Introducing scale factor adjustments on agent-based simulations of the immune system

Immune system processes can be simulated using both system dynamics (SD) models based on differential equations and Agent-based (AB) models. The two approaches are intrinsically different but some methodologies have been developed to convert SD models into AB models with a variable degree of success. However, until now none of such methods have considered the use of scale factors in SD to AB model conversion. In this work, we revisited a well know SD model describing the interaction between effector T cells and tumor cells that was previously shown unsuitable for AB modeling. We introduced non-dimensional scaling factors in AB modeling and compared AB and AD simulations through a sensitivity analysis. Under this scenario, we obtained AB models that could successfully reproduce SD simulations with a reasonable number of agents and a stochastic behavior that did not compromise computer resources. In general, our results justify the introduction of nondimensional scaling factors to reproduce SD simulations with AB models