Tissue engineering, or regenerative medicine, is a novel field that uses various means to develop biological substitutes used to repair or even replace living tissues. Past efforts to restore healing tissues are limited, and their methods lack accuracy.
The objective of this research is to simulate and predict behaviors of bone tissue and biomaterials both separately, and collectively, as they restore form and function during tissue regeneration and wound healing processes. Not only will more effective and dependable means of analyzing tissue regeneration be developed, the properties of carbon based biomaterials that prove most advantageous in assisting tissue regeneration will be identified.
Through in vitro experiments, primary human osteoblasts and their methods of proliferation were extensively studied. RAMAN spectroscopy, X-RAY diffraction and Atomic Force Microscopy were employed to study the molecular structure of various carbon fibers of interest. Both
osteoblasts and carbon fibers were then studied collectively to understand how various material properties affected osseous tissue formation potential.
An intricate cellular automation based computer program was developed that visually and mathematical predicts osseous tissue formation. A model combining the Logistic and Malthusian Laws was developed to predict both the growth rate and overall cell population of osteoblasts with respect to time. Estimations for cellular parameters such as individual cell volume and mass were constructed and used to calculate tissue density as a function of cell population. Multivariate regression models were formulated to describe cellular behavior in terms of the structural properties of a biomaterial. Additionally, Monte Carlo simulations were performed to provide estimations of developing tissue density with respect to time and material properties.
Ultimately a very comprehensive series of theoretical models were successfully developed that can be used separately, or collectively, to provide accurate information pertaining to bone tissue dynamics. Each model’s accuracy, combined with its versatility, provide accurate information pertaining to osseous tissue formation, even when experimental data is unattainable. Through this initiative, the material properties of carbon have proven superior in both structure and performance. Any material’s ability to promote or prevent bone tissue growth can now be promptly examined through the utilization of these models.