Speeding New COVID Treatments

Speeding/Improving COVID Treatment with machine learning

Speeding New COVID Treatments with Computational Tool

University of New Mexico, Michael Haederle, May 3, 2021 in CACM

Scientists at the University of New Mexico (UNM) and the University of Texas at El Paso have developed a computational tool to help drug researchers quickly identify anti-COVID molecules before the virus invades human cells or disable it in the early stages of infection. The team unveiled REDIAL-2020, an open source suite of computational models that can help to rapidly screen small molecules for potential COVID-fighting traits. REDIAL-2020 is based on machine learning (ML) algorithms that quickly process massive volumes of data and tease out patterns that might be missed by human researchers. The team validated the ML forecasts by comparing datasets from the National Center for Advancing Translational Sciences to the known effects of approved drugs in UNM's DrugCentral database.