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Assessment of Antibody Self-Interaction by Bio-Layer-Interferometry as a Tool for Early Stage Formulation Development

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Abstract

Purpose

To speed up the drug development process in the biopharmaceutical industry, high throughput methods are indispensable for assessing drug candidates and potential lead formulations, in particular during late stages of discovery and early phases of development. This study aimed to establish a bio-layer-interferometry based high throughput assay for assessing formulation dependent mAb self-interaction (SI-BLI) and to compare the results with kD values obtained by dynamic light scattering (DLS).

Methods

Self-interaction of proprietary and commercially available mAbs was analyzed by SI-BLI and dynamic light scattering (DLS).

Results

We found significant correlations of the SI-BLI results and kD-values obtained by DLS for both, different mAbs in one platform formulation and for mAbs formulated in several buffer compositions. In total, we assessed self-interaction propensity of different mAbs in 58 formulations and found significant Pearson correlation (p < 0.05) between kD and results of SI-BLI.

Conclusions

The SI-BLI results correlate with kD and enable fast ranking of both different drug candidates and potential lead formulations. Thus, SI-BLI might decrease the risk to lose potent mAb candidates during transition from discovery to development, and help to accelerate the development of high concentration liquid formulations.

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Abbreviations

AUC:

Analytical ultracentrifugation

BLI:

Bio-layer-interferometry

DLS:

Dynamic light scattering

HCLF:

high (protein) concentration liquid formulation

HDX-MS:

Hydrogen-Deuterium exchange mass spectrometry

mAb:

Monoclonal antibody

PBS:

Phosphate buffered saline

SI-BLI:

Self-interaction assay based on Bio-layer-interferometry

SIC:

Self-interaction chromatography

SLS:

Static Light Scattering

References

  1. Ecker DM, Jones SD, Levine HL. The therapeutic monoclonal antibody market. MAbs. 2015;7:9–14.

    Article  CAS  Google Scholar 

  2. Shire SJ, Shahrokh Z, Liu J. Challenges in the development of high protein concentration formulations. J Pharm Sci. 2004;93:1390–402.

    Article  CAS  Google Scholar 

  3. Yadav S, Liu J, Shire SJ, Kalonia DS. Specific interactions in high concentration antibody solutions resulting in high viscosity. J Pharm Sci. 2010;99:1152–68.

    Article  CAS  Google Scholar 

  4. Laue T. Proximity energies: A framework for understanding concentrated solutions. J Mol Recognit. 2012;25:165–73.

    Article  CAS  Google Scholar 

  5. Lilyestrom WG, Yadav S, Shire SJ, Scherer TM. Monoclonal antibody self-association, cluster formation, and rheology at high concentrations. J Phys Chem B. 2013;117:6373–84.

    Article  CAS  Google Scholar 

  6. Esfandiary R, Parupudi A, Casas-Finet J, Gadre D, Sathish H. Mechanism of Reversible Self-Association of a Monoclonal Antibody: Role of Electrostatic and Hydrophobic Interactions. J Pharm Sci. 2015;104:577–86.

    Article  CAS  Google Scholar 

  7. Binabaji E, Ma J, Zydney AL. Intermolecular Interactions and the Viscosity of Highly Concentrated Monoclonal Antibody Solutions. Pharm Res. 2015;32:3102–9.

    Article  CAS  Google Scholar 

  8. Connolly BD, Petry C, Yadav S, Demeule B, Ciaccio N, Moore JMR, et al. Weak interactions govern the viscosity of concentrated antibody solutions: High-throughput analysis using the diffusion interaction parameter. Biophys J. 2012;103:69–78.

    Article  CAS  Google Scholar 

  9. Le Brun V, Friess W, Bassarab S, Mühlau S, Garidel P. A critical evaluation of self-interaction chromatography as a predictive tool for the assessment of protein-protein interactions in protein formulation development: A case study of a therapeutic monoclonal antibody. Eur J Pharm Biopharm. 2010;75:16–25.

    Article  Google Scholar 

  10. Dear BJ, Hung JJ, Truskett TM, Johnston KP. Contrasting the Influence of Cationic Amino Acids on the Viscosity and Stability of a Highly Concentrated Monoclonal Antibody. Pharm Res. 2017;34:193–207.

    Article  CAS  Google Scholar 

  11. Agrawal NJ, Helk B, Kumar S, Mody N, Sathish HA, Samra HS, et al. Computational tool for the early screening of monoclonal antibodies for their viscosities. MAbs. 2016;8:43–8.

    Article  CAS  Google Scholar 

  12. Hofmann M, Winzer M, Weber C, Gieseler H. Prediction of Protein Aggregation in High Concentration Protein Solutions Utilizing Protein-Protein Interactions Determined by Low Volume Static Light Scattering. J Pharm Sci Elsevier Ltd. 2016;105:1819–28.

    CAS  Google Scholar 

  13. Hedberg SHM, Heng JYY, Williams DR, Liddell JM. Self-Interaction Chromatography of mAbs: Accurate Measurement of Dead Volumes. Pharm Res. 2015;32:3975–85.

    Article  CAS  Google Scholar 

  14. Liu Y, Caffry I, Wu J, Geng SB, Jain T, Sun T, et al. High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy. MAbs. 2014;6:483–92.

