Modeling of gene therapy for regenerative cells using intelligent agents

Gene therapy is an exciting field that has attracted much interest since the first submission of clinical trials. Preliminary results were very encouraging and prompted many investigators and researchers. However, the ability of stem cells to differentiate into specific cell types holds immense potential for therapeutic use in gene therapy. Realization of this potential depends on efficient and optimized protocols for genetic manipulation of stem cells. It is widely recognized that gain/loss of function approaches using gene therapy are essential for understanding specific genes functions, and such approaches would be particularly valuable in studies involving stem cells. A significant complexity is that the development stage of vectors and their variety are still not sufficient to be efficiently applied in stem cell therapy. The development of scalable computer systems constitutes one step toward understanding dynamics of its potential. Therefore, the primary goal of this work is to develop a computer model that will support investigations of virus' behavior and organization on regenerative tissues including genetically modified stem cells. Different simulation scenarios were implemented, and their results were encouraging compared to ex vivo experiments, where the error rate lies in the range of acceptable values in this domain of application.