Enhancing dendritic cell immunotherapy for XXXX using a simple mathematical model.

@entity5 @entity19 @entity320
BACKGROUND: The immunotherapy using dendritic cells (DCs) against different varieties of @entity5 is an approach that has been previously explored which induces a specific immune response. This work presents a mathematical model of DCs immunotherapy for @entity320 in @entity19 based on work by Experimental Immunotherapy Laboratory of the Medicine Faculty in the Universidad Autonoma de Mexico (UNAM). METHOD: The model is a five delay differential equation (DDEs) which represents a simplified view of the immunotherapy mechanisms. The mathematical model takes into account the interactions between @entity5 cells, dendritic cells, naive cytotoxic T lymphocytes cells (inactivated cytotoxic cells), effector cells (cytotoxic T activated cytotoxic cells) and transforming growth factor b cytokine (T G F-b). The model is validated comparing the computer simulation results with biological trial results of the immunotherapy developed by the research group of UNAM. RESULTS: The results of the growth of @entity5 cells obtained by the control immunotherapy simulation show a similar amount of @entity5 cell population than the biological data of the control immunotherapy. Moreover, comparing the increase of @entity5 cells obtained from the immunotherapy simulation and the biological data of the immunotherapy applied by the UNAM researchers obtained errors of approximately 10 %. This allowed us to use the model as a framework to test hypothetical treatments. The numerical simulations suggest that by using more doses of DCs and changing the infusion time, the @entity5 growth decays compared with the current immunotherapy. In addition, a local sensitivity analysis is performed; the results show that the delay in time "   ", the maximal growth rate of @entity5 "r" and the maximal efficiency of @entity5 cytotoxic cells rate "aT" are the most sensitive model parameters. CONCLUSION: By using this mathematical model it is possible to simulate the growth of the @entity5 cells with or without immunotherapy using the infusion protocol of the UNAM researchers, to obtain a good approximation of the biological trials data. It is worth mentioning that by manipulating the different parameters of the model the effectiveness of the immunotherapy may increase. This last suggests that different protocols could be implemented by the Immunotherapy Laboratory of UNAM in order to improve their results.
