Millions of drug-eluting stents are implanted in coronary arteries worldwide, yet little is understood about how the drugs are actually distributed to the surrounding tissue. The drug coatings can cause the formation of blood clots in the arteries–an often fatal condition. Now researchers at MIT have built a computer model to predict the performance of different types of stents under a variety of conditions.
“The model allows us to change the stent–the design, dimensions, materials, drug, and the way it is released,” says Elazer Edelman, a professor of Health Science and Technology (HST) at MIT and the principal investigator of the project. “Then we can place the stent, alone or adjacent to other stents, in arteries with different diseases or in different natural states. By rapidly considering thousands of different design features, the model can do things that can otherwise not be done.”
Kinam Park, a professor of biomedical engineering at Purdue University, in West Lafayette, IN, says that Edelman is a “pioneer” in modeling drug-eluting stents–metal meshes coated with drugs, such as anti-scarring or anti-inflammatory medication. In addition to releasing drugs, the stents act as physical supports to help keep an artery open. The drugs tend to diffuse into the bloodstream at an unpredictable rate, despite many efforts to build polymer compounds to control drug release. “There are some areas with too much drug, and areas where there are no drugs,” says Park. “Tissue can be damaged, and patients can die. The model is the first to test the drug-releasing profiles of stents and is critical for the design and development of new, better stents.”
The computer model simulates the dynamics of blood flowing around a stent in order to evaluate how the drug is released from the stent and dispersed in the arterial wall. The researchers started with a two-dimensional stent and vessel design and created an algorithm that solves the fluid-flow and drug-delivery equations for each tiny segment of the domain. Now, they can do 3-D simulations to better show the stent’s drug-eluting profile.
“The model can show exactly what the drug distribution is as a function of time,” says Park. So researchers can model the different states of the arteries, visualizing where the drug will be deposited and what will happen.
The mathematical model allows the researchers to change the parameters of the program, such as the stent configurations, the materials, the shape of the blood-vessel wall, and the drug-flow properties, so that they can test different experimental conditions. “We created an automatic algorithm so that we have the flexibility to visualize different elements without having to start from scratch,” says Vijaya Kolachalama, a postdoctoral associate at HST working on the program. (There are currently only four drug-eluting stent designs that are approved by the U.S. Food and Drug Administration.)
A simulation yielding optimal drug-releasing properties could let researchers know what drug to discharge and in what fashion, says Park. “It’s a model for building next-generation stents.”
The model has been “eye opening,” says Edelman. “It is surprising how often the drugs don’t penetrate or deposit where expected.” He compares the blood flow across a stent to white-water rapids flowing over a rock: some of the water strikes the base, flies up in the air, and comes back down, instead of flowing over the rock. So the water continuously recirculates in the same area, making the design of a stent “critically important.”
Parts of the computational findings have been validated by animal and in vitro models. The work was recently published in the Journal of Controlled Release and is funded by the National Institute of Health.
As stents become more sophisticated, Edelman says, there is a huge gap between how researchers think the devices work and how they actually behave in animal models and humans. Trials in live subjects can be costly and time consuming, and in some cases they even result in death.
The MIT researchers are pushing to make computer modeling part of the FDA regulatory process and have made their algorithms available to others so that the software can evolve.
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