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School of Science Institute for
Mathematical Modeling and
Computational Science

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An integrated approach to studying transplant rejection

PI: J. Arciero (Department of Mathematical Sciences, IUPUI) , G. Raimondi (Consultant, University of Pittsburgh) 

Organ transplantation is a life-saving surgical procedure through which the functionality of an organ system can be restored. The primary challenge accompanying organ transplantation is the response by the recipient’s immune system. The immune system recognizes the transplanted tissue as a foreign material and mounts a massive immune response that destroys the transplant. Thus, there is currently a great medical need to predict the conditions that lead to transplant rejection and to determine treatments that could induce tolerance of the immune response to the transplant while preserving the immune system’s functionality.

To date, systems-based mathematical modeling has not been applied to transplant rejection, although several mathematical models have been developed for the immune response to infections. The integrated approach of the proposed project applies mathematical modeling techniques based on experimental observations and measurements in pancreatic islet cells to predict how alterations in the immune response influence the rejection of an organ transplant. In particular, the mathematical model is used to assess the effectiveness of three different methods that help to suppress the immune response triggered by an organ transplant. By identifying the most successful of the three methods to limit the inflammatory response to the transplant, this study provides a first step in predicting treatments that would induce tolerance of the immune response to the transplant while preserving the immune system’s overall capacity to fight against legitimate pathogens.