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

Xavier J. H. Pepin; Iain Grant; J. Matthew Wood
Pharmaceutical Research · Vol. 40, Issue 9 · pp. 2195-2214 · 2023

Abstract

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.

Bibliographic Information

JournalPharmaceutical Research
PublisherSpringer
Publication Date2023-09-01
Publication Year2023
Volume40
Issue9
Pages2195-2214
Document TypeJournal Article
Print ISSN0724-8741
eISSN1573-904X
DOI10.1007/s11095-023-03567-0

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NARA Access Coverage1984-01-01~Current
Journal Homepagehttps://www.springer.com/journal/11095
Publisher PageOpen Publisher Page
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