Videos

Agent-based modeling of cells in tissues to understand and predict disease

March 28, 2017
Abstract
The most prevalent, devastating, and complex diseases of our time, such as diabetes, cardiovascular disease, and infectious diseases, result from the interactions of heterogeneous cells with one another and with their environment. However, the emergence of disease from these interactions at the multi-cell level is still poorly understood, and drugs typically target single molecular pathways while disregarding how cellular heterogeneities might affect drug efficacy at the tissue-level. To address this void, we develop new computational tools in combination with experimental approaches in order to integrate and predict how individual cell behaviors dynamically give rise to physiological and pathological tissue-level adaptations. Leveraging the versatility and adaptability of agent-based modeling, we have simulated structural adaptations of large and small blood vessels, skeletal muscle regeneration following injury, and immune cell trafficking and differentiation during inflammation and infection. Our studies have suggested new mechanistic hypotheses and provided guidance for the design of novel therapies.