Cargando…

The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies

The main objective of this tutorial is to provide the readers with a roadmap of how to establish increasingly complex target‐mediated drug disposition (TMDD) models for monoclonal antibodies. To this end, we built mathematical models, each with a detailed visualization, starting from the basic TMDD...

Descripción completa

Detalles Bibliográficos
Autores principales: Pressly, Michelle A., Peletier, Lambertus A., Zheng, Songmao, Sharma, Vishnu D., Lien, Yi Ting (Kayla), Wang, Weirong, Zhou, Honghui, Schmidt, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196441/
https://www.ncbi.nlm.nih.gov/pubmed/36752286
http://dx.doi.org/10.1002/psp4.12927
_version_ 1785044354908291072
author Pressly, Michelle A.
Peletier, Lambertus A.
Zheng, Songmao
Sharma, Vishnu D.
Lien, Yi Ting (Kayla)
Wang, Weirong
Zhou, Honghui
Schmidt, Stephan
author_facet Pressly, Michelle A.
Peletier, Lambertus A.
Zheng, Songmao
Sharma, Vishnu D.
Lien, Yi Ting (Kayla)
Wang, Weirong
Zhou, Honghui
Schmidt, Stephan
author_sort Pressly, Michelle A.
collection PubMed
description The main objective of this tutorial is to provide the readers with a roadmap of how to establish increasingly complex target‐mediated drug disposition (TMDD) models for monoclonal antibodies. To this end, we built mathematical models, each with a detailed visualization, starting from the basic TMDD model by Mager and Jusko to the well‐established, physiologically based model by Li et al. in a step‐wise fashion to highlight the relative importance of key physiological processes that impact mAb kinetics and system dynamics. As the models become more complex, the question of structural and parameter identifiability arises. To address this question, we work through a trastuzumab case example to guide the modeler's choice for model and parameter optimization in light of the context of use. We leave the readers of this tutorial with a brief summary of the advantages and limitations of each model expansion, as well as the model source codes for further self‐guided exploration and hands‐on analysis.
format Online
Article
Text
id pubmed-10196441
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-101964412023-05-20 The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies Pressly, Michelle A. Peletier, Lambertus A. Zheng, Songmao Sharma, Vishnu D. Lien, Yi Ting (Kayla) Wang, Weirong Zhou, Honghui Schmidt, Stephan CPT Pharmacometrics Syst Pharmacol Tutorials The main objective of this tutorial is to provide the readers with a roadmap of how to establish increasingly complex target‐mediated drug disposition (TMDD) models for monoclonal antibodies. To this end, we built mathematical models, each with a detailed visualization, starting from the basic TMDD model by Mager and Jusko to the well‐established, physiologically based model by Li et al. in a step‐wise fashion to highlight the relative importance of key physiological processes that impact mAb kinetics and system dynamics. As the models become more complex, the question of structural and parameter identifiability arises. To address this question, we work through a trastuzumab case example to guide the modeler's choice for model and parameter optimization in light of the context of use. We leave the readers of this tutorial with a brief summary of the advantages and limitations of each model expansion, as well as the model source codes for further self‐guided exploration and hands‐on analysis. John Wiley and Sons Inc. 2023-03-23 /pmc/articles/PMC10196441/ /pubmed/36752286 http://dx.doi.org/10.1002/psp4.12927 Text en © 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Tutorials
Pressly, Michelle A.
Peletier, Lambertus A.
Zheng, Songmao
Sharma, Vishnu D.
Lien, Yi Ting (Kayla)
Wang, Weirong
Zhou, Honghui
Schmidt, Stephan
The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title_full The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title_fullStr The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title_full_unstemmed The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title_short The quest for balance between capturing data and model complexity: A quantitative clinical pharmacology approach applied to monoclonal antibodies
title_sort quest for balance between capturing data and model complexity: a quantitative clinical pharmacology approach applied to monoclonal antibodies
topic Tutorials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196441/
https://www.ncbi.nlm.nih.gov/pubmed/36752286
http://dx.doi.org/10.1002/psp4.12927
work_keys_str_mv AT presslymichellea thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT peletierlambertusa thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT zhengsongmao thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT sharmavishnud thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT lienyitingkayla thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT wangweirong thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT zhouhonghui thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT schmidtstephan thequestforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT presslymichellea questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT peletierlambertusa questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT zhengsongmao questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT sharmavishnud questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT lienyitingkayla questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT wangweirong questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT zhouhonghui questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies
AT schmidtstephan questforbalancebetweencapturingdataandmodelcomplexityaquantitativeclinicalpharmacologyapproachappliedtomonoclonalantibodies