The application of quantum computing to healthcare and life sciences is expected to transform computational medical science. The US federal government has signaled that it is committed to a quantum-enabled future, and is significantly supporting this emerging field. Exciting applications of quantum technology include the diagnosis of diseases, design of pharmaceuticals, strategies for personalized medical interventions, and analysis of medical images. Below, we’ll explore some of these promising applications, establishing how today’s research in quantum algorithms could translate into tomorrow’s expanded treatment options for doctors and better outcomes for patients.
Quantum-assisted machine learning for health diagnostics and data
With the Rise of AI, What IP Disputes in Healthcare Are Likely to Emerge?
Munck Wilson Mandala Partner Greg Howison shared his perspective on some of the legal ramifications around AI, IP, connected devices and the data they generate, in response to emailed questions.
Medical diagnostics have benefited considerably from data-driven insights powered by artificial intelligence (AI) and machine learning (ML). Quantum computing is expected to further AI in medical sciences by increasing the efficiency, accuracy, or speed of some ML methods. Used to holistically analyze medical data, this could empower doctors to see new patterns in a patient’s history and suggest different (and perhaps better) treatment methods. For example, medical imaging techniques – including CT, MRI, and X-ray scans – are crucial diagnostic tools. But the resolution of these images is often limited, and tumors or other abnormalities can be missed. Quantum computing has the potential to improve the analysis of medical images, enhancing image-aided diagnostic methods and accelerating patients’ treatment timelines. Improvements such as these would lead to more effective outcomes and lower costs, as well as more time for doctors to do what matters most: care for patients.
Quantum simulation for protein-folding
Quantum technology could also dramatically improve our understanding of protein folding. In recent years, computational biologists have written impressive algorithms to model the shape of proteins. These models allow scientists to better understand the body’s natural processes by illustrating how protein folding dictates biological interactions. However, these algorithms still lack the precision necessary to achieve desired breakthroughs in personalized medicine. Future quantum computers could change that.
Scientists believe we’ll one day be able to capture the dynamics of ever larger proteins computationally, rather than experimentally, reducing the time and cost of bringing life-saving treatments to patients. Further, researchers hope to someday use the simulation capabilities of quantum computers more broadly, not only modeling protein structures, but also simulating critical metabolic processes and ensuring that therapeutics have their intended effect.
A Personalized Approach to Medication Nonadherence
At the Abarca Forward conference earlier this year, George Van Antwerp, managing director at Deloitte, discussed how social determinants of health and a personalized member experience can improve medication adherence and health outcomes.
Small-molecule drug design with hybrid quantum algorithms
Another exciting use case of quantum computing is small molecule simulation. To develop new materials and chemicals, researchers typically evaluate thousands of chemical reactions and molecular interactions. Today, quantum computers are already being used in combination with state-of-the-art neural networks to help produce candidates for small molecules—a type of biological compound that, thanks to their small size, can be quickly absorbed into the body and thus are valuable drug types. Scientists believe that a future, more sophisticated quantum computer will be able to produce viable small molecule candidates for experimentalists to synthesize and explore further. These simulations will allow biologists to focus their work on the most promising candidates, helping them to conduct more efficient and accurate experiments. The ultimate downstream effect being breakthrough treatments for providers and patients.
The future of quantum in healthcare
While quantum computing may still be a few years away from realizing its full potential, it’s gaining substantial momentum across the health and life sciences industry. With promises of more efficient and reliable diagnoses, future breakthroughs in personalized medicine and targeted therapeutics, and an expedited R&D lifecycle, industry leaders must be prepared to invest in quantum technologies to deliver better outcomes for their organizations and patients.
Photo: metamorworks, Getty Images
Isabella Bello Martinez is a Quantum Technologist at Booz Allen Hamilton who specializes in strategic thinking for long-term quantum growth strategies and quantum technologies application research. She leads external outreach for Booz Allen’s quantum team and the delivery of analytical products for a variety of clients. Isabella helps clients imagine how emerging technologies will impact their businesses, and then helps them create the teams, policies, and practices to make that vision a reality. An engineer by training, Isabella earned her ScB from Brown University and her MS from the University of Notre Dame.
