Quantum Leap

Dig into a story about how high-performance computing can advance healthcare, and you’re bound to encounter some heady subject matter. Lucky for you, dear reader, this first topic is pretty straightforward.

They refer to it informally as “the chandelier.” It doesn’t take a data scientist to see why. With its impressive array of tubes and wires, the golden apparatus looks like a particularly fancy light fixture, the kind of thing that Louis XIV might’ve put in a guest bedroom at Versailles.

But this so-called chandelier isn’t designed to provide illumination — at least not in the literal sense. It’s actually the heart of a quantum computer, like the IBM Quantum System One that now stands in the center of the Lerner Research Institute on Cleveland Clinic’s main campus. Not only is this the first quantum computer in healthcare, but it’s also the first private-sector, on-site, IBM-managed quantum computer in the United States.

And it’s just the beginning. The quantum computer is the cornerstone of an even bigger and even bolder initiative: the Discovery Accelerator.

The Discovery Accelerator is an integral part of the new Cleveland Innovation District, a $1 billion endeavor that will nearly double Cleveland Clinic’s research capacity, attract and create new healthcare and technology businesses and train a high-tech workforce.

Having a hard time wrapping your head around this part? Think about flipping a coin. When it lands, it’s either going to be heads or tails. When it’s spinning in midair, though, it might be considered a little bit of both — some probability of heads, some probability of tails. This is akin to how a quantum computer processes data.

The hardware itself is beyond cool. In fact, it’s almost unimaginably cold. Put it this way: The lowest natural temperature ever recorded on Earth was minus 128.6 degrees Fahrenheit at a research station in Antarctica. But that seems downright balmy compared to the temperature at the business end of the quantum computer’s chandelier: minus 459.6 degrees Fahrenheit (or nearly absolute zero, for those of you who paid attention in chemistry class).

That’s colder than the vacuum of outer space. It has to be, to ensure that the quantum computer’s processor works correctly. The colder its qubits are, the less they move and the less they interfere with each other, which makes their data more stable and accurate.

As far as Dr. Jehi is concerned, the advantage of having a quantum computer on-site at Cleveland Clinic’s main campus can’t be overstated.

“Quantum computing is the future of how we’ll do computing for research,” she says. “Other organizations have access to quantum computing, but only through the cloud. They’re waiting in line, and the line goes on for months. It’s hard to lead in that situation. Fortunately, thanks to our partnership with IBM, Cleveland Clinic has its own quantum computer, in the middle of one of the top healthcare systems in the world.”

Remember 2001: A Space Odyssey? “Open the pod bay doors, HAL.” AI run amok!

For a more timely example, look no further than chatbots such as ChatGPT. In recent months, you’ve probably at least heard about these buzzed-about AI programs, if not tried them out for yourself. Trained on large bodies of text from the internet, chatbots can generate responses — frequently quite good, albeit sometimes flawed — for seemingly any prompt you wish to throw at them.

The terms “AI” and “machine learning” are sometimes used interchangeably, although the latter properly refers to a specific type of AI where a computer program can learn on its own, without being explicitly programmed. Machine learning employs algorithms for refining and improving performance over time.

AI is already making a difference in a variety of settings across Cleveland Clinic. In the Robert J. Tomsich Pathology & Laboratory Medicine Institute (PLMI), for example, AI is used to scan slides for signs of disease. In analyzing a pap smear or a blood smear, it can quickly detect abnormal cells.

“The goal with AI is to revolutionize how we diagnose and treat disease,” says PLMI Chair Brian Rubin, MD, PhD.

“Predictive algorithms could help, say, a person who has heart failure,” Dr. Rubin says. “With AI, we can make predictions by looking at laboratory values and enable interventions that might prevent someone from progressing to a more serious form of the disease.”

This brings us to another important point: Quantum computing isn’t going to replace classical computing. These technologies, along with AI and the hybrid cloud, will coexist and complement one another.

“At this early stage, we don’t actually know for sure which applications could potentially be solved better on quantum computers or classical computers,” says Dan Blankenberg, PhD, a researcher in the Genomic Medicine Institute at Cleveland Clinic who specializes in developing computational approaches for analyzing biological big data.

Dr. Blankenberg and his team are working with IBM on a benchmarking framework for quantum computing. This involves abstract mathematical models based on real-world problems that classical computing cannot solve, such as calculating all the ways that protein can interact in a therapeutic drug or improving the targeting of tumor cells in radiation therapy.

