We analysed the global research landscape associated with the application of quantum technologies to the life sciences, focussing on quantum computers and simulators. We highlighted current developments and trends, opportunities and challenges, and initiatives and activities to help enable the ecosystem in the future. We carried out the research using a detailed literature review, stakeholder interviews and a comprehensive scientometric analysis.
We analysed the global research landscape associated with the application of quantum technologies to the life sciences, focussing on quantum computers and simulators. We highlighted current developments and trends, opportunities and challenges, and initiatives and activities to help enable the ecosystem in the future. We carried out the research using a detailed literature review, stakeholder interviews and a comprehensive scientometric analysis.
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 combination of Quantum Technologies and Artificial Intelligence (AI) is shaping a new approach in life sciences and healthcare. The growing complexity of biomedical data, along with the demand for quick and precise decision-making, has led to the exploration of new computing methods beyond traditional systems. AI has shown great success in medical diagnosis, disease prediction, drug discovery, and healthcare analytics. However, traditional AI models have drawbacks when it comes to optimization, scalability, and computational efficiency. Quantum technologies offer new computing principles based on quantum mechanics, allowing for parallel processing and better optimization. This review provides a detailed look at recent progress in quantum technologies and AI applications within life sciences and healthcare. The paper examines the basics of quantum computing, quantum-inspired algorithms, and hybrid quantum-AI frameworks, emphasizing their uses in disease diagnosis, medical imaging, genomics, molecular modeling, and drug discovery. It also discusses current challenges, practical limitations, and future research directions. This review aims to give researchers, students, and practitioners a clear understanding of the developing quantum-AI landscape and its potential effects on future healthcare systems.
Quantum computing has heralded a new era of computational capabilities, enabling the resolution of complex problems that are intractable for classical computers. The health care sector, renowned for its data-rich and computationally intensive challenges, stands to benefit significantly from quantum-based algorithms. This research paper surveys the current landscape of quantum algorithm applications in health care, emphasizing their potential in simulation modeling, decision support, adversarial robustness, and cross-domain recommendations. By integrating findings from recent literature, this survey critically examines both the opportunities and limitations inherent to quantum-driven approaches in health care. The paper provides an in-depth literature review, methodology for categorizing quantum algorithmic applications, a discussion of empirical and simulated results, and concludes with insights for future research. This work aims to serve as a comprehensive reference for researchers and practitioners seeking to understand and develop quantum-based solutions in health care.
Quantum computing has evolved from a largely theoretical discipline into a field of growing interest for commercial and industrial applications. Recent advances in quantum hardware, algorithms, and cloud-based access have enabled early experimentation outside academic environments, raising questions about its potential impact on real-world decision-making and operational problems. This paper provides an overview of the current state of quantum computing with a focus on its emerging relevance in commercial contexts. It examines the categories of problems that have attracted attention from industry, particularly those involving high combinatorial complexity such as optimization, scheduling, logistics, and resource allocation. The analysis also reviews the global landscape of companies and initiatives engaged in quantum computing, highlighting different technological approaches, maturity levels, and regional characteristics. In parallel, the paper discusses the principal challenges and limitations that constrain widespread adoption, including hardware immaturity, algorithmic readiness, cost factors, and organizational requirements. By considering both opportunities and risks, this study aims to present a balanced and realistic perspective on the role quantum computing may play in business environments. The objective is to clarify the current position of quantum computing within the broader technological landscape and to support informed interpretation of its potential, limitations, and future trajectory in commercial applications.
Quantum computing is a potentially highly-disruptive technology for several domains across the Computer Science field. However, many technological challenges still prevent the construction of a fault-tolerant and reliable quantum computer. These challenges sparked enormous interest in the scientific community, which led to the development of several independent strands of research. Consequently, research in the quantum computing domain is fragmented, making it highly specialized. This can lead to missed opportunities in identifying valuable research directions and contributions from neighboring research areas. For these reasons, this paper provides an overview of the current state of play in quantum computing for different quantum research areas at different layers of the development stack. Furthermore, for each of them, we highlight possible new outlooks that could be pivotal in the near future.