Journal of the American Medical Informatics Association
A primer for quantum computing and its applications to healthcare and biomedical research
Thomas J S Durant, Elizabeth Knight, Brent G. Nelson, Sarah Nixon Dudgeon, Seung Joon Lee, Dominic Walliman, Hobart P Young, Lucila Ohno-machado A, Wade L. Schulz
OBJECTIVES: To introduce quantum computing technologies as a tool for biomedical research and highlight future applications within healthcare, focusing on its capabilities, benefits, and limitations. TARGET AUDIENCE: Investigators seeking to explore quantum computing and create quantum-based applications for healthcare and biomedical research. SCOPE: Quantum computing requires specialized hardware, known as quantum processing units, that use quantum bits (qubits) instead of classical bits to perform computations. This article will cover (1) proposed applications where quantum computing offers advantages to classical computing in biomedicine; (2) an introduction to how quantum computers operate, tailored for biomedical researchers; (3) recent progress that has expanded access to quantum computing; and (4) challenges, opportunities, and proposed solutions to integrate quantum computing in biomedical applications.
OBJECTIVES: To introduce quantum computing technologies as a tool for biomedical research and highlight future applications within healthcare, focusing on its capabilities, benefits, and limitations. TARGET AUDIENCE: Investigators seeking to explore quantum computing and create quantum-based applications for healthcare and biomedical research. SCOPE: Quantum computing requires specialized hardware, known as quantum processing units, that use quantum bits (qubits) instead of classical bits to perform computations. This article will cover (1) proposed applications where quantum computing offers advantages to classical computing in biomedicine; (2) an introduction to how quantum computers operate, tailored for biomedical researchers; (3) recent progress that has expanded access to quantum computing; and (4) challenges, opportunities, and proposed solutions to integrate quantum computing in biomedical applications.
The use of quantum computing1 in healthcare represents a significant shift with the potential to revolutionize medical research, diagnostics, and treatment. Quantum computing can process and analyze large datasets much faster than classical computing, offering new opportunities in healthcare. This paper examines the various ways quantum computing can be applied in healthcare, such as in drug discovery, genetic research, personalized medicine, and complex disease modeling. By using quantum algorithms, researchers can identify new treatment targets and simulate the effects of drugs on human biology in ways that were previously impossible, which can reduce the time and cost of bringing new drugs to market. Quantum computing also allows for analyzing large genomic datasets2, which can help tailor treatments to individual genetic profiles. Additionally, this technology helps in modeling complex biological systems and disease processes, providing insights into the mechanisms of diseases at a molecular level and enabling the development of more effective treatments. However, integrating quantum computing into healthcare comes with challenges such as technical limitations, the need for specialized expertise, data security concerns, and ethical considerations. This paper provides a comprehensive overview of the potential applications of quantum computing in healthcare, addresses the associated challenges, and discusses the future directions of this growing field, emphasizing the importance of interdisciplinary collaboration in fully utilizing quantum technologies in medicine. In recent years, quantum computing has rapidly advanced and attracted significant interest from academia and industry due to its unique ability to process information differently, resulting in previously unattainable computational capabilities. Despite its potential, the full impact of quantum computing on healthcare has not been thoroughly explored. This survey paper provides a systematic analysis of quantum computing's various capabilities in improving healthcare systems, focusing on its potential to transform compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing4, medical imaging5, and operational optimization. Through a comprehensive review of existing literature, we have developed taxonomies6 covering different aspects, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, offering a comprehensive view of the quantum computing paradigm for healthcare. Our survey aims to assist new and experienced researchers in quantum computing and healthcare by helping them comprehend the current research landscape, identify potential opportunities and challenges, and make informed decisions when developing new architectures and applications for quantum computing in healthcare
Quantum Computing (QC) has become an interdisciplinary and fast-developing field, with a lot of interest shown by both the academic and industrial community because of its essentially new paradigm of information processing and outstanding capabilities of the quantum computer based on its innovation and a complete break with the paradigm of non-quantum computing. Although this is the future of this potential, there is very little that is known of its transformative effect in the health industry. The survey is the first attempt to give a systematic and broad overview of how quantum computing can improve healthcare, especially in compute-intensive applications like optimization of operations, medical imaging, DNA sequencing, personalized medicine, and drug discovery. The concepts covered in this chapter are comprised of foundational concepts, enabling technologies, areas of applications, system requirements, and architectural models, security, unresolved challenges and imminent research directions. This chapter takes into consideration the general outlook on the quantum computing's significance in medicine and also serves as an efficient guide for new researchers or well-established ones looking into the area. It tries to bring light into the existing research environment, point out the prospects and the challenges and achieve the guidance of the design of future quantum-driven healthcare architectures and applications.
