Simulations of drug-eluting stents by engineers at Boston Scientific provide an understanding of the drug-release mechanism by tying experimental findings to a computational model.
Lexi Carver, Comsol, Inc
Contributing authors: Travis Schauer and Ismail Guler, Boston Scientific Corp
Treating arteries in the heart that have been blocked by plaque is a common challenge for medical professionals. Known as stenosis, the condition restricts blood flow to the heart, resulting in symptoms such as shortness of breath and chest pain. It is sometimes resolved using stents – small, tubular meshed structures that treat blocked arteries. They are usually placed in the coronary artery and expanded with a balloon catheter to keep the artery open, as depicted in How a stent works. While stents are successful at holding arteries open, an artery can close again with excessive tissue growth over the stent. This is called restenosis and although it is the body’s
A. Plaque in a vessel restricts the flow of blood. B. A stent has been placed at the blockage and expanded. C. The blood flow returns to normal. The center block provides a close up of the stent and vessel wall. The square on the right provides a cut away of a stent leg.
natural healing response, it impedes recovery. Thus, drug-eluting stents were developed to deliver medicine which acts to reduce cell proliferation and prevent the unwanted growth into the artery tissue. Some stents contain a coating composed of medicine and a polymer matrix that provides a controlled delivery. Each strand of the stent mesh is surrounded by this coating. Stent designs have improved significantly in recent years in an effort to reduce restenosis rates, but much remains unknown regarding the drug release process.
Drug release behavior
Travis Schauer, Ismail Guler, and a team of other engineers at Boston Scientific, a company that develops devices and technologies to diagnose and treat a wide range of medical conditions, have sought to better understand the mechanism of medicine release with computer simulation. Using COMSOL Multiphysics, they have modeled a stent coating to investigate the release profile (the rate at which the medicine diffuses out of the coating and into the vessel tissue) and the influencing factors. They used the Optimization Module in the software to fit their simulation as closely as possible to experimental data curves. “By gaining knowledge of the underlying mechanisms and microstructure of the coating, we are able to understand the release process and tailor it to achieve a desired microstructure of the coating and achieve a desired profile,” said
The coating microstructure prior to release appears on the left and the interconnected empty pores surrounded by the polymer matrix following the release from the coating are on the right.
Schauer. This may ultimately lead to a level of control over the release that has until now been impossible. The stent coating that Schauer and Guler modeled is a microstructure with two layers or phases: a medicine rich, surface-connected phase and a phase with drug molecules encapsulated by a polymer. The development of this microstructure is affected by the solubility of the drug, the drug-to-polymer ratio, and the processing conditions during manufacturing. When the stent is inserted into an artery, the medicine-rich phase quickly dissolves and diffuses into the tissue, leaving behind interconnected cavities (pores) in the polymer coating, as depicted in the accompanying photographs. Meanwhile, the molecules encapsulated by the polymer diffuse more slowly.
Modeling medicine delivery
Schauer and Guler idealized the complex geometry of the coating microstructure. In their model, the coating consists of a pattern of cylindrical pores filled with solid medicine surrounded by a polymer shell containing the dissolved drug and solid drug encapsulated by the polymer. The molecules diffuse radially and axially, but the microstructure geometry only changes radially, at the boundary between shell and pore. Therefore, a 2D axisymmetric model was sufficient. The
The sketch provides an idealized microstructure of the stent coating, with a single pore in the center. The labels R refers to the pore radius and t to the shell thickness.
simulation software let Schauer and Guler easily customize their model. “We focused on understanding the transport phenomena at hand instead of spending time on cumbersome programming,” Schauer remarked. “We customized the underlying equations according to our needs directly through the user interface.” They performed simulations for two release profiles, in vitro and in vivo cases, seeking a description of the cumulative release of the medicine. “We wanted to understand why certain release profiles were observed,” said Guler and Schauer. “We compared experimental data to the release profiles generated in our simulations to confirm our findings.”
The two scientists then tracked the dissolution of solid drug and the diffusion of dissolved drug. As it dissolves within the pores, the pores fill with liquid media from the surrounding tissue. The medicine has a different solubility limit in the liquid media than it does in the polymer, which results in a discontinuity in the dissolved medicine concentration at the interface between pore and shell. As Guler explained, “Appropriate interface conditions were easily implemented in COMSOL using a stiff-spring method, which ensured the continuity of the diffusive flux.” The customizable boundary conditions available in the software let Schauer and Guler easily add the necessary terms. Certain model parameters had to be estimated because they were ‘effective’ values that could not be measured directly, such as the polymer shell thickness. Another was the retardation coefficient that accounts for the twisted shape and constriction of the pores, steric effects, and other potential influences on the diffusion through the pores. These parameters were refined using the software’s Optimization Module.
Simulation results alongside experimental results show release curves for the in vitro and in vivo cases.
Schauer and Guler made an initial guess for the shell thickness and retardation coefficient, based on experimental kinetic drug release (KDR) data. They compared the model’s predicted release profile to the KDR curves. Based on the results, the Optimization Module modified the shell thickness and retardation coefficient to obtain a best fit between the model results and the experimental data. The release curves in Similated results plotted with experimental results confirm that the medicine in the pores releases quickly, while the dispersed molecules in the shell diffuse slowly through the encapsulating polymer. The results in Predicted medicine concentrations depict the faster dissolution and diffusion in the pore, compared to the shell.
Future stent studies
The predicted medicine concentration are for the in vitro case after two hours. C/Cs is the dissolved drug concentration/solubility limit. S/S0 is the solid-drug concentration/initial solid-drug concentration.
Reducing restenosis rates is an ongoing goal that is greatly aided by drug-eluting stents. The modeling approach employed by Schauer and Guler offers valuable insight into one type of release mechanism. Although the simplified microstructure model does not capture all the details of the release curves, the pore-shell simulation showed good agreement, lending confidence to the appropriateness of their idealized model. Using a diffuse-interface theory, researchers at the FDA are developing even more comprehensive simulations to examine the microstructure formation. These models aim to explain the relationship between processing, microstructure, and release behavior in controlled systems. Ultimately, simulation has the potential to give medical device designers more control over the delivery process and improve treatment for patients with cardiovascular disease.
