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Annual reports in computational chemistry

Federated quantum machine learning for drug discovery and healthcare

Mandeep Kaur Saggi, Amandeep Singh Bhatia, Sabre Kais

Published Jan 1, 2024• 13 citations
Publisher
DOI
10.1016/bs.arcc.2024.10.007

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Quantum computing, a paradigm rooted in quantum mechanics, is poised to revolutionize healthcare by addressing computational challenges that classical systems cannot solve efficiently. With their ability to process vast datasets through superposition and entanglement, quantum computers offer new approaches to drug discovery, diagnostics, genomics, and personalized medicine. This paper examines the fundamental principles of quantum computing and its application in the healthcare domain. It examines real-world use cases such as quantum machine learning for biomarker detection, molecular simulation for drug development, and quantum optimization for healthcare logistics. Additionally, the study outlines the technological, ethical, and infrastructural challenges that must be overcome for quantum healthcare solutions to achieve full clinical integration. By assessing current research, experimental applications, and the trajectory of quantum advancements, this paper provides a roadmap for the responsible and effective deployment of quantum computing in modern healthcare systems. Keywords: Quantum Computing, Healthcare Technology, Quantum Machine Learning, Personalized Medicine, Drug Discovery, Biomarker Detection.