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Lipid Bilayer Vesicle Generation Using Microfluidic Jetting
Published on: February 21, 2014
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In-vitro studies of jet injections.
Pankaj Rohilla1, Jeremy O Marston1
1Department of Chemical Engineering, Texas Tech University, Lubbock, TX 79409, United States.
International Journal of Pharmaceutics
|July 16, 2019
Summary
Needle-free jet injection depth depends non-linearly on standoff distance. Researchers used gelatin models to study jet dynamics, finding confinement effects caution against using gelatin as a human tissue proxy.
Area of Science:
- Biomedical Engineering
- Fluid Dynamics
- Materials Science
Background:
- Needle-free jet injection offers advantages over traditional needles.
- Understanding injection dynamics is crucial for optimizing device design and efficacy.
- Gelatin is often used as a model for soft biological tissues.
Purpose of the Study:
- To investigate the key parameters influencing needle-free jet injection dynamics.
- To quantify the effect of standoff distance, gel properties, and liquid viscosity on penetration depth.
- To evaluate the suitability of gelatin as a surrogate for human tissue in injection studies.
Main Methods:
- Utilized homogeneous gelatin as a model substrate for jet injection.
- Employed high-speed imaging to analyze liquid jet propagation and dispersion.
- Used a load cell to measure impact forces at varying standoff distances and liquid viscosities.
Main Results:
- Demonstrated significant effects of standoff, gel modulus, and liquid viscosity on penetration depth.
- Identified a key non-linear relationship between standoff distance and penetration depth.
- Highlighted that confinement effects in gelatin models differ from human tissue, cautioning against direct extrapolation.
Conclusions:
- The non-linear dependence of penetration depth on standoff distance has critical implications for future needle-free injector design.
- Findings underscore the limitations of using gelatin as a direct substitute for human tissue due to confinement differences.
- Further research is needed to refine models for more accurate prediction of jet injection behavior in biological tissues.
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