Classical computing works by processing bits, or 0s and 1s representing electrical signals of on and off. Quantum computing employs a very different technique for information processing. It uses qubits, which can exist as both a 1 and 0 at the same time, and uses the properties of subatomic particles in quantum physics such as interference, entanglement, and superposition to extend computational capabilities to hitherto unprecedented levels. The efficacy of quantum computing for important verticals such as healthcare where quantum computing can enable important breakthroughs in the development of life-saving drugs, performing quick DNA sequencing, detecting diseases in early stages, and performing other compute-intensive healthcare related tasks is not yet fully explored. Furthermore, implementations of quantum computing for healthcare scenarios such as these have their own unique set of requirements. Unfortunately, existing literature that address all of these dimensions is largely unstructured. This research is intended to be the first systematic analysis of the capabilities of quantum computing in enhancing healthcare systems. This article is structured with the help of taxonomies developed from existing literature to provide a panoramic view of the background and enabling technologies, applications, requirements, architectures, security and open issues, and future research directions. We believe the paper will aid both new and experienced researchers working in both quantum computing and the healthcare domains in visualizing the diversity in current research, in better understanding both pitfalls and opportunities, and coming up with informed decisions when designing new architectures and applications for quantum computing in healthcare.
Classical computing works by processing bits, or 0s and 1s representing electrical signals of on and off. Quantum computing employs a very different technique for information processing. It uses qubits, which can exist as both a 1 and 0 at the same time, and uses the properties of subatomic particles in quantum physics such as interference, entanglement, and superposition to extend computational capabilities to hitherto unprecedented levels. The efficacy of quantum computing for important verticals such as healthcare where quantum computing can enable important breakthroughs in the development of life-saving drugs, performing quick DNA sequencing, detecting diseases in early stages, and performing other compute-intensive healthcare related tasks is not yet fully explored. Furthermore, implementations of quantum computing for healthcare scenarios such as these have their own unique set of requirements. Unfortunately, existing literature that address all of these dimensions is largely unstructured. This research is intended to be the first systematic analysis of the capabilities of quantum computing in enhancing healthcare systems. This article is structured with the help of taxonomies developed from existing literature to provide a panoramic view of the background and enabling technologies, applications, requirements, architectures, security and open issues, and future research directions. We believe the paper will aid both new and experienced researchers working in both quantum computing and the healthcare domains in visualizing the diversity in current research, in better understanding both pitfalls and opportunities, and coming up with informed decisions when designing new architectures and applications for quantum computing in healthcare.
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.
Quantum computing uses fundamentally different ways of information processing compared to traditional computing systems such as the use of qubits (quantum bits) and the quantum properties of subatomic particles such as interference, entanglement and superposition to extend the computational capabilities to hitherto unprecedented levels. Although quantum computing systems promise to provide exponential performance benefits in processing, the field is still in an embryonic phase with active ongoing research and development. The efficacy of quantum computing for important verticals such as healthcare—where quantum computing can enable important breakthroughs such as developing drugs, quick DNA sequencing, processing big healthcare data, and performing other compute-intensive tasks—is not yet fully explored. Keeping in view, this article explores this area and analyzes the potential of quantum computing for healthcare systems. We explore various dimensions within healthcare ecosystem where quantum computing could introduce new possibilities through higher computational speed to perform complex healthcare computations. Implementations of quantum computing in the healthcare scenarios have their own unique set of requirements. And therefore, we not only identify those key elements but also present a taxonomy of existing literature around quantum-based healthcare ecosystem, distinguishing cryptography in classical vs modern era along the way. Finally, we explore current challenges, their causes, and future research directions in implementing quantum computing systems in healthcare.