Bone is a living part of the body that can, in most situations, heal itself
after fracture. However, in some situations, healing may fail. Compromised
conditions, such as large bone defects, aging, immuno-deficiency, or genetic
disorders, might lead to delayed or non-unions. Treatment strategies for those
conditions remain a clinical challenge, emphasizing the need to better
understand the mechanisms behind endogenous bone regeneration. Bone healing is
a complex process that involves the coordination of multiple events at
different length and time scales. Computer models have been able to provide
great insights into the interactions occurring within and across the different
scales (organ, tissue, cellular, intracellular) using different modeling
approaches [partial differential equations (PDEs), agent-based models, and
finite element techniques]. In this review, we summarize the latest advances
in computer models of bone healing with a focus on multiscale approaches and
how they have contributed to understand the emergence of tissue formation
patterns as a result of processes taking place at the lower length scales