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Delivery of Antibodies into the Murine Brain via Convection-enhanced Delivery
Published on: July 18, 2019
Retro-convection enhanced drug delivery: a computational study
Peng Wang1, William L Olbricht
1School of Chemical and Biomolecular Engineering, Cornell University, 120 Olin Hall, Ithaca, NY 14853, USA. pw96@cornell.edu
Annals of Biomedical Engineering
|April 2, 2010
Summary
Retro-convection enhanced delivery (R-CED) shows promise for overcoming the blood-brain barrier (BBB). However, mathematical modeling reveals R-CED has limitations in treatment volume, requiring further experimental evaluation.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Drug Delivery
Background:
- The blood-brain barrier (BBB) presents a significant challenge for delivering therapeutics to the brain.
- Retro-convection enhanced delivery (R-CED) is an emerging technique to improve drug transport across the BBB.
Purpose of the Study:
- To develop and utilize a mathematical model to analyze fluid flow and mass transfer in brain tissue during R-CED.
- To predict pressure, flow patterns, and drug concentration profiles.
- To evaluate the impact of microdialysis membranes on R-CED efficacy.
Main Methods:
- Development of a mathematical model for R-CED therapy.
- Computer simulations to obtain numerical results for pressure, fluid flow, and drug concentration.
- Detailed analysis of three microdialysis membrane types.
- Sensitivity analysis of various parameters.
Main Results:
- Fluid flow in brain tissue was independent of the microdialysis membrane type.
- Mass transfer and drug distribution were highly dependent on membrane selection.
- R-CED effectively generated fluid flows but did not significantly increase the effective treatment volume.
Conclusions:
- While R-CED shows potential for brain drug delivery, its efficacy in achieving a large treatment volume needs further investigation.
- The choice of microdialysis membranes significantly impacts drug distribution, not fluid flow.
- Experimental re-evaluation of R-CED is recommended to optimize its application.
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