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Journal of Immunology Research
Volume 2015, Article ID 401956, 14 pages
Research Article

The Role of Aggregates of Therapeutic Protein Products in Immunogenicity: An Evaluation by Mathematical Modeling

1Pharmacokinetics, Dynamics and Metabolism-New Biological Entities, Pfizer, Andover, MA 01810, USA
2Pharmacokinetics, Dynamics and Metabolism-New Biological Entities, Pfizer, Cambridge, MA 02138, USA
3Pharmacokinetics, Dynamics and Metabolism-New Biological Entities, Pfizer, San Diego, CA 92121, USA

Received 31 July 2015; Accepted 7 October 2015

Academic Editor: Marzio Pennisi

Copyright © 2015 Liusong Yin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Therapeutic protein products (TPP) have been widely used to treat a variety of human diseases, including cancer, hemophilia, and autoimmune diseases. However, TPP can induce unwanted immune responses that can impact both drug efficacy and patient safety. The presence of aggregates is of particular concern as they have been implicated in inducing both T cell-independent and T cell-dependent immune responses. We used mathematical modeling to evaluate several mechanisms through which aggregates of TPP could contribute to the development of immunogenicity. Modeling interactions between aggregates and B cell receptors demonstrated that aggregates are unlikely to induce T cell-independent immune responses by cross-linking B cell receptors because the amount of signal transducing complex that can form under physiologically relevant conditions is limited. We systematically evaluate the role of aggregates in inducing T cell-dependent immune responses using a recently developed multiscale mechanistic mathematical model. Our analysis indicates that aggregates could contribute to T cell-dependent immune response by inducing high affinity epitopes which may not be present in the nonaggregated TPP and/or by enhancing danger signals to break tolerance. In summary, our computational analysis is suggestive of novel insights into the mechanisms underlying aggregate-induced immunogenicity, which could be used to develop mitigation strategies.