Computer Sciences and Information Technology

Title :

Mechanistic modeling of the SARS-CoV-2 and immune system interplay

Area of research :

Engineering Sciences, Life Sciences & Biotechnology, Computer Sciences and Information Technology, Mathematical Sciences, COVID-19 Research

Focus area :

Modelling of COVID-19

Principal Investigator :

Dr Mohit Kumar Jolly, Assistant Professor, Indian Institute of Science (IISc), Bengaluru

Timeline Start Year :


Contact info :


Executive Summary :

The disease caused by SARS-CoV-2 is a global pandemic that threatens to bring long-term changes worldwide. Severe symptoms such as pneumonia and Acute Respiratory Distress Syndrome can be caused by tissue damage mostly due to aggravated and unresolved innate and adaptive immune response, often resulting from a cytokine storm. However, the mechanistic underpinnings of such responses remain elusive, with an incomplete understanding of how an intricate interplay among infected cells and cells of innate and adaptive immune system can lead to such diverse clinicopathological outcomes. Dynamical systems approach to dissect the emergent nonlinear intra-host dynamics among virally infected cells, the immune response to it and the consequent immunopathology. By mechanistic analysis of cell-cell interactions, we have identified key parameters affecting the diverse clinical phenotypes associated with COVID-19. This minimalistic yet rigorous model can explain the various phenotypes observed across the clinical spectrum of COVID-19, various co-morbidity risk factors such as age and obesity, and the effect of antiviral drugs on different phenotypes. It also reveals how a fine-tuned balance of infected cell killing and resolution of inflammation can lead to infection clearance, while disruptions can drive different severe phenotypes. These results will help further the case of rational selection of drug combinations that can effectively balance viral clearance and minimize tissue damage simultaneously

Organizations involved