In the years to come, quantum computing will find applications in different industries - from IT and finance to transportation. Within the medical industry, quantum technology has the potential to reduce the time it takes to develop new drugs as well as speed up the computationally demanding tasks of analysing and interpreting large amounts of biological data. The new Novo Nordisk Foundation Center Quantum for Life based at the University of Copenhagen has taken up this challenge. But new quantum hardware alone will not get us there. It will require the development of an entirely new type of software – quantum software.
In the years to come, quantum computing will find applications in different industries - from IT and finance to transportation. Within the medical industry, quantum technology has the potential to reduce the time it takes to develop new drugs as well as speed up the computationally demanding tasks of analysing and interpreting large amounts of biological data. The new Novo Nordisk Foundation Center Quantum for Life based at the University of Copenhagen has taken up this challenge. But new quantum hardware alone will not get us there. It will require the development of an entirely new type of software – quantum software.
Owing to its large degree handling data in fundamentally novel manners, resulting in computational capabilities that were once unattainable, the interdisciplinary field of quantum computing has experienced a growth or increase in scope and garnered significant focus from the academic and business communities. Quantum computing holds significant potential; however, the precise manner in which it will revolutionize the future of healthcare continues to be predominantly uncertain. This chapter primarily focuses on the capacity of quantum computing to upgrade computationally demanding tasks in the medical field, interconnected in the realm of medical innovations, which encompasses pharmaceutical research, targeted therapy, genome sequencing, and next-generation sequencing. This report offers the fundamental interpretation of the various capabilities of quantum computing in propelling advancements in medical innovations. The dawn of a new age is driven by the integration of quantum computing and artificial intelligence (AI), which are set to revolutionize complex biological simulations, the analysis of genetic data, and progress in drug development. The vastness and complexity of biological data complicates the management of conventional computing tools, limiting the precision for medical advances. With AI's predictive capabilities combined with quantum computers’ high processing speeds, biological analysis and clinical applications can be rapidly accelerated. This chapter focuses on the role of machine learning in fast-tracking of drug development through molecular mechanics, which can be grouped into AI-powered approaches that aim accept to replicate the action of particles with greater accuracy and efficiency, enabling the identification of potential drug candidates more quickly. By leveraging AI-driven simulations, scientists can explore complex molecular interactions, predict the efficiency of compounds, and optimize drug design processes. Quantum-enhanced algorithms facilitate quick modeling of chemical interactions, comprehensive analysis of drug-receptor binding strengths, and high precision in pharmaceutical kinetics. Additionally, we investigate quantum-assisted deep neural nets and artificial neural networks to improve forecasting disease advancement and pinpointing potential treatment targets. These models are directed to acknowledge complicated biological processes like protein folding, epigenetic alterations, and the connections between metabolic pathways.
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.
There are signs that we are approaching a technical revolution that might take humankind’s computational capabilities to a new level. Quantum Computing leverages the principles of quantum mechanics, enabling the computational power to solve specific problems currently intractable for classical computers (e.g., cracking cryptographic keys). Since we are getting to a point where we can no longer build smaller, more powerful, more efficient devices with conventional methodologies, we need to think of new ways for technological progress. The manufacturing of microchips is reaching its limits in the use of traditional architectures. Hence, new and more advanced technologies need to address the challenges of increasing energy consumption and data processing. Connectivity, scalable architectures and concepts like Cloud Computing and Software-as-a-Service have already helped to scale computational-intense applications in the last years and have attracted the interest of IS researchers (e.g., Benlian et al. 2009 ; Benlian et al. 2018 ; Messerschmidt and Hinz 2013 ). Looking ahead to the next generation, computing will comprise technologies that enable high-performance applications far beyond today’s possibilities. One prominent example with a disruptive potential is Quantum Computing. While there are abundant open questions and directions for further developments, researchers in this area have made substantial progress in the last decade, indicating that, after medical imaging, lasers, and superconductors, another quantum-technological innovation might be approaching. We, therefore, intend to provide an overview of the current state of Quantum Computing research and outline how this new technology might stimulate research in Information Systems.
Quantum Computing often described as one of the most exciting frontiers of modern science—a field that does not just push the boundaries of technology but also reshapes how we think about solving problems. Unlike classical computers, which process information in simple 0s and 1s, quantum mechanics, allowing a single qubit to explore multiple possibilities at the same time. This gives them the potential to perform calculations that would take even today’s most powerful supercomputers thousands of years. In recent years, progress has been rapid, with breakthroughs in hardware, algorithms and applications that range from developing new medicines to strengthening artificial intelligence and tackling climate change. Yet, enormous challenges remain, such as stabilizing fragile qubits, reducing error rates, and making these systems accessible beyond a handful of elite labs. This paper explores both the promises and the pitfalls of quantum computing, offering a closer look at how it could reshape industries, global security and even the pace of human innovation in the decades ahead.
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 is a new and evolving technology that has immense potential to transform healthcare and medicine. Quantum computers, which are based on the ideas of quantum mechanics, make use of quantum bits, or “qubits,” and exploit entanglement and super positioning. As a result, quantum computers may do certain calculations and algorithms orders of magnitude quicker than traditional, “classical” computers. In healthcare, quantum computing has the potential to expedite drug discovery and development, improve diagnostic accuracy, and improve patient monitoring. In particular, by simulating medication interactions and refining molecular architectures, quantum computing may facilitate faster progress in the pharmaceutical industry. Additionally, quantum algorithms have the potential to diagnose some illnesses more quickly and accurately. Quantum computing may also be used to evaluate enormous amounts of physiological data from wearables and apps for remote health monitoring.