The human knee joint is the largest and most complex joint of the human body. The interdependencies encountered in the musculoskeletal system are crucial in understanding musculoskeletal conditions. Patient-specific models are promising methods to unravel clinical diagnosis. However, as the range of medical and experimental data is expanding, it has become a challenge to integrate data in virtual models in a way that it is comprehensive and reliable for medical diagnosis. In this thesis, we focus on a novel modelling paradigms that encompasses mechanics with microscale and physiological data which aims at being practical for clinical investigation. We integrate microstructural and physiological data into articulation simulations, by investigating different biological organization levels such as organ, tissue, cellular, and molecular level. We consider synergies between in vitro data, medical imaging data and computational models, which can have a significant impact on the development of realistic simulation tools to answer clinical challenges.