A computational framework for predicting leakage in subcutaneous injections.

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.