Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation

Comput Biol Med. 2023 Dec:167:107686. doi: 10.1016/j.compbiomed.2023.107686. Epub 2023 Nov 8.

Abstract

Persistence of the pathology of in-stent restenosis even with the advent of drug-eluting stents warrants the development of highly resolved in silico models. These computational models assist in gaining insights into the transient biochemical and cellular mechanisms involved and thereby optimize the stent implantation parameters. Within this work, an already established fully-coupled Lagrangian finite element framework for modeling the restenotic growth is enhanced with the incorporation of endothelium-mediated effects and pharmacological influences of rapamycin-based drugs embedded in the polymeric layers of the current generation drug-eluting stents. The continuum mechanical description of growth is further justified in the context of thermodynamic consistency. Qualitative inferences are drawn from the model developed herein regarding the efficacy of the level of drug embedment within the struts as well as the release profiles adopted. The framework is then intended to serve as a tool for clinicians to tune the interventional procedures patient-specifically.

Keywords: Continuum growth modeling; Drug-eluting stents; Endothelium; Growth factors; Pharmacodynamics; Pharmacokinetics; Rapamycin; Restenosis; Smooth muscle cells.

MeSH terms

  • Computer Simulation
  • Coronary Restenosis*
  • Drug-Eluting Stents*
  • Humans
  • Sirolimus / pharmacology
  • Stents

Substances

  • Sirolimus