MAST: A Multi-Agent based Spatio-Temporal Model of the Interaction between Immune System and Tumor Growth Feeded with Single-Cell Data
In recent years, single-cell technologies, both at imaging and sequencing level, have given the possibility to observe how tissues and organs are spatially and temporally organized as a system of multiple cells, able to communicate and interact with each other.
In this context, multi-agent based spatial models could present an interesting approach for developing personalized medicine strategies, for their ability to simulate complex systems of different types of cells, stochastic behavior and interaction among cells. Moreover, if coupled with partial differential equations, dependency of cell behavior on concentration of communication molecules and nutrients can be also modeled.
I will present a model of the interaction between immune system and tumor growth and will show how it can be used with patient-specific single-cell RNA-sequencing and imaging data to drive therapeutic decision.