Each year in the United States alone, several hundred thousand people suffer skeletal fractures that do not heal from the original treatment, resulting in non-union. Patients with non-unions are afflicted with prolonged disability and often undergo multiple costly surgeries. To improve patient outcomes, there is a clinical need for therapeutic strategies that mitigate non-union risk by stimulating bone repair. As the primary loadbearing tissue, the skeleton dynamically adapts its structure and composition to mechanical loads, and controlled loading via rehabilitation represents a non-pharmacologic target with the potential to stimulate endogenous bone regeneration mechanisms. Prior research has demonstrated that the adaptive response of healing tissue to mechanical cues are magnitude dependent, where moderate mechanical loading potently enhances osteogenesis, but excessive loading promotes fibrosis and non-union. However, the study of mechanobiology in vivo has largely remained qualitative and these thresholds are not well defined largely because the temporal progression of mechanical conditions during dynamic activities like walking and exercise cannot be measured accurately. This technical limitation hinders the ability of researchers to investigate skeletal mechanobiology and exploit it for therapeutic purposes.

The primary objectives of this thesis were to develop technical approaches to longitudinally monitor dynamic mechanical cues during bone healing and elucidate how specific magnitudes promote repair. Our overall hypothesis was that moderate mechanical stimulation exerted via periodic ambulatory activity could enhance bone regeneration. To test this hypothesis, we engineered a fully implantable wireless strain sensor platform that enabled real-time non-invasive monitoring of mechanical cues in a pre-clinical model of skeletal repair. We used the sensor platform and image-based finite element analyses to quantify the progression of tissue-level mechanical cues during gait under varying degrees of load sharing. We discovered that early-stage strain magnitudes correlated with significantly improved healing outcomes, where tissue-level compressive strains of 2-7% imparted by moderate stiffness fixation tripled the defect bridging rate and enhanced bone formation by 60% relative to traditional higher stiffness fixation. Mechanical load sharing enhanced bone repair by promoting a mechanistic shift from primarily intramembranous toward endochondral ossification. Furthermore, strain magnitudes at later time points correlated with the status of healing, demonstrating feasibility of strain sensing techniques as an X-ray-free healing assessment. Remarkably, we also observed that osteogenic mechanical loading exerted substantial previously unexplored effects on early stage biological processes that precede mineralization, including immune cytokine signaling and angiogenesis. Load-shielded defects exhibited increased VEGF expression and vascular volume at intermediate healing time points, while immune cytokines associated with cellular recruitment, acute inflammation, and matrix synthesis were elevated by mechanical loading. These results suggest the immune response after skeletal injury is mechanosensitive and can be modulated by early mechanical loading to coordinate enhanced bone repair.

At the conclusion of the experiments, we attained a deeper understanding of how specific mechanical cues regulate bone repair in vivo, and established a novel sensor platform to further investigate mechanobiology. The knowledge gained by this thesis aids the development of integrative therapeutic strategies that stimulate bone repair via functional rehabilitation. In addition, the technological outcomes of this thesis serve as foundational support for the expanded development of implantable medical sensor technologies with broad implications to enhance diagnostics, therapeutic development, and interventional surveillance.