Mathematical Modeling of Coupled Drug and Drug-encapsulated Nanoparticle Transport in Patient-specific Coronary Artery Walls
23/09/2010 Thursday 23rd September 2010, 15:00 (Conference Room, Instituto de Sistemas e Robótica, North Tower, 7th floor, IST)
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Shaolie Hossain, ICES, The University of Texas at Austin
Atherosclerosis is the gradual build up of plaque material in the arterial wall, composed primarily of lipid-rich fatty deposit, inflammatory cells, and fibrous tissue. A vast majority of heart attacks occur when there is a sudden rupture in the atherosclerotic plaque, exposing its prothrombotic core materials to the coronary blood flow, forming blood clots that can cause blockage of the arterial lumen. The diseased arteries can be treated with drugs delivered locally to these rupture–prone plaques termed “vulnerable plaques”. In designing these local drug delivery devices, important issues regarding drug distribution and targeting need to be addressed to ensure device design optimization. For example, a drug delivery implant adjacent to a target tissue may not produce the desired safe and efficacious therapy. Therefore, the main objective of this work was to develop a computational tool-set that provides predictive local pharmacokinetic insight into the design and analysis of a catheter-based drug delivery system that uses nanoparticles as drug carriers to treat vulnerable plaques and diffuse atherosclerosis. A three-dimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically by applying finite element based isogeometric analysis that uses NURBS. Simulations were run on a patient-specific multilayered coronary artery wall segment with a typical vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method successfully captured trends observed in local drug delivery and demonstrated its potential utility in optimizing design parameters, including delivery location, nanoparticle surface properties, and drug release rate.
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