Quantum Machine Learning: Revolutionizing Drug Discovery

Adegoke Ayuba, Lawrence Kelvin, Terry Tera

Published Nov 3, 2023• 2 citations

Abstract

This article presents a compelling exploration into the transformative potential of Quantum Machine Learning (QML) in the realm of drug discovery. The main findings of this study underscore the profound impact of QML, as it offers a revolutionary approach to drug development. By synergizing quantum computing and machine learning, QML enables precision and efficiency at every stage of drug discovery. Its applications encompass target identification, molecular docking, pharmacokinetics prediction, toxicity assessment, and accelerated drug screening. The significance of these findings lies in the promise of expedited, cost-effective, and targeted drug development. The marriage of quantum computing and machine learning opens new frontiers for precision medicine and holds the potential to reshape the pharmaceutical landscape. This article delves into the foundational principles, real-world case studies, and ethical considerations surrounding the implementation of QML in drug discovery, illuminating its potential to revolutionize the field and improve patient outcomes.

DOI: 10.31219/osf.io/3p8s6

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