    Article  Google Scholar 

  15. Estep P, Caffry I, Yu Y, Sun T, Cao Y, Lynaugh H, et al. An alternative assay to hydrophobic interaction chromatography for high-throughput characterization of monoclonal antibodies. MAbs. 2015;7:553–61.

    Article  CAS  Google Scholar 

  16. Saito S, Hasegawa J, Kobayashi N, Kishi N, Uchiyama S, Fukui K. Behavior of Monoclonal Antibodies: Relation between the Second Virial Coefficient (B2) at Low Concentrations and Aggregation Propensity and Viscosity at High Concentrations. Pharm Res. 2012;29:397–410.

    Article  CAS  Google Scholar 

  17. Hopkins MM, Lambert CL, Bee JS, Parupudi A, Bain DL. Determination of Interaction Parameters for Reversibly Self-Associating Antibodies: A Comparative Analysis. J Pharm Sci Elsevier Ltd. 2018;107:1820–30.

    CAS  Google Scholar 

  18. Sun T, Reid F, Liu Y, Cao Y, Estep P, Nauman C, et al. High throughput detection of antibody self-interaction by bio-layer interferometry. MAbs. 2013;5:838–41.

    Article  Google Scholar 

  19. Zhang Z, Liu Y. Recent progresses of understanding the viscosity of concentrated protein solutions. Curr Opin Chem Eng Elsevier Ltd. 2017;16:48–55.

    Article  Google Scholar 

  20. Liu J, Nguyen MDH, Andya JD, Shire SJ. Reversible self-association increases the viscosity of a concentrated monoclonal antibody in aqueous solution. J Pharm Sci. 2005;94:1928–40.

    Article  CAS  Google Scholar 

  21. Li L, Kumar S, Buck PM, Burns C, Lavoie J, Singh SK, et al. Concentration dependent viscosity of monoclonal antibody solutions: Explaining experimental behavior in terms of molecular properties. Pharm Res. 2014;31:3161–78.

    Article  CAS  Google Scholar 

  22. Yadav S, Scherer TM, Shire SJ, Kalonia DS. Use of dynamic light scattering to determine second virial coefficient in a semidilute concentration regime. Anal Biochem. 2011;411:292–6.

    Article  CAS  Google Scholar 

  23. Tomar DS, Kumar S, Singh SK, Goswami S, Li L. Molecular basis of high viscosity in concentrated antibody solutions: Strategies for high concentration drug product development. MAbs. 2016;8:216–28.

    Article  CAS  Google Scholar 

  24. Sorret LL, DeWinter MA, Schwartz DK, Randolph TW. Challenges in Predicting Protein-Protein Interactions from Measurements of Molecular Diffusivity. Biophys J Biophysical Society. 2016;111:1831–42.

    CAS  Google Scholar 

  25. Arora J, Hu Y, Esfandiary R, Sathish HA, Bishop SM, Joshi SB, et al. Charge-mediated Fab-Fc interactions in an IgG1 antibody induce reversible self-association, cluster formation, and elevated viscosity. MAbs. 2016;8:1561–74.

    Article  CAS  Google Scholar 

  26. Arora J, Hickey JM, Majumdar R, Esfandiary R, Bishop SM, Samra HS, et al. Hydrogen exchange mass spectrometry reveals protein interfaces and distant dynamic coupling effects during the reversible self-association of an IgG1 monoclonal antibody. MAbs. 2015;7:525–39.

    Article  CAS  Google Scholar 

  27. Kanai S, Liu J, Patapoff TW, Shire SJ. Reversible Self-Association of a Concentrated Monoclonal Antibody Solution Mediated by Fab–Fab Interaction That Impacts Solution Viscosity. J Pharm Sci. 2008;97:4219–27.

    Article  CAS  Google Scholar 

  28. Geng SB, Wittekind M, Vigil A, Tessier PM. Measurements of Monoclonal Antibody Self-Association Are Correlated with Complex Biophysical Properties. Mol Pharm. 2016;13:1636–45.

    Article  CAS  Google Scholar 

  29. Hedberg SHM, Heng JYY, Williams DR, Liddell JM. Micro scale self-interaction chromatography of proteins: A mAb case-study. J Chromatogr A. 2016;1434:57–63.

    Article  CAS  Google Scholar 

  30. Yang D, Correia JJ, Iii WFS, Roberts CJ, Singh S, Hayes D, et al. Weak IgG self and hetero-association characterized by fluorescence analytical ultracentrifugation. Protein Sci. 2018;27:1334–48.

    Article  CAS  Google Scholar 

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Acknowledgements

This study was part of the project “Self-Interaction and targeted Engineering of monoclonal antibodies (Self-I-E)”. This project is funded by the Bayerische Forschungsstiftung. The authors would like to thank the whole Protein Sciences & CMC Department of MorphoSys AG for their outstanding support. In addition, the authors would like to thank Dr. Daniel Weinfurtner and Dr. Roy Eylenstein for their support during the initial phase of this project.

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Correspondence to Wolfgang Frieß.

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Guest Editors: Ahmed Besheer and Hanns-Christian Mahler

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Domnowski, M., Jaehrling, J. & Frieß, W. Assessment of Antibody Self-Interaction by Bio-Layer-Interferometry as a Tool for Early Stage Formulation Development. Pharm Res 37, 29 (2020). https://doi.org/10.1007/s11095-019-2722-4

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