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

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.

Experience with Biodegradable Polymer Coated Sirolimus-Eluting Coronary Stent System in “Real-Life” Percutaneous Coronary Intervention: 24-Month Data from the Manipal-S Registry

“…The permanent presence of these polymers has been correlated to inflammatory responses, hypersensitivity issues, lack of a complete endothelization, thrombus formation, and local toxicity in preclinical trials as well as clinical studies [31][32][33][34]. Furthermore, durable polymers which were used in first-generation DES were associated with mechanical complications (e.g., polymer delamination and "webbed" polymer surface which led to stent expansion issues) [35] and the nonuniform coating had resulted in an erratic drug distribution.…”

New Drug-Eluting Stents

“…A total of 180 patients will be enrolled in this prospective, multicenter study and randomly assigned Translumina has licensed the technology for several companies and therefore different anti-proliferative and antiinflammatory agents have been tested. To the present, the largest successful experience was with a combination of sirolimus (120 g/cm 2 ) and probucol (100 g/cm 2 ) 14 Modified microporous stent surface…”

“…The permanent presence of these polymers has been correlated to inflammatory responses and local toxicity in preclinical analysis. 10 -13 Furthermore, durable polymers used in first-generation DES have been associated with mechanical complications (eg, polymer delamination and "webbed" polymer surface leading to stent expansion issues) 14 and nonuniform coating resulting in erratic drug distribution. As a consequence, in recent years, the focus of clinical research has been on the development of novel drug carrier systems including absorbable (or biodegradable) polymers and nonpolymeric stent surfaces.…”

Additive Manufacturing of Biomaterials, Tissues, and Organs

“…Computational modeling can aid prediction of release profiles from various drug delivery systems 6,31,40 and may be of particular value for drug delivery systems based on AM structures. These computational models will provide insights into the effects of the geometrical design, microarchitecture, and spatial distributions of active and passive agents on the release profiles.…”