Understudied factors in drug-coated balloon design and evaluation: A biophysical perspective

Abstract

Drug-coated balloon (DCB) percutaneous interventional therapy allows for durable reopening of the narrowed lumen via physical tissue expansion and local anti-restenosis drug delivery, providing an alternative to traditional uncoated balloons or a permanent indwelling implant such as a conventional metallic drug-eluting stent. While DCB-based treatment of peripheral arterial disease (PAD) has been incorporated into clinical guidelines, DCB use has been recently curtailed due to reports that showed evidence of increased mortality risk in patients treated with paclitaxel (PTX)-coated balloons. Given the United States Food and Drug Administration's 2019 consequent warning regarding PTX-eluting DCBs and the subsequent marked reduction in clinical DCB use, there is now a critical need to better understand the compositional and mechanical factors underlying DCB efficacy and safety. Most work to date on DCB refinement has focused on designing both the enabling balloon catheter and alternate coatings composed of various drugs and excipients, followed by device evaluation in preclinical and clinical studies. We contend that improvement in DCB performance will require a better understanding of the biophysical factors operative during and following balloon deployment, and moreover that the elaboration and demonstrated control of these factors are needed to address current concerns with DCB use. This article provides a perspective on the biophysical interactions that govern DCB performance and offers new design strategies for the development of next-generation DCB devices.

Keywords: arterial disease; drug‐coated balloon; stenosis; vascular drug delivery.

FIGURE 1

Stages of DCB deployment. The DCB procedure includes balloon placement at the target site (top), balloon inflation (middle), and balloon deflation/retraction (bottom). During placement, the balloon is guided to and positioned at the site of plaque accumulation. During inflation, the plaque is compressed, and coating constituents (coating/drug) are transferred from the balloon surface to the arterial wall. During deflation/retraction, some transferred constituents adhere to/are adsorbed by the arterial wall, while some is lost to the circulation.

FIGURE 2

Interfacial mechanisms during DCB angioplasty. While the interfacial bond is formed between the coating and the artery during balloon inflation, there can be a few possible ways by which the bond failure can occur during balloon deflation.

FIGURE 3

Intrinsic shape of the balloon coatings. Image derived from scanning electron microscopy show spherical structures for shellac (a) and conical structures for urea (b). The coatings were developed at room temperature by mixing paclitaxel with the respective materials in 1:1 ratio, using a micro‐pipetting method. Nylon‐12 was used as the balloon material. Processed from data published in Chang et al.

FIGURE 4

Surface modification of balloon catheters. (a) Oxygen‐based functional groups were added to the polymer molecules present on the Nylon‐12 films by exposing them to atomic oxygen in the chamber. (b) Scanning electron microscopy images of untreated and ultraviolet‐ozone plasma treated balloon surfaces. Obtained from Azar et al.

FIGURE 5

Bench‐top studies in DCB design and evaluation. (a) Candidate DCBs could be deployed and evaluated in an ex vivo flow system, with essential system components including a pump/pressure transducer to facilitate controlled flow, a linear motor/load cell to impart/monitor axial loads, a camera to measure vessel deformation, and an access port for catheter placement in a vascular test segment. (b) Candidate coatings could also be evaluated in a uniaxial test set‐up, in which planar tissue and coatings samples are placed in controlled contact under mechanical loading scenarios that simulate the biophysical interactions operative during DCB deployment.

FIGURE 6

Physics‐based modeling of drug‐coated balloon delivery. (a) True solution for the bound drug was computed on the mesh setting with the highest density. (b) Arterial vessel concentration for bound drug for solutions based on four mesh configurations and a supervised learning model‐predicted solution were plotted as a function of cross‐sectional depth. Reproduced from Kolandaivelu et al.