Arteries constantly adapt to changes in the chemical and mechanical microenvironment, with vascular smooth muscle cells (SMCs) being the mediators. Although SMCs are primarily associated with short term vasoregulation, they also sense long term changes in the microenvironment and switch phenotypes to synthesize collagen, new SMCs and other extracellular matrix constituents. This not only leads to mass production, but the newly added collagen/SMC mass also has different preferred directions and stress–free reference configurations with respect to the existing tissue. The constrained mixture theory (CMT) introduced by Humphrey and Rajagopal provides a comprehensive framework to model these effects in a continuum mechanical setting. However, the CMT is computationally expensive as each constituent’s history needs to be tracked over time. Therefore its use has been limited to simple, axisymmetric geometries. A novel continuum mechanical framework is developed based on the temporally homogenized CMT, where a constituent–wise multiplicative split of the inelastic deformation gradient into a growth and a remodeling part is used to independently describe the volumetric and isochoric contributions of the adaptation. Evolution equations are formulated to model the addition and removal of mass due to chemical stimuli such as sustained, elevated SMC activation as well as local micromechanical stimuli. This enables modeling the effect of external agents such as antihypertensive drugs or growth inhibitors and analyzing their role in the long term adaptation of the arterial wall. SMC activity is modeled based on an extended Hai and Murphy model that accounts for stretch–dependent calcium dynamics and calcium sensitization. Viscoelastic relaxation is modeled using an approach similar to Sempertegui and Avril (2023) , where the constituent’s configuration evolves slowly towards its homeostatic deposition state. Algorithms for the implementation in finite element programs will be presented. Simulation results for representative boundary value problems will be shown to demonstrate the capabilities of the proposed framework.