How Is Quantum Computing Being Used in Healthcare?

How Does Quantum Computing Compare with Traditional Computing?

Traditional computing is based on deterministic computing. In essence, the 1’s and 0’s, or bits, translate to specific outputs. Quantum computing is based on probabilistic computing.

“Each unit of computation, or qubit, has a continuous probability of being between 0 and 1,” says Jehi. “So, it can store a lot more information compared with a classical computer, and it can process computation much faster because it can do it in parallel rather than sequentially. They are fundamentally different.”

According to Amazon Web Services, quantum computing operates using quantum principles. Those include:

• Superposition: This concept can be visualized using waves. If two ripples are created next to each other in the water, they will overlap and create an entirely new pattern. Applied to quantum computing, if you combine two quantum states, they will create an entirely new state and, inversely, each quantum state can be represented as the combination of two or more states, according to AWS. This principle is at the core of quantum computing and enables the technology to process a large and complex number of operations in parallel at the same time.
• Entanglement: According to AWS, “quantum entanglement occurs when two systems link so closely that knowledge about one gives you immediate knowledge about the other, no matter how far apart they are.” This concept enables quantum computers to quickly solve complex problems by drawing conclusions based on the behavior of one qubit in relation to another.
• Decoherence: Defined as “the loss of information from a system into the environment,” decoherence is a challenge for quantum computing and must be considered when designing the system that supports the quantum computer.

According to Jehi, quantum computing is much more aligned with biological sciences than with classical computing.

“In its essence, it’s a much more naturalistic way of thinking about computing. In medicine, we have been trying to force nature and the human body into a black and white paradigm, whereas nature and the human body are continuous things,” she says. “Classical computing is black and white. It’s a 1 or a 0. So, in principle, it’s beneficial when studying nature and the human body to use a computation system that mirrors its continuity.”

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Enabling Medical Research and Precision Medicine with Quantum Computing

Cleveland Clinic chose to work with IBM on its quantum computing initiative due to its long-term perspective on disruptive and transformative technology. The partnership gives Cleveland Clinic access to IBM’s data sciences, engineers and researchers, allowing their teams to work with IBM’s full spectrum of computation, including high-performance computing, artificial intelligence, machine learning and quantum computing.

The partnership also involved the installation of a quantum computer on the Cleveland Clinic campus. According to Jehi, it’s the only place in the world that has a quantum computer fully dedicated to healthcare and life sciences.

“That gives us the flexibility to ask questions, take risks and be more aggressive in figuring out this technology,” she says, adding that quantum computing is pushing Cleveland Clinic to think about research questions differently.

The organization made a huge investment to obtain the quantum computer, but Jehi emphasizes that Cleveland Clinic is not adopting the technology for its own benefit, but because it sees it as the technology of the future.

“We are very interested in building teams across the spectrum of healthcare, academia and biomedical research that would be interested in partnering with us and collaborating with the focus of figuring out what quantum means for healthcare,” she says.

The health system’s main goal for the technology is to accelerate how it approaches biomedical discovery. Since announcing the Discovery Accelerator in 2021 and embarking on the 10-year partnership with IBM, Jehi says the organization has identified three pillars of quantum computing.

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The first is quantum simulations, which is quantum research that transforms a chemical formula into a 3D structure. Quantum simulations are important in fields such as drug discovery, therapeutics and immunotherapy, Jehi explains. They enable the simulation of structures that have been impossible to simulate with today’s tools.

The second pillar is quantum machine learning, which encompasses the computing that AI is not yet able to handle, whether due to models not getting past a certain threshold of accuracy or because it’s too expensive.

“The models require too much data for their input,” says Jehi. “Could quantum machine learning simplify the extent of inputs that need to go into a model to get better predictions?”

The third pillar is quantum optimization, in which quantum computing can optimize processes such as supply chains and the design of clinical trials.

“What they have in common is the ability to use quantum computing for problems that are impossible to solve with classical computing,” says Jehi.

The Technology That Supports Quantum Computing

Jehi notes that it’s not possible to adopt quantum computing without having a robust infrastructure in place.

“Quantum is tomorrow. You cannot jump there without first being in the present, and that includes AI and high-performance computing. That is the foundation that we built upon,” she says.

Having a foundation of high-performance computing and AI means that healthcare organizations also need to have robust hybrid cloud infrastructures. In addition, the organization needs the talent and a workforce with the skills to operate such complex computing. Jehi says Cleveland Clinic did a lot of education for its existing computation teams and informatics groups.

“A big chunk of the effort went into workforce development and upscaling,” she adds.

The Challenge of Quantum Computing and Cybersecurity

While quantum computing has the potential to greatly benefit research across industries, it presents a security challenge as well. Security experts anticipate that, eventually, quantum computers will be so effective that they will be able to break current encryption, leading to an alarming rise in cyberattacks.

To combat this, Congress passed HR 7535, the Quantum Computing Cybersecurity Preparedness Act, which requires that executive agencies maintain an inventory of all IT in use by the organization that is vulnerable to decryption by quantum computers. The law requires the Office of Management and Budget to develop a plan for migrating agency IT to post-quantum cryptography, which is encryption strong enough to resist a cyberattack from an advanced quantum computer.

This is an issue healthcare organizations will need to be prepared for as well, as the industry is a major target for cyberattackers.

The Future of Quantum Computing in Healthcare

While the possibilities of quantum computing in medicine and life sciences are endless, currently, industry is just scratching the surface of how the technology can be applied in medicine.

“Theoretically, in the future, quantum computing can be applied to deliver services to the patients who need them the most, when they need them the most. It can be used to prioritize different interventions,” says Jehi. “Now, health systems struggle with supply chain disruption or services that are not equally available to all their patients. Quantum computing has the promise of helping with that.”

Eventually, quantum computing can be used to gain additional insights from medical images and perhaps to diagnose diseases like cancer earlier, when they’re less of a danger to a patient, using a simple blood test.

However, Jehi explains that the technology itself needs to improve before healthcare researchers can begin to ask the questions that really matter.

“Take drug discovery, for example. Right now, we can simulate certain sizes of molecules with quantum that we cannot with AI. But to get a transformative effect, where we are discovering things that have immediate clinical translation, we are not there yet,” she says, adding that achieving that requires more research.

Jehi points out that to advance healthcare research, the field needs more qubits, better error mitigation and more predictable computation.

At the same time, she believes that the healthcare community needs to become more comfortable taking risks as well as separating research and technology from its immediate business value.

“That’s the error we made with AI in healthcare generally. We stayed on the sidelines waiting for AI to prove its value while other disciplines really were much further along than us,” she says. “We waited for others to finally demonstrate that AI can work for whatever their use cases were, then we jumped on it and said we want to use it in healthcare and are, after the fact, trying to squeeze it into what we do.”

The problem, according to Jehi, is that healthcare leaders always approached AI as a business proposition. She emphasizes that leaders can’t think of quantum computing as a business proposition but should see it as a research proposition and be comfortable figuring the technology out for themselves.

“We have to figure out what it can and cannot do so that we define the roadmap and we’re not playing catch up after the fact,” she says. Finally, the industry needs to be more proactive in thinking about the policy and governance implications of a technology as disruptive as quantum computing, particularly when it comes to the cybersecurity aspect, according to Jehi. “We should not repeat the mistakes that we made with AI,” she says.

Editor's note: This article was originally published on Sept. 27, 2023.