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

Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 8406521 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-904X (Electronic) Linking ISSN: 07248741 NLM ISO Abbreviation: Pharm Res Subsets: MEDLINE

Publication: 1999- : New York, NY : Kluwer Academic/Plenum Publishers
Original Publication: Stuttgart ; New York : Thieme, c1984-

Biopharmaceutics*/methods ; Diabetes Mellitus, Type 2*; Humans ; Models, Biological ; Injections, Subcutaneous ; Proteins

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.
(© 2023. The Author(s).)

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Keywords: PBBM; back-flow; backpressure; depot; injection; modeling and simulation; physiology; subcutaneous

0 (Proteins)

Date Created: 20230827 Date Completed: 20231005 Latest Revision: 20231006

20240829

PMC10547635

10.1007/s11095-023-03567-0

37634241