“Quantum computing is a completely different way to do computational tasks,” Dr. Blankenberg says. “You have to approach your problems and formulate your questions differently than you would for a classical computing system. We’re trying to better understand where quantum computing may give us an advantage over classical computing.”

For Shaun Stauffer, PhD, the Discovery Accelerator could hold the key to making the process of drug discovery more expeditious and more cost-effective.

“It’s going to change the vector,” says Dr. Stauffer, Director of the Center for Therapeutics Discovery at Cleveland Clinic, where investigators develop innovative hypotheses to help create new medicines for patients.

Traditionally, researching a potential drug could entail testing thousands of compounds before finding one whose risk factors were low enough to take to a clinical trial — a process that takes years and can cost more than $800 million.

Working closely with IBM, Dr. Stauffer and his team are aiming to streamline drug discovery by leveraging AI and molecular dynamics modeling.

“With computational science,” Dr. Stauffer says, “we have an opportunity to make smarter decisions upfront and to reduce the number of compounds that we have to synthesize to identify a clinical candidate.”

Like the GPS app on your phone that helps you navigate traffic on highways and byways, advanced computing will help scientists avoid research bottlenecks. “A big part of drug discovery is risk mitigation and risk removal,” Dr. Stauffer says. “These new tools will have embedded knowledge about what to avoid. We’ll receive a clear option that should allow us to get from point A to point B with a much higher level of confidence.”

The work of Dr. Stauffer’s team overlaps with the efforts of other Cleveland Clinic colleagues. Dr. Rubin specializes in epithelioid hemangioendothelioma (EHE), a rare cancer of the blood vessels, heretofore widely thought to be “undruggable.” Jae Jung, PhD, is the holder of the Betsy B. deWindt Endowed Chair in Cancer Biology and Director of the Global Center for Pathogen & Human Health Research, which is seeking to create broaderspectrum inhibitors to block new mutations of the coronavirus that causes COVID-19. For Dr. Rubin and Dr. Jung, the Discovery Accelerator’s capabilities in small-molecule drug discovery could have a significant impact.

“Every medical student should be exposed to some level of analyzing big data,” Dr. Mehta says. “They need to be able to handle this, because this is the digital world that we live in now.”

A pilot program — the first of its kind — has been launched at the Lerner College of Medicine, where students can take an elective to hone their skills in AI, data science and the Python computer language, the lingua franca of AI coding. The long-term vision is to eventually expand the course and make it available to a broader audience.

“We have to teach our trainees the right use of this technology, the responsible and ethical use of these tools, to translate discoveries into patient benefit,” says Dr. Moravec, Director of the Research Education and Training Center in the Lerner Research Institute.

“We’re already training people how to be good clinicians and good scientists,” Dr. Moravec says. “They already speak the language of medicine and science. Now we need to train them how to speak the language of data and computation, too.”

As Dr. Jehi likes to put it: The Discovery Accelerator par tners need to become “bilingual.”

Cleveland Clinic and IBM have a lot in common, according to IBM’s Dr. Zhou. “Both organizations have innovation in their DNA,” she says. “But we don’t always speak the same language. Cleveland Clinic speaks the language of medicine and life sciences. IBM speaks the language of computing. We still have a lot to learn from each other.”

Those learnings are poised to benefit others, too. Cleveland Clinic is a founding partner of the Life Sciences and Healthcare Quantum Innovation Hub. Spearheaded by the Washington, D.C.-based collaborative Connected DMV, this new initiative seeks to spur advances in quantum computing. As the lead healthcare system in the coalition,  Cleveland Clinic has been tapped to help define quantum computing’s role in the future of healthcare and to educate other health systems about the possibilities.

And don’t underestimate the unquantifiable power of the human touch.

“Patients will still come to us and say, ‘Doc, what do you think?’” Dr. Mehta says. “When people are at their most vulnerable and they’re scared, they want someone who has been through thick and thin with them, someone they can trust. When the rubber meets the road, we’ll always need someone who understands everything that patients are going through on a human level and can help them make the right decision.”

As the technology continues to evolve, so will the roles of the flesh-and-blood caregivers who use these tools. But how, exactly? Stay tuned.

“It’s a really important question,” says Dr. Smith of IBM.

“These advances in computing technology — quantum computing, AI and the hybrid cloud — will allow augmentation and scaling of expertise. But it’s not about replacing people. It’s about giving them more power to go faster, to go further and to understand more.”