optimal redox condition, >90% reduced antibody could be reoxidized to form an intact antibody on Protein A resin in an hour. In addition, this study showed high flexibility on the range of the intact mAb fraction in the initial reduced mAb sample (the lower limit of intact mAb faction could be 14% based on the data reported in this study). Furthermore, a kinetic model based on elementary oxidative reactions was constructed to help optimize the reoxidation conditions and to predict product purity. Together, the deep understanding of interchain disulfide bond reoxidation, combined with the predictive kinetic model, provided a good foundation to implement a rescue strategy to generate high-purity antibodies with substantial cost savings in manufacturing processes.

Keywords