Predictive Modeling and Experimental Control of Macrophage Pro-Inflammatory Dynamics

Macrophages are immune cells which play a key role in the reaction to biomaterials. They exhibit a functional phenotype (or state) induced by the stimulus received and conditions of the microenvironment. This polarization process is governed by specific cytokines that are released by the macrophage itself, as well as produced by other cellular activation mechanisms. Cytokines act as phenotype markers within a heterogeneous range whose extremes are historically identified as pro-inflammatory or M1 and anti-inflammatory or M2. In such a context, this work aims to propose a predictive modeling approach for the simulation of the response to a pro-inflammatory stimulus in macrophages. This will allow us to subsequently simulate the immune reaction induced by the presence of biomaterials at the cellular level, with the final goal to build a digital twin of the inflammatory response in a foreign body reaction. To do that, existing Ordinary Differential Equation (ODE) and Agent Based (AB) models have been considered and validated with in-vitro experimental data. Preliminary results highlight a better agreement of the AB approach over the ODE models taken into account in this work. This specific scheme is making simplified assumptions on spatial resolution and diffusion of inflammation (both cytokine and macrophages). However, the good agreement that we have observed in this simplified model encourages the use of a more advanced and comprehensive hybrid simulation platform based on AB modeling which implements a more thorough description of the intracellular pathways and the microenvironment.