The treatment of cardiovascular diseases often involves coronary stents. Even with drug-eluting stents (DES), implantation can give rise to in-stent restenosis: endothelial denudation and overstretch injuries may result in uncontrolled tissue growth and formation of obstruction to the blood flow [1]. Critical areas where such side effects occur highly depend on the shear stresses, drug distribution and inflammatory response of the artery. This work is aimed at coupling hemodynamics, tissue growth and pharmacokinetics in arteries with DES. The stented artery lumen constitutes the fluid domain, where hemodynamics and drug release are modelled. Navier Stokes equations are used to simulate blood flow and hemodynamic indicators are analyzed to predict possible areas of inflammation and thrombosis. Drug elution from the stent into the lumen is modeled by means of an advection-diffusion equation and tailored boundary conditions. We identify the solid domain with the arterial wall. Advection-diffusion-reaction equations form the basis of modeling the transport and interaction of species and drug release by direct stent contact in the vessel wall. All governing equations for the wall species are coupled to a continuum mechanical description of volumetric growth [2]. The drug concentration is coupled at the interface between the arterial wall and the lumen to account for downstream deposition of the drug. To account for the fluid domain deformation due to the volumetric growth, we apply an elastic mesh update method. Since the healing process and drug elution span a time frame of weeks, a staggered approach is derived to couple the fluid and the solid models. The method is tested in an idealized artery with a ring stent and then applied to a patient-specific stented artery. In both cases, the finite-element meshes are designed to have matching interface between the artery wall and the lumen domain. In particular, we compare the effects of drug coupling and hemodynamic indicators on the endothelium and volumetric growth. All simulations are performed by means of finite element method using FEAP and the in-house code XNS. REFERENCES [1] A. Cornelissen, et al., In-vivo assessment of vascular injury for the prediction of in-stent restenosis. International Journal of Cardiology, 388: 131151, 2023. [2] K. Manjunatha, et al. "Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation." Computers in Biology and Medicine 167: 1076