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Quantum Machine Learning in Drug Discovery

Adegoke Ayuba, Lawrence Kelvin, Terry Tera, Rose Jessica

Published Nov 7, 2023• 2 citations
Publisher

Abstract

This article explores the transformative potential of Quantum Machine Learning (QML) in drug discovery. QML leverages quantum computing and advanced machine learning to accelerate the identification of drug candidates, predict molecular interactions, and optimize compounds. Key applications include efficient virtual screening, molecular simulation, and predictive modeling. While promising, QML faces technical challenges, requiring collaboration between quantum experts and pharmaceutical researchers. In summary, QML offers a faster, cost-effective path to drug development, with the potential to reshape the pharmaceutical industry and advance medical science.

DOI
10.31219/osf.io/fqge9

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