SBIR Phase I: Rapid repurposing and translation of COVID-19 therapeutics using a AI-based biosimulation platform: application to ACE2 and Ca2+ multi-target therapies (COVID-19)

The broader impact of this SBIR Phase I project is to provide immediate positive outcomes in the COVID-19 therapeutics. The platform will use artificial intelligence (AI) to develop models describing and ultimately predicting how specific individuals respond to various therapeutic combinations. This process can be extended to other diseases and conditions. This SBIR Phase I project will utilize an artificial intelligence/machine learning-based in silico platform for optimizing combinations and dosing strategies of approved drugs as a repurposed, multi-target approach against COVID-19 to minimize the viral load, infection and replication in specific tissues. A key objective of the proposed work is to target COVID-19 replication transmission and effectively lower the net viral load, subsequently increasing clinical efficacy and patient survival. This project will develop a multiscale mechanistic model of drug-target interaction, encompassing expression levels, and interaction kinetics of therapies with signaling pathways to prevent viral infection and inflammation that can result in widespread tissue damage and increased mortality. The technology will enable, with high predictive accuracy, the selection of individuals and combinations of proposed drugs to optimize the dosage regimen that leads to a maximum therapeutic efficacy. This will further enable physicians to rapidly redeploy these therapies off-label in COVID-19 patients in the immediate term. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.