Investigating Immune System Aging: System Dynamics and Agent-Based Modeling

dynamics, system dynamics, agent based simulation System dynamics and agent based simulation models can both be used to model and understand interactions of enti-ties within a population. Our modeling work presented here is concerned with understanding the suitability of the differ-ent types of simulation for the immune system aging prob-lems and comparing their results. We are trying to answer questions such as: How fit is the immune system given a cer-tain age? Would an immune boost be of therapeutic value, e.g. to improve the effectiveness of a simultaneous vaccina-tion? Understanding the processes of immune system aging and degradation may also help in development of therapies that reverse some of the damages caused thus improving life expectancy. Therefore as a first step our research focuses on T cells; major contributors to immune system functionality. One of the main factors influencing immune system aging is the output rate of naive T cells. Of further interest is the num-ber and phenotypical variety of these cells in an individual, which will be the case study focused on in this paper. 1