The use of quantum technologies opens up new opportunities for the development of medicines, improving the quality of diagnostics, protection of medical information and personal data, increasing the efficiency of medical decision-making. The aim of the research was to study the prospects of development and application of quantum technologies in the field of healthcare. In order to achieve the goal, the analysis of separate clusters of quantum technologies with maximum prospects of commercial application in healthcare was performed; the patent landscape of the considered technological area was built; a review of market products for healthcare created on the basis of quantum technologies was prepared. It is shown that quantum sensors, quantum computing and quantum-resistant cybersecurity solutions have received maximum development in healthcare. The number of created technical solutions in the technological field under consideration, which received patent protection, is more than 6.5 thousand, of which 3.5 thousand are supported. As key beneficiaries of the use of quantum technologies in healthcare it is proposed to consider, first of all, pharmaceutical companies and biotechnology startups, which can reduce the time of modeling and testing of drugs, improve the accuracy of predicting side effects of drugs and drug-drug interactions through the use of quantum computing, accelerate the analysis of big data and optimize clinical trial protocols.
The use of quantum technologies opens up new opportunities for the development of medicines, improving the quality of diagnostics, protection of medical information and personal data, increasing the efficiency of medical decision-making. The aim of the research was to study the prospects of development and application of quantum technologies in the field of healthcare. In order to achieve the goal, the analysis of separate clusters of quantum technologies with maximum prospects of commercial application in healthcare was performed; the patent landscape of the considered technological area was built; a review of market products for healthcare created on the basis of quantum technologies was prepared. It is shown that quantum sensors, quantum computing and quantum-resistant cybersecurity solutions have received maximum development in healthcare. The number of created technical solutions in the technological field under consideration, which received patent protection, is more than 6.5 thousand, of which 3.5 thousand are supported. As key beneficiaries of the use of quantum technologies in healthcare it is proposed to consider, first of all, pharmaceutical companies and biotechnology startups, which can reduce the time of modeling and testing of drugs, improve the accuracy of predicting side effects of drugs and drug-drug interactions through the use of quantum computing, accelerate the analysis of big data and optimize clinical trial protocols.
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
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, 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.
Abstract Quantum computing hardware and software have made enormous strides over the last years1. Questions around quantum computing’s impact on research and society have changed from “if” to “when/how”. The 2020s have been described as the “quantum decade”, and the first production solutions that drive scientific and business value are expected to become available over the next years. Medicine, including fields in healthcare and life sciences, has seen a flurry of quantum-related activities and experiments in the last few years (although medicine and quantum theory have arguably been entangled ever since Schrödinger’s cat2). The initial focus was on biochemical and computational biology problems3,4,5,6,7,8; recently, however, clinical and medical quantum solutions have drawn increasing interest. The rapid emergence of quantum computing in health and medicine necessitates a mapping of the landscape. In this review, clinical and medical proof-of-concept quantum computing applications are outlined and put into perspective. These consist of over 40 experimental and theoretical studies from the last few years. The use case areas span genomics, clinical research and discovery, diagnostics, and treatments and interventions. Quantum machine learning (QML) in particular has rapidly evolved and shown to be competitive with classical benchmarks in recent medical research. Near-term QML algorithms, for instance, quantum support vector classifiers and quantum neural networks, have been trained with diverse clinical and real-world data sets. This includes studies in generating new molecular entities as drug candidates, diagnosing based on medical image classification, predicting patient persistence, forecasting treatment effectiveness, and tailoring radiotherapy. The use cases and the applied algorithms are summarized. In addition, this review provides an outlook on medicine in the quantum era. There has been much discussion about healthcare’s journey towards precision medicine and the quadruple aim (better health, lower costs, enhanced patient experiences, and improved healthcare practitioner work lives)9. While a range of technical and ethical challenges remain, quantum computing is poised to become a key enabler for advancing towards the holy grail: keeping people healthy through proactive medical care and guidance at the level of an individual.
ABSTRACT Quantum technologies, driven by principles of quantum mechanics like superposition and entanglement, have shown transformative potential in drug discovery, medical diagnosis, precision medicine, and other therapeutic interventions. However, the research on emerging quantum technologies at early to late stages of development for healthcare applications is limited. The main objective of this study was to identify emerging quantum technologies such as quantum computing, diagnostics, and therapeutics, with a focus on specific applications within healthcare, such as drug discovery, diagnosis assistance, precision medicine, and treatment interventions. We conducted a comprehensive review of this landscape by analyzing data from clinical trials, published literature, and soft intelligence sources. The analysis revealed 116 quantum technologies such as computing algorithms, therapeutics, sensors, and imaging applications that are currently in development or already in the market. Diagnosis assistance‐related technologies, including technologies such as magnetoencephalography and quantum dots, constituted the majority of the technologies, while quantum computing‐related machine learning and algorithms were significant in drug discovery and precision medicine applications. The integration of quantum technologies into healthcare faces challenges such as infrastructure demands, regulatory frameworks, and the need for professional training. However, with ongoing advancements, quantum technologies are uniquely positioned to revolutionize diagnostic accuracy, computational capacity for drug design, and precision medicine. This horizon scan highlights the current innovation landscape of emerging quantum technologies in healthcare and the challenges in facilitating the integration of these technologies into healthcare systems.
Transformative impact and change can be acquired by quantum computing in the field of medical sciences and clinical care. This chapter explores the revolutionary prospects of quantum physics, that is, superposition and entanglement, with its application in medical sciences and healthcare. Additionally, a comprehensive framework of the technology is presented in this chapter in the facets of quantum artificial intelligence applications, drug discovery, personalized treatment, biomarker discovery, and data management. The chapter examines the concepts from quantum computing to advanced healthcare from next-generation applications. Despite a transforming potential, challenges due to technical complexities, ethical and regulatory concerns, high cost, and limited accessibility from the unification of quantum computing with healthcare are also presented. A practical roadmap is discussed at the end of the chapter to integrate multidisciplinary technologies for creating smart quantum healthcare solutions. Actionable insights are offered in the section for healthcare and biomedical scientists, healthcare providers, pharmaceutical and biotechnological companies, public health management, and startup companies to dive into the possibilities that quantum computing can provide in healthcare.