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SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters

PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection....

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Detalles Bibliográficos
Autores principales: Pepin, Xavier J. H., Grant, Iain, Wood, J. Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547635/
https://www.ncbi.nlm.nih.gov/pubmed/37634241
http://dx.doi.org/10.1007/s11095-023-03567-0
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author Pepin, Xavier J. H.
Grant, Iain
Wood, J. Matthew
author_facet Pepin, Xavier J. H.
Grant, Iain
Wood, J. Matthew
author_sort Pepin, Xavier J. H.
collection PubMed
description PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection. This paper is part of a series and focusses on the first aspect. METHODS: A mathematical model, SubQ-Sim, was developed incorporating the details of the various substructures within the subcutaneous environment together with the calculation of dynamic drug disposition towards the lymph ducts and venous capillaries. Literature was searched to derive key model parameters in healthy and diseased subjects. External factors such as body temperature, exercise, body position, food or stress provide a means to calculate the impact of “life events” on the pharmacokinetics of subcutaneously administered drugs. RESULTS: The model predicts the tissue backpressure time profile during the injection as a function of injection rate, volume injected, solution viscosity, and interstitial fluid viscosity. The shape of the depot and the concentrations of the formulation and proteins in the depot are described. The model enables prediction of formulation backflow following premature needle removal and the resulting formulation losses. Finally, the effect of disease (type 2 diabetes) or the presence of recombinant human hyaluronidase in the formulation on the injection pressure, are explored. CONCLUSIONS: This novel model can successfully predict tissue back pressure, depot dimensions, drug and protein concentration and formulation losses due to incorrect injection, which are all important starting conditions for predicting drug absorption from a subcutaneous dose. The next article will describe the absorption model and validation against clinical data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-023-03567-0.
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spelling pubmed-105476352023-10-05 SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters Pepin, Xavier J. H. Grant, Iain Wood, J. Matthew Pharm Res Original Research Article PURPOSE: To construct a detailed mechanistic and physiologically based biopharmaceutics model capable of predicting 1) device-formulation-tissue interaction during the injection process and 2) binding, degradation, local distribution, diffusion, and drug absorption, following subcutaneous injection. This paper is part of a series and focusses on the first aspect. METHODS: A mathematical model, SubQ-Sim, was developed incorporating the details of the various substructures within the subcutaneous environment together with the calculation of dynamic drug disposition towards the lymph ducts and venous capillaries. Literature was searched to derive key model parameters in healthy and diseased subjects. External factors such as body temperature, exercise, body position, food or stress provide a means to calculate the impact of “life events” on the pharmacokinetics of subcutaneously administered drugs. RESULTS: The model predicts the tissue backpressure time profile during the injection as a function of injection rate, volume injected, solution viscosity, and interstitial fluid viscosity. The shape of the depot and the concentrations of the formulation and proteins in the depot are described. The model enables prediction of formulation backflow following premature needle removal and the resulting formulation losses. Finally, the effect of disease (type 2 diabetes) or the presence of recombinant human hyaluronidase in the formulation on the injection pressure, are explored. CONCLUSIONS: This novel model can successfully predict tissue back pressure, depot dimensions, drug and protein concentration and formulation losses due to incorrect injection, which are all important starting conditions for predicting drug absorption from a subcutaneous dose. The next article will describe the absorption model and validation against clinical data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-023-03567-0. Springer US 2023-08-27 2023 /pmc/articles/PMC10547635/ /pubmed/37634241 http://dx.doi.org/10.1007/s11095-023-03567-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Research Article
Pepin, Xavier J. H.
Grant, Iain
Wood, J. Matthew
SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title_full SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title_fullStr SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title_full_unstemmed SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title_short SubQ-Sim: A Subcutaneous Physiologically Based Biopharmaceutics Model. Part 1: The Injection and System Parameters
title_sort subq-sim: a subcutaneous physiologically based biopharmaceutics model. part 1: the injection and system parameters
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547635/
https://www.ncbi.nlm.nih.gov/pubmed/37634241
http://dx.doi.org/10.1007/s11095-023-03567-0
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