Advancements in the modelling and simulation of electrically active implants, such as deep brain stimulation (DBS) and cochlear implants to treat neurological diseases and hearing impairment, require solving coupled problems that integrate accurate modelling of electric field distributions, multi-physics interactions, and multiscale phenomena. This work employs the electro-quasistatic (EQS) approximation derived from Maxwell’s equations to efficiently model low-frequency electric interactions in conductive biological tissues while integrating microscopic, mesoscopic, and macroscopic dynamics. For cochlear implants, we developed a parametric model to account for the porosity of the modiolus, the bony, conical axis of the cochlea that houses the primary neurons of the auditory pathway in the form of spiral ganglia. This novel approach provides new insights into how bone structure impacts electric field distributions in both space and time, thereby influencing spiral ganglion neuron stimulation. Combined with analyses of material heterogeneities, anisotropies, and evolving interface conditions, it enhances our understanding of optimal electrode placement and stimulation strategies. By addressing these critical factors, our work strengthens the knowledge base and supports future advances in cochlear implant therapies. In DBS, our multiscale models link mesoscopic phenomena, such as changes in firing rates in neural networks, to macroscopic outcomes, including electric field distribution and stimulation parameters, enhancing the understanding of the stimulation's impact on signal transmission in brain neural networks. A large-scale biophysical model of the striatum, a subcortical nucleus crucial for motor control, cognition, and motivation, coupled with a finite element-based advanced volume conductor model of DBS, captures the intricate interactions between stimulation fields and neural dynamics. Additionally, modelling the trimodal response of single neurons to DBS revealed key mechanisms underlying the efficacy and precision of DBS and may result in improved treatment protocols. These findings support adaptive real-time simulations and strengthen our understanding of the interrelations between tissue properties and the electric field resulting from stimulation. Ultimately, this contributes to developing more effective and safer therapies for neurological disorders.