Multi-Scale Hybrid Agent-Based Model Investigating mTORC1’s Influence on COVID-19.

COVID-19 outcomes vary widely among individuals, with most having mild illness, while a small percentage experience severe symptoms and a minor fraction death. Several treatments for COVID-19 have been proposed. One of the most promising is the inhibition of mTORC1 by Sirolimus. However, not all patients are sensitive to this treatment. To uncover the complex relations behind the heterogeneity and sensitivity of some individuals to treatments, we developed a hybrid agent-based model of the innate immune response to study the infection in the whole lung. The model includes key cells involved in the disease and critical intracellular factors such as NF-kB, IRF3, STAT1, and mTORC1. We calibrated and validated our model using literature and our own experimental data. We used it to explore different scenarios and explain our experimental results showing a positive correlation between mTORC1 activity and viral replication but a negative correlation between mTORC1 and IFN-a expression. Our initial simulations showed that mTORC1 is a master regulator of intracellular viral response and suggested novel intervention targets upstream of mTORC1. Our aim is to personalize the model and quantify the role of mTORC1 in the COVID-19 heterogeneity.

Multi-Scale Hybrid Agent-Based Model Investigating mTORC1’s Influence on COVID-19.

Monday, July 14 at 6:00pm

Sandra Annie Tsiorintsoa

"Multi-Scale Hybrid Agent-Based Model Investigating mTORC1’s Influence on COVID-19."

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