MPET2 : a multi-network poroelastic and transport theory for predicting absorption of monoclonal antibodies delivered by subcutaneous injection

Subcutaneous injection of monoclonal antibodies (mAbs) has attracted much attention in the pharmaceutical industry. During the injection, the drug is delivered into the tissue producing strong fluid flow and tissue deformation. While data indicate that the drug is initially uptaken by the lymphatic system due to the large size of mAbs, many of the critical absorption processes that occur at the injection site remain poorly understood. Here, we propose the MPET2 approach, a multi-network poroelastic and transport model to predict the absorption of mAbs during and after subcutaneous injection. Our model is based on physical principles of tissue biomechanics and fluid dynamics. The subcutaneous tissue is modeled as a mixture of three compartments, i.e., interstitial tissue, blood vessels, and lymphatic vessels, with each compartment modeled as a porous medium. The proposed biomechanical model describes tissue deformation, fluid flow in each compartment, the fluid exchanges between compartments, the absorption of mAbs in blood vessels and lymphatic vessels, as well as the transport of mAbs in each compartment. We used our model to perform a high-fidelity simulation of an injection of mAbs in subcutaneous tissue and evaluated the long-term drug absorption. Our model results show good agreement with experimental data in depot clearance tests.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:30

Enthalten in:

Drug delivery - 30(2023), 1 vom: 26. Dez., Seite 2163003

Sprache:

Englisch

Beteiligte Personen:

Wang, Hao [VerfasserIn]
Hu, Tianyi [VerfasserIn]
Leng, Yu [VerfasserIn]
de Lucio, Mario [VerfasserIn]
Gomez, Hector [VerfasserIn]

Links:

Volltext

Themen:

Antibodies, Monoclonal
Biomechanical modeling
Journal Article
Monoclonal antibodies
Multi-network poroelastic (MPET) model
Subcutaneous biomechanics
Subcutaneous injection

Anmerkungen:

Date Completed 11.01.2023

Date Revised 21.01.2023

published: Print

Citation Status MEDLINE

doi:

10.1080/10717544.2022.2163003

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM351364838