Predicting diafiltration solution compositions for final ultrafiltration/diafiltration steps of monoclonal antibodies
Article first published online: 19 FEB 2011
Copyright © 2011 Wiley Periodicals, Inc.
Biotechnology and Bioengineering
Volume 108, Issue 6, pages 1338–1346, June 2011
How to Cite
Teeters, M., Bezila, D., Benner, T., Alfonso, P. and Alred, P. (2011), Predicting diafiltration solution compositions for final ultrafiltration/diafiltration steps of monoclonal antibodies. Biotechnol. Bioeng., 108: 1338–1346. doi: 10.1002/bit.23067
- Issue published online: 12 APR 2011
- Article first published online: 19 FEB 2011
- Accepted manuscript online: 15 FEB 2011 12:00AM EST
- Manuscript Accepted: 21 JAN 2011
- Manuscript Revised: 2 JAN 2011
- Manuscript Received: 5 NOV 2010
- monoclonal antibody;
Many liquid formulations for monoclonal antibodies (MAbs) require the final ultrafiltration/diafiltration step to operate at high protein concentrations, often at or above 100 g/L. When operating under these conditions, the excipient concentrations and pH of the final diafiltered retentate are frequently not equal to the corresponding excipient concentrations and pH of the diafiltration buffer. A model based on the Poisson–Boltzmann equation combined with volume exclusion was extended to predict both pH and excipient concentrations in the retentate for a given diafiltration buffer. This model was successfully applied to identify the diafiltration buffer composition required to achieve the desired pre-formulated bulk drug substance (retentate) conditions. Predictions were in good agreement with the experimental results, and reduced the number of experimental iterations needed to define the diafiltration buffer composition. Additionally, the predictive model was applied in a sensitivity analysis across ranges of protein charge, protein concentration, and diafiltration buffer pH and excipient concentration. This sensitivity analysis can facilitate the design of experiments for robustness testing, and allow for generalized predictions across classes of molecules such as MAbs. Biotechnol. Bioeng. 2011; 108:1338–1346. © 2011 Wiley Periodicals, Inc.