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In silico bone mechanobiology: modeling a multifaceted biological system

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Mechanobiology, the study of the influence of mechanical loads on biological processes through signaling to cells, is fundamental to the inherent ability of bone tissue to adapt its structure in response to mechanical stimulation. The immense contribution of computational modeling to the nascent field of bone mechanobiology is indisputable, having aided in the interpretation of experimental findings and identified new avenues of inquiry. Indeed, advances in computational modeling have spurred the development of this field, shedding new light on problems ranging from the mechanical response to loading by individual cells to tissue differentiation during events such as fracture healing. To date, in silico bone mechanobiology has generally taken a reductive approach in attempting to answer discrete biological research questions, with research in the field broadly separated into two streams: (1) mechanoregulation algorithms for predicting mechanobiological changes to bone tissue and (2) models investigating cell mechanobiology. Future models will likely take advantage of advances in computational power and techniques, allowing multiscale and multiphysics modeling to tie the many separate but related biological responses to loading together as part of a larger systems biology approach to shed further light on bone mechanobiology. Finally, although the ever‐increasing complexity of computational mechanobiology models will inevitably move the field toward patient‐specific models in the clinic, the determination of the context in which they can be used safely for clinical purpose will still require an extensive combination of computational and experimental techniques applied to in vitro and in vivo applications. WIREs Syst Biol Med 2016, 8:485–505. doi: 10.1002/wsbm.1356

This article is categorized under:

  • Analytical and Computational Methods > Computational Methods
  • Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models
  • Physiology > Physiology of Model Organisms
The dichotomy that has developed in computational bone mechanobiology research, as researchers endeavor to understand the adaptive nature of bone.
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The evolution of finite element (FE) models of bone cells from (a) idealized lacunae to (b) osteocyte geometries generated from X‐ray nano‐tomography, predicting strain amplification that has been (c) validated experimentally. Advances from (d) computational fluid dynamics (CFD) models of osteocytes with the development of (e) fluid–structure interaction (FSI) techniques, predicting velocities and shear stresses that have been (f) validated using tracer studies.
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Computational models that take various biochemical factors into account, developed by (a) Kelly and Prendergast, (b) Isaksson et al., (c) Pérez and Prendergast, and (d) Burke and Kelly, compared with experimental evidence.
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Mechanoregulation models of growth: (a) Prediction of tissue growth in a finger joint developed by Heegaard et al. provided a good prediction of (b) experimental outcomes. (c) Growth in a fracture callus under loading predicted by Garcia‐Aznar et al.
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Early tissue differentiation algorithms developed by (a) Carter et al., (b) Claes and Heigele, and (c) Lacroix and Prendergast. (d) Lacroix et al. implemented their model to predicted healing in a fracture callus.
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Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models
Physiology > Physiology of Model Organisms
Analytical and Computational Methods > Computational Methods

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