Quantum Algorithms for Healthcare – Digital Health

The field of computational life sciences can and should invest in the development of quantum algorithms today to take advantage of the near-term improvements and long-term transformative potential of quantum technology.

Technological advances have always led to breakthroughs in medicine. Robert Hooke’s detailed drawings of cells were based on his compound microscope, and the development of COVID-19 A vaccine based on computer-assisted genetic research. The arrival of quantum technology is likely to lead to another important revolution in medical science, affecting the art of the possible in life sciences and biological research.

Quantum computing is one of several sub-fields of Quantum information science (QIS), which leverages quantum mechanics to improve and enable existing technologies. In particular, quantum computers are expected to allow some large and complex systems to be modeled more accurately, efficiently, or in some cases more quickly. They show great promise as optimization tools or as engines to simulate very small things like interactions between individual amino acids. For health, life, and medical sciences to be among the first fields to benefit from upcoming advances in paradigm shift technology, experts in these fields—biologists, chemists, vaccinologists, and so on—must engage with quantum paradigm applications today.

Promising technology, still in its infancy

To realize the full potential of quantum computing, its hardware must be improved and scaled. In short, the quantum hardware available today consists of prototypes with fewer than 1,000 quantum bits or qubits, which are analogous to the qubits used in non-quantum (eg, classical) computers. Tech giants, small startups, government labs, and universities alike are currently exploring how to make better devices. Some research groups predict that it will exceed 1 million qubits as early as 2030. A quantum computer of this size will allow what is known as “large-scale” quantum computing.

Because quantum computing is based on different mathematical principles than traditional computers –Possibility versus inevitability—You must also create a new program to manage and use it. Fortunately, quantum programs and algorithms can be designed and even tested without the need for mature quantum hardware. In some cases, this is achieved through rigorous mathematical proofs. In other cases, the algorithm can be tested on the model hardware available today, or run on a quantum computer simulation on a classical machine. many organizationsIncluding Oak Ridge National Laboratoriesdedicated time and resources to create versatile software that can evolve alongside hardware.

Reimagine the future workforce

However, hardware and software are only part of what is needed to develop quantum computers specifically designed to solve the world’s most pressing problems. Researchers specializing in QIS often lack the domain knowledge necessary to apply quantum computation to other fields. For health sciences to take advantage of what will be available in 2030, biologists, geneticists, vaccinologists and other medical researchers must ensure that their knowledge is shared with teams of quantum experts. The world’s best quantum computer won’t be able to help a biologist design the next mRNA vaccine if the biologist isn’t familiar with quantum algorithms; This general lack of exposure to quantum computing is perhaps one of the biggest barriers facing QIST as a whole, but it is one that could be solved by multidisciplinary teams.

How to get started with Quantum for Health

It can be hard to imagine how advances in medicine or the life sciences would be powered by typical quantum machines. However, many of the quantum algorithms currently under development are hybrid in nature. This means that these algorithms are based on both existing “classical” computers and quantum computers, allowing for the benefit of prototype quantum devices. Even in cases where a hybrid algorithm does not work as expected, the process of trying to create a quantum algorithm sometimes leads to the discovery of a new classical algorithm, dubbed “quantum-inspired”, that is better than the original method.

Hybrid quantum algorithms and quantum-inspired algorithms are natural steps in the evolution towards pure quantum methods. However, those who invent these new algorithms often lack domain knowledge in other areas, making it difficult to translate additional algorithmic research into ready-to-use software. The importance of this intersection has not gone unnoticed. For example, the UK has set aside $8.4 billion in 2021 for experimentation In “An Enhanced Quantum Computing Platform for Pharmaceutical Research and Development” and Many pharmaceutical companies They are all partnering with quantum companies to explore quantum applications in drug discovery.

The powerful quantum devices that will enable the full realization of the potential of quantum computing may take a decade. However, we can begin to extract the benefits of the quantum revolution today by leveraging quantum algorithms in hybrid computing systems that take advantage of quantum and classical computers in tandem. The true success of these hybrid systems will also require mixed teams of quantum data scientists and life scientists to apply these systems to biological research. Not only will this identify areas that are ripe for further exploration when more quantum devices become available, but it will also help train the health research workforce in quantum computing. This integration of computing methods and multidisciplinary teams will accelerate the application of quantum computing in life sciences research and lay the foundation for the next quantum revolution.

About Kevin Vigilant, Chief Medical Officer and EVP

Dr. Kevin Vigilante is a health business leader for Booz Allen, advising government healthcare clients in the Departments of Health and Human Services, Veterans Affairs, and the Military Health System. He currently leads a group of businesses for the Department of Veterans Affairs. Kevin is a clinician who brings new ideas to health system planning and operational efficiency, biomedical informatics, life sciences and research management, public health, program evaluation, and preparedness. His work has been published in academic journals and high-profile media including the New York Times on a wide range of topics, including research innovation and informatics, tax policy and health care reform, and the care of disadvantaged people with HIV.

About Isabella Martinez, Senior Quantum Technologist

Isabella Bello Martinez is a quantum technology expert at Booz Allen specializing in strategic thinking for long-term quantum growth strategies and quantum application research. She leads the Booz Allen quantum team’s external outreach and delivery of analytical products to a variety of clients. Isabella helps clients imagine how emerging technologies will impact their business, and then helps them create the teams, policies, and practices to make that vision a reality. Isabella, who worked as an engineer, earned a Bachelor of Science from Brown University and a Master’s degree from the University of Notre Dame.

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