Computer simulation models and visualization tools for tissue engineering

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The objective of this research is the development of computer simulation models and visualization tools to facilitate the work of tissue engineers.  Computational models with predictive abilities will greatly speed up progress in this area. Such models will help researchers predict the dynamic response of cell populations to external stimuli, thus enabling them to assess the effect of various system parameters on the rates of tissue regeneration processes, as well as on the structure and quality of the final bio-artificial constructs.  However, the simulation of tissue growth is a computationally challenging problem requiring large grids to handle the populations of discrete cells and small time steps to accurately describe the cell population dynamics. Tissue regeneration is one of the most challenging bioengineering problems today.  The current approach for treating organ or tissue failure includes transplantation, surgical reconstruction or implanting artificial devices, therapies that are limited in success. An alternative is to replace the failing tissue or organ with a biological substitute grown from the patient's own cells.  Biological substitutes must reproduce the architecture of the tissues they replace. For this reason, they are built on three-dimensional scaffolds made from suitable biomaterials.  Besides serving as the structural component, the scaffolds provide the proper shape of the bio-artificial construct and a three-dimensional matrix for guided cell migration and proliferation.  Scaffolds may also be used to promote wound healing, a serious problem with patients suffering from many debilitating diseases.  Currently, the development of tissue substitutes is almost exclusively based on empirical approaches that require many expensive and time-consuming experiments motivated by biological discoveries.  However, tissues are highly complex systems and a multitude of factors can influence their function, structure and growth rates.  These factors range from properties of biomaterials and scaffolds to the numerous external stimuli that modulate important cellular functions in ways that are still poorly understood.