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A mathematical model for predicting drug release from a biodurable drug-eluting stent coating

✍ Scribed by Syed Hossainy; Santosh Prabhu


Publisher
John Wiley and Sons
Year
2008
Tongue
English
Weight
219 KB
Volume
87A
Category
Article
ISSN
1549-3296

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✦ Synopsis


Abstract

Drug‐eluting stents (DESs) are drug–device combination products that have been commercialized and demonstrated to be safe and efficacious in treating coronary artery disease. They have been very effective in reducing the extent of neointimal hyperplasia and therefore in preventing or minimizing the occurrence of in‐stent restenosis. In order to develop a successful DES, it is imperative that the coating be designed so as to deliver, after stent implantation, a therapeutic dose of the drug for the desired time duration at the site of the arterial blockage. Mathematical models are very valuable tools that can be used to study the effect of different coating parameters on drug delivery and can therefore help in coating design. We have developed a bimodal lumped‐parameter mass transport model to describe the release of the drug everolimus from a biodurable fluoropolymer‐based DES coating. We assume that the dispersed drug phase contributes to two discrete modes of drug transport through the coating. These are the fast mode (mode I) which is the release of the drug from a highly percolated structure of drug phase within the polymer, and the slow mode (mode II) which is the release of the drug from a nonpercolated, polymer‐encapsulated phase of the drug within the coating. The three coefficients in the governing equations describing the model, i.e. the two effective diffusivities corresponding to each of the two modes and the fraction of the drug in one of the two modes, were determined by fitting with available DES release data. The predictive power of the model is demonstrated by comparing the release rate from different coating configurations (thickness and drug to polymer ratios) with experimental data. Also, it is demonstrated that if limited experimental data are available at early time points, the model can be used to predict drug release at subsequent time points. © 2008 Wiley Periodicals, Inc. J Biomed Mater Res, 2008


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