Treffer: A computational framework for predicting leakage in subcutaneous injections.

Title:
A computational framework for predicting leakage in subcutaneous injections.
Authors:
de Lucio M; School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette IN 47907, USA. Electronic address: mdeluci@purdue.edu., Vlachos PP; School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette IN 47907, USA., Gomez H; School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette IN 47907, USA.
Source:
International journal of pharmaceutics [Int J Pharm] 2026 Jan 05; Vol. 687, pp. 126431. Date of Electronic Publication: 2025 Nov 24.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Elsevier/North-Holland Biomedical Press Country of Publication: Netherlands NLM ID: 7804127 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-3476 (Electronic) Linking ISSN: 03785173 NLM ISO Abbreviation: Int J Pharm Subsets: MEDLINE
Imprint Name(s):
Original Publication: Amsterdam, Elsevier/North-Holland Biomedical Press.
MeSH Terms:
Computer Simulation* , Skin*/metabolism , Skin*/anatomy & histology, Injections, Subcutaneous/methods ; Humans ; Animals ; Subcutaneous Tissue
Contributed Indexing:
Keywords: Auto-injector; Backflow; Leakage; Monoclonal antibody; Pre-filled syringe; Subcutaneous injection
Entry Date(s):
Date Created: 20251126 Date Completed: 20251210 Latest Revision: 20251210
Update Code:
20251211
DOI:
10.1016/j.ijpharm.2025.126431
PMID:
41297863
Database:
MEDLINE

Weitere Informationen

Subcutaneous injection of biologics has become a viable alternative to intravenous infusion for treating diseases such as cancer, autoimmune disorders, and diabetes. However, some of the injected fluid can leak from the skin post-injection, a phenomenon known as leakage or backflow. This loss of medication may be significant and could impact drug efficacy. Despite its clinical relevance, there are currently no computational models capable of predicting drug leakage dynamics. In this work, we develop a high-fidelity computational framework to model leakage during subcutaneous injection. The model incorporates a simplified skin and subcutaneous morphology. The model is validated against experimental data on tissue swelling and leakage dynamics for different injection devices. We then use it to assess the influence of key parameters, including injection depth, injection volume, needle gauge, injection site, and wait time.
(Copyright © 2025 Elsevier B.V. All rights reserved.)

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mario de Lucio reports financial support was provided by Eli Lilly and Company. Mario de Lucio reports a relationship with Eli Lilly and Company that includes: employment. Mario de Lucio is an employee of Eli Lilly and Company. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.