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A review of quantitative modeling of B cell responses to antigenic challenge

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Abstract

A key role of B cells in the mammalian immune response is the generation of antibodies that serve to protect the organism against antigenic challenges. The same process may also be detrimental in the context of autoimmunity. Several modeling approaches have been applied to this aspect of the immune response, from predicting potential epitopes to describing B cells progress through developmental models and simulating antibody production. Here we review some of the modeling techniques, and summarize models that describe different activation mechanisms for B cells, including T cell dependent and independent models. We focus on viral infection as a prototype system, and briefly describe case studies in other disease areas such as bacterial infection and oncology. We single out aspects of the B cell response for which there are current knowledge gaps. We outline areas in need of further research in modeling applications to ultimately produce a “B cell module” for a complete immune response model.

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Acknowledgments

The authors are Pfizer employees and shareholders. The authors gratefully acknowledge Dr. Catherine Yeh’s support in implementing in MATLAB the published models used for the computer simulations.

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Authors and Affiliations

  1. Pharmacokinetics, Dynamics and Metabolism - New Biological Entities, Pfizer, Andover, MA, USA

    Timothy P. Hickling

  2. Pharmacokinetics, Dynamics and Metabolism - New Biological Entities, Pfizer, Cambridge, MA, USA

    Xiaoying Chen

  3. Pharmacokinetics, Dynamics and Metabolism - New Biological Entities, Pfizer, San Diego, CA, USA

    Paolo Vicini

  4. Pharmacometrics, Global Clinical Pharmacology, Pfizer, Cambridge, MA, USA

    Satyaprakash Nayak

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  1. Timothy P. Hickling
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  2. Xiaoying Chen
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  4. Satyaprakash Nayak
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Correspondence to Satyaprakash Nayak.

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Hickling, T.P., Chen, X., Vicini, P. et al. A review of quantitative modeling of B cell responses to antigenic challenge. J Pharmacokinet Pharmacodyn 41, 445–459 (2014). https://doi.org/10.1007/s10928-014-9388-7

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  • DOI: https://doi.org/10.1007/s10928-014-9388-7

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