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Research Directions Quantum Technologies

How can quantum technologies be applied in healthcare, medicine and the life sciences?

Frederik F. Flöther, Paul F. Griffin

Published Jan 1, 2023• 17 citations
Publisher

Abstract

Quantum technologies, including computing, communication/security and sensing, have significantly advanced over the last years. Industry-specific applications are now being intensely researched and healthcare, medicine and the life sciences represent one of the focus areas.
DOI
10.1017/qut.2023.1

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The interdisciplinary field of quantum computing has garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to cutting-edge computational capabilities.However, despite its potential, the full extent of quantum computing's impact on healthcare remains largely unexplored.This white paper explores the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization thus, providing a panoramic view of the quantum computing[1] paradigm for healthcare.
Quantum computing, an interdisciplinary area that processes data in fundamentally different ways, has recently grown and attracted a lot of attention from academics and businesses alike because of its potential to achieve computational powers that were previously unimaginable. Quantum computing's potential in the medical field has not been thoroughly explored as yet. Computing at the quantum level has the potential to revolutionize computationally intensive healthcare applications such as personalized medicine, drug discovery, medical imaging, DNA sequencing, and operational optimization. This review article provides the first all- encompassing examination of the many applications of quantum computing to healthcare systems, focusing on these specific domains. Many different areas are covered by our taxonomies, such as foundational and enabling technologies, applications, needs, architectures, security, open problems, and potential avenues for future study. The outcome of this thorough literature study is an all-encompassing perspective on the quantum computing paradigm as it pertains to healthcare. Synthetic intelligence (AI) and quantum computing are about to converge, and this article delves into how that can change the face of healthcare. In this study, we take a look at how quantum physics might help us understand how to improve AI for faster drug development, more precise clinical diagnostics, and more tailored treatment plans. The investigation probes the means by which molecular-level quantum simulations can represent complicated organic processes, enabling the unprecedented prediction of treatment interactions and the design of medicine. Also covered in the article is the idea of using quantum sensors in conjunction with AI to provide better clinical imaging that can pick up on more widespread problems. Highlighting its role in bringing in a new technology of personalized medicinal drug and efficient drug improvement, this synergy is discussed for its transformational power.
In recent years, the interdisciplinary field of quantum computing has rapidly developed and garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to hitherto unattainable computational capabilities. However, despite its potential, the full extent of quantum computing’s impact on healthcare remains largely unexplored. This survey paper presents the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization. Through a comprehensive analysis of existing literature, we have developed taxonomies across different dimensions, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, providing a panoramic view of the quantum computing paradigm for healthcare. Our survey aims to aid both new and experienced researchers in quantum computing and healthcare by helping them understand the current research landscape, identifying potential opportunities and challenges, and making informed decisions when designing new architectures and applications for quantum computing in healthcare.
The field of quantum computing has rapidly evolved in an interdisciplinary approach, calling for significant attention from academia and industry alike in recent years. This interest is largely due to the fact that quantum computers utilize the principles of quantum mechanics to compute and manipulate information, which offers capabilities and speeds (for specific, particularly complicated) computations that are beyond the capabilities of traditional computers. While the potential of quantum computing offers much promise, it has not yet been fully explored within the health care sector; the field remains in its early stages of development. This work investigates the impact of quantum computing on modern health care systems by focusing specifically on its transformative potential in performing computationally- intensive tasks such as drug discovery, precision and personalized medicine, DNA sequencing strategies, high-definition medical imaging, and managing health care operations more efficiently. In addition, this survey presents an all-encompassing view of how quantum computing will be used in healthcare and will serve as an excellent resource. The survey intends to promote greater insight into the state of the current research landscape while identifying critical opportunities and deficiencies that impact future decisions regarding the development of nextgeneration quantum-enabled healthcare solutions.