Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans
Salvage of endogenous immunoglobulin G (IgG) by the neonatal Fc receptor (FcRn) is implicated in many clinical areas, including therapeutic monoclonal antibody kinetics, patient monitoring in IgG multiple myeloma, and antibody-mediated transplant rejection. There is a clear clinical need for a fully...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fimmu.2019.00674/full |
| _version_ | 1818527530227859456 |
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| author | Felicity Kendrick Neil D. Evans Oscar Berlanga Stephen J. Harding Michael J. Chappell |
| author_facet | Felicity Kendrick Neil D. Evans Oscar Berlanga Stephen J. Harding Michael J. Chappell |
| author_sort | Felicity Kendrick |
| collection | DOAJ |
| description | Salvage of endogenous immunoglobulin G (IgG) by the neonatal Fc receptor (FcRn) is implicated in many clinical areas, including therapeutic monoclonal antibody kinetics, patient monitoring in IgG multiple myeloma, and antibody-mediated transplant rejection. There is a clear clinical need for a fully parameterized model of FcRn-mediated recycling of endogenous IgG to allow for predictive modeling, with the potential for optimizing therapeutic regimens for better patient outcomes. In this paper we study a mechanism-based model incorporating nonlinear FcRn-IgG binding kinetics. The aim of this study is to determine whether parameter values can be estimated using the limited in vivo human data, available in the literature, from studies of the kinetics of radiolabeled IgG in humans. We derive mathematical descriptions of the experimental observations—timecourse data and fractional catabolic rate (FCR) data—based on the underlying physiological model. Structural identifiability analyses are performed to determine which, if any, of the parameters are unique with respect to the observations. Structurally identifiable parameters are then estimated from the data. It is found that parameter values estimated from timecourse data are not robust, suggesting that the model complexity is not supported by the available data. Based upon the structural identifiability analyses, a new expression for the FCR is derived. This expression is fitted to the FCR data to estimate unknown parameter values. Using these parameter estimates, the plasma IgG response is simulated under clinical conditions. Finally a suggestion is made for a reduced-order model based upon the newly derived expression for the FCR. The reduced-order model is used to predict the plasma IgG response, which is compared with the original four-compartment model, showing good agreement. This paper shows how techniques for compartmental model analysis—structural identifiability analysis, linearization, and reparameterization—can be used to ensure robust parameter identification. |
| first_indexed | 2024-12-11T06:37:18Z |
| format | Article |
| id | doaj.art-f4419d9338704737b240e0fdd9eb98e5 |
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| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-11T06:37:18Z |
| publishDate | 2019-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-f4419d9338704737b240e0fdd9eb98e52022-12-22T01:17:21ZengFrontiers Media S.A.Frontiers in Immunology1664-32242019-04-011010.3389/fimmu.2019.00674424121Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in HumansFelicity Kendrick0Neil D. Evans1Oscar Berlanga2Stephen J. Harding3Michael J. Chappell4School of Engineering, University of Warwick, Coventry, United KingdomSchool of Engineering, University of Warwick, Coventry, United KingdomDepartment of Research and Development, The Binding Site Group Limited, Birmingham, United KingdomDepartment of Research and Development, The Binding Site Group Limited, Birmingham, United KingdomSchool of Engineering, University of Warwick, Coventry, United KingdomSalvage of endogenous immunoglobulin G (IgG) by the neonatal Fc receptor (FcRn) is implicated in many clinical areas, including therapeutic monoclonal antibody kinetics, patient monitoring in IgG multiple myeloma, and antibody-mediated transplant rejection. There is a clear clinical need for a fully parameterized model of FcRn-mediated recycling of endogenous IgG to allow for predictive modeling, with the potential for optimizing therapeutic regimens for better patient outcomes. In this paper we study a mechanism-based model incorporating nonlinear FcRn-IgG binding kinetics. The aim of this study is to determine whether parameter values can be estimated using the limited in vivo human data, available in the literature, from studies of the kinetics of radiolabeled IgG in humans. We derive mathematical descriptions of the experimental observations—timecourse data and fractional catabolic rate (FCR) data—based on the underlying physiological model. Structural identifiability analyses are performed to determine which, if any, of the parameters are unique with respect to the observations. Structurally identifiable parameters are then estimated from the data. It is found that parameter values estimated from timecourse data are not robust, suggesting that the model complexity is not supported by the available data. Based upon the structural identifiability analyses, a new expression for the FCR is derived. This expression is fitted to the FCR data to estimate unknown parameter values. Using these parameter estimates, the plasma IgG response is simulated under clinical conditions. Finally a suggestion is made for a reduced-order model based upon the newly derived expression for the FCR. The reduced-order model is used to predict the plasma IgG response, which is compared with the original four-compartment model, showing good agreement. This paper shows how techniques for compartmental model analysis—structural identifiability analysis, linearization, and reparameterization—can be used to ensure robust parameter identification.https://www.frontiersin.org/article/10.3389/fimmu.2019.00674/fullbiological systemslumped-parameter systemsimmunoglobulin Gneonatal Fc receptorparameter estimationstructural identifiability |
| spellingShingle | Felicity Kendrick Neil D. Evans Oscar Berlanga Stephen J. Harding Michael J. Chappell Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans Frontiers in Immunology biological systems lumped-parameter systems immunoglobulin G neonatal Fc receptor parameter estimation structural identifiability |
| title | Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans |
| title_full | Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans |
| title_fullStr | Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans |
| title_full_unstemmed | Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans |
| title_short | Parameter Identification for a Model of Neonatal Fc Receptor-Mediated Recycling of Endogenous Immunoglobulin G in Humans |
| title_sort | parameter identification for a model of neonatal fc receptor mediated recycling of endogenous immunoglobulin g in humans |
| topic | biological systems lumped-parameter systems immunoglobulin G neonatal Fc receptor parameter estimation structural identifiability |
| url | https://www.frontiersin.org/article/10.3389/fimmu.2019.00674/full |
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