Multischaal Modellering van Kraakbeen Mechanobiologie: Inzichten in Degeneratie en Regeneratie

Osteoarthritis (OA) is a common and painful degenerative joint disease that affects millions of people worldwide. It occurs when the cartilage—the smooth tissue that cushions the ends of bones—gradually breaks down, leading to joint stiffness, swelling, and reduced mobility. Despite its prevalence, understanding degradation of cartilage in OA and how to support its repair, remains a major challenge. This PhD thesis aimed to tackle this challenge by developing computational multiscale models integrating cartilage mechanics at different length scales with intracellular biochemical processes, to provide deeper insights into cartilage degeneration and regeneration. Firstly, a comparative study of bioreactor setups was conducted to evaluate their ability to replicate physiological joint mechanics. Subsequently, a multiscale modeling workflow for articular cartilage was developed spanning from the joint-tissue scale to the cell scale down to the intracellular scale. The cellular force from cell scale finite element model was coupled with intracellular regulatory networks using a Hill's function, bridging the gap between mechanical stimulation and biochemical response of the cell. The multiscale modeling workflow was calibrated and validated with respect to an in vitro study of dynamic compression of cartilage explants. A multiscale model of the human knee joint model was then developed using the multiscale modeling workflow, to study the patho-physiology of knee cartilage following meniscectomy. The multiscale model successfully predicted catabolic responses in articular cartilage following meniscectomy. The catabolic processes followed a gradient which correlated with the gradient in mechanical loading across the thickness of cartilage. Furthermore, a novel in silico-in vitro framework was established in this thesis using a cartilage-on-chip device. Multiscale experiments were designed using the cartilage-on-chip device to study chondrocyte mechanobiology across multiple length scales, and the results were compared with predictions from the multiscale model. Finally, the multiscale workflow was implemented in a user-friendly model execution environment (MEE), providing an accessible tool for researchers to explore cartilage mechanobiology and support future applications in in silico clinical trials and patient-specific studies. This PhD thesis advances the field by integrating computational and experimental approaches, offering a comprehensive framework to study cartilage degeneration and regeneration at multiple length scales.