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Optimization of Drug Delivery by Drug-Eluting Stents.

Bozsak F, Gonzalez-Rodriguez D, Sternberger Z, Belitz P, Bewley T, Chomaz JM, Barakat AI - PLoS ONE (2015)

Bottom Line: However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation.We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance.The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Hydrodynamique (LadHyX), École Polytechnique-CNRS, Palaiseau cedex, France.

ABSTRACT
Drug-eluting stents (DES), which release anti-proliferative drugs into the arterial wall in a controlled manner, have drastically reduced the rate of in-stent restenosis and revolutionized the treatment of atherosclerosis. However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation. We present a framework to optimize DES design such that restenosis is inhibited without affecting the endothelial healing process. To this end, we have developed a computational model of fluid flow and drug transport in stented arteries and have used this model to establish a metric for quantifying DES performance. The model takes into account the multi-layered structure of the arterial wall and incorporates a reversible binding model to describe drug interaction with the cells of the arterial wall. The model is coupled to a novel optimization algorithm that allows identification of optimal DES designs. We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance. Paclitaxel-eluting stents perform optimally by releasing their drug either very rapidly (within a few hours) or very slowly (over periods of several months up to one year) at concentrations considerably lower than current DES. In contrast, sirolimus-eluting stents perform optimally only when drug release is slow. The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.

No MeSH data available.


Related in: MedlinePlus

Contour plots of the cost function for paclitaxel (left column) and sirolimus (right column) over the design space consisting of initial concentration in the stent polymerc0 and release timetE.The scale for the cost function representation is truncated at a maximum of 1; all values larger than 1 are colored black. The dashed magenta lines in panels A and B mark the time scales for drug unbinding. The green contour line traces , the yellow contour line , and the red contour line . The horizontal axis at the top of the plot marks the time points of 1 (h)our, 1 (d)ay, 1 (w)eek, 1 (m)onth and 1 (y)ear. Gray dots indicate evaluated designs. Optimization cases A: paclitaxel release and B: sirolimus release with baseline cocnentration thresholds. C: Paclitaxel release and D: sirolimus release with concentration thresholds reduced by a factor of 10. E: Paclitaxel release and F: sirolimus release with concentration thresholds increased by a factor of 10.
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pone.0130182.g007: Contour plots of the cost function for paclitaxel (left column) and sirolimus (right column) over the design space consisting of initial concentration in the stent polymerc0 and release timetE.The scale for the cost function representation is truncated at a maximum of 1; all values larger than 1 are colored black. The dashed magenta lines in panels A and B mark the time scales for drug unbinding. The green contour line traces , the yellow contour line , and the red contour line . The horizontal axis at the top of the plot marks the time points of 1 (h)our, 1 (d)ay, 1 (w)eek, 1 (m)onth and 1 (y)ear. Gray dots indicate evaluated designs. Optimization cases A: paclitaxel release and B: sirolimus release with baseline cocnentration thresholds. C: Paclitaxel release and D: sirolimus release with concentration thresholds reduced by a factor of 10. E: Paclitaxel release and F: sirolimus release with concentration thresholds increased by a factor of 10.

Mentions: Fig 7A shows the surface of the cost function obtained using the baseline model setup for paclitaxel elution. The plot is the result of a natural neighbor interpolation [65] of the evaluated designs indicated by the gray dots. In analogy to topographical maps (equating function value magnitude with elevation), we can describe the the cost function as a mountain range with two valleys that define two optimal regions. We will refer to the directions of increasing concentrations and release time as north and east, respectively. Three colored contours are shown in Fig 7A: the green contour line traces and thus defines the border for inefficacious designs; the yellow contour line traces and thus marks the threshold of toxicity in the media; the red contour line traces and hence demarcates concentrations above which inhibition of EC wound healing would be expected to occur. It should be noted that the interpolated surface is only as good as the underlying evaluated designs (indicated by gray dots). Even if this fact limits our ability to reach detailed conclusions in some local regions of the design space, the overall conclusions are unaffected.


