High Throughput Prediction Approach for Monoclonal Antibody Aggregation at High Concentration
- 904 Downloads
Characterization of the monoclonal antibody aggregation process and identification of stability factors that could be used as indicators of aggregation propensity with an emphasis on a large number of samples and low protein material consumption.
Differential scanning calorimetry, dynamic light scattering and size exclusion chromatography were used as the main methodological approaches. Conformational stability, colloidal stability and aggregation kinetics were assessed for two different IgG monoclonal antibody (mAbs) subclasses. Aggregation was induced by exposing the mAbs to 55°C for 3 weeks. mAb samples were prepared in different formulations and concentrations from 1 mg/mL to 50 mg/mL.
High temperature stress of mAb samples revealed that monoclonal antibodies followed first order aggregation kinetics, which suggests that the rate-limiting step of monomer loss was unimolecular. Conformational stability of mAbs was estimated with denaturation temperature measurements. Colloidal stability was assessed with dynamic interaction parameter k D . The correlation between aggregation kinetics and colloidal and conformational stability factors was evaluated and the dynamic interaction parameter was found to be a promising predictor of aggregation propensity of monoclonal antibodies. The meaning of using an intermolecular interaction parameter for prediction of what is essentially a unimolecular process is also discussed.
This work estimates the significance of different predictors of aggregation propensity at high concentrations as a part of a high throughput, low resource screening method and is a contribution towards determining protein aggregation phenomena in actual systems used for the development and production of biopharmaceuticals.
Key wordsaggregation modelling aggregation predictors biopharmaceuticals intermolecular interactions protein aggregation
Dynamic light scattering
Differential scanning calorimetry
Size exclusion chromatography
- 5.Mossallatpour S, Ghahghaei A. The effect of Hoffmeister salts on the chaperoning action of β-casein in preventing aggregation of reduced α-Lactalbumin. Biom J. 2015;1:58–68.Google Scholar
- 8.George A, Wilson WW. Predicting protein crystallization from a dilute solution property. Acta Cryst. 1994;50:361–5.Google Scholar
- 9.G. W. H. Hochne, W. F. Hemminger and F. H. J., Differential Scanning Calorimetry, Berlin: Springer, 2003.Google Scholar
- 10.H. C. Hulst, Dynamic light scattering: with applications to chemistry, biology, and Physics, Dover Publications Inc., 1981.Google Scholar
- 11.J. B. Berne and R. Pecora, Light scattering by small particles, Dover Publications Inc, 2000.Google Scholar
- 13.Sun T, Chance RR, Graessley WW, Lohse DJ. A study of the separation principle in size exclusion chromatography. Macromolecules. 2004;37:4304–12.Google Scholar
- 16.Wilson WW, DeLucas LJ. Applications of the second virial coefficient: protein crystallization and solubility. Acta Cryst. 2014;F70:543–54.Google Scholar
- 19.Stranz M, Kastango ES. A review of pH and Osmolarity. Int J Pharm Compd. 2013;6(3):216–20.Google Scholar
- 31.B. J. Dear, J. J. Hung, T. M. Truskett and K. P. Johnston, Contrasting the influence of cationic amino acids on the viscosity and stability of a highly concentrated monoclonal antibody, Pharm Res, p. [Epub ahead of print], 2016.Google Scholar
- 32.Wang W. Advanced protein formulations. Protein Sci. 2015;24(7):1031–9.Google Scholar
- 35.R. Y. C. Huang, R. E. Iacob, S. R. Krystek, M. Jin, H. Wei, L. Tao, T. K. Das, A. A. Tymiak, J. R. Engen and G. Chen, Characterization of aggregation propensity of a human fc-fusion protein therapeutic by hidrogen/deuterium exchange mass spectrometry, J Am Soc Mass Spectrom, vol. Published online 15 August, 2016.Google Scholar
- 40.Arzenšek D, Kuzman D, Podgornik R. Colloidal interactions between monoclonal antibodies in aqueous solutions. J Colloid Interface Sci. 2012; doi: 10.1016/j.jcis.2012.06.055.