Optimization of Drug Delivery by Drug-Eluting Stents.

Bozsak F, Gonzalez-Rodriguez D, Sternberger Z, Belitz P, Bewley T, Chomaz JM, Barakat AI - PLoS ONE (2015)

Contour plots of the cost function for paclitaxel (left column) and sirolimus (right column) over the design space consisting of initial concentration in the stent polymerc0 and release timetE.The scale for the cost function representation is truncated at a maximum of 1; all values larger than 1 are colored black. The dashed magenta lines in panels A and B mark the time scales for drug unbinding. The green contour line traces , the yellow contour line , and the red contour line . The horizontal axis at the top of the plot marks the time points of 1 (h)our, 1 (d)ay, 1 (w)eek, 1 (m)onth and 1 (y)ear. Gray dots indicate evaluated designs. Optimization cases A: paclitaxel release and B: sirolimus release with baseline cocnentration thresholds. C: Paclitaxel release and D: sirolimus release with concentration thresholds reduced by a factor of 10. E: Paclitaxel release and F: sirolimus release with concentration thresholds increased by a factor of 10.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4470631&req=5

pone.0130182.g007: Contour plots of the cost function for paclitaxel (left column) and sirolimus (right column) over the design space consisting of initial concentration in the stent polymerc0 and release timetE.The scale for the cost function representation is truncated at a maximum of 1; all values larger than 1 are colored black. The dashed magenta lines in panels A and B mark the time scales for drug unbinding. The green contour line traces , the yellow contour line , and the red contour line . The horizontal axis at the top of the plot marks the time points of 1 (h)our, 1 (d)ay, 1 (w)eek, 1 (m)onth and 1 (y)ear. Gray dots indicate evaluated designs. Optimization cases A: paclitaxel release and B: sirolimus release with baseline cocnentration thresholds. C: Paclitaxel release and D: sirolimus release with concentration thresholds reduced by a factor of 10. E: Paclitaxel release and F: sirolimus release with concentration thresholds increased by a factor of 10.
Mentions: Fig 7A shows the surface of the cost function obtained using the baseline model setup for paclitaxel elution. The plot is the result of a natural neighbor interpolation [65] of the evaluated designs indicated by the gray dots. In analogy to topographical maps (equating function value magnitude with elevation), we can describe the the cost function as a mountain range with two valleys that define two optimal regions. We will refer to the directions of increasing concentrations and release time as north and east, respectively. Three colored contours are shown in Fig 7A: the green contour line traces and thus defines the border for inefficacious designs; the yellow contour line traces and thus marks the threshold of toxicity in the media; the red contour line traces and hence demarcates concentrations above which inhibition of EC wound healing would be expected to occur. It should be noted that the interpolated surface is only as good as the underlying evaluated designs (indicated by gray dots). Even if this fact limits our ability to reach detailed conclusions in some local regions of the design space, the overall conclusions are unaffected.

Bottom Line: However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation.We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance.The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Hydrodynamique (LadHyX), École Polytechnique-CNRS, Palaiseau cedex, France.

ABSTRACT
Drug-eluting stents (DES), which release anti-proliferative drugs into the arterial wall in a controlled manner, have drastically reduced the rate of in-stent restenosis and revolutionized the treatment of atherosclerosis. However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation. We present a framework to optimize DES design such that restenosis is inhibited without affecting the endothelial healing process. To this end, we have developed a computational model of fluid flow and drug transport in stented arteries and have used this model to establish a metric for quantifying DES performance. The model takes into account the multi-layered structure of the arterial wall and incorporates a reversible binding model to describe drug interaction with the cells of the arterial wall. The model is coupled to a novel optimization algorithm that allows identification of optimal DES designs. We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance. Paclitaxel-eluting stents perform optimally by releasing their drug either very rapidly (within a few hours) or very slowly (over periods of several months up to one year) at concentrations considerably lower than current DES. In contrast, sirolimus-eluting stents perform optimally only when drug release is slow. The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.

No MeSH data available.


Related in: MedlinePlus