The world is on the cusp of a new era of computing with the advent of quantum technology, a highly touted but abstract branch of engineering with the potential to transform the healthcare industry that has yet to be fully leveraged in real-world applications.
Near-term uses run the gamut from streamlining clinical trials to optimizing back-end functions for payers and providers, and could start being used in practice as early as the next few years.
“I’m loath to put an exact timeframe — is it a year? Is it two years, three years to get in production? But we’re seeing real results today that say this is going to be tractable in the near-term,” Christopher Savoie, CEO of quantum software developer Zapata Computing, told Healthcare Dive.
Quantum computers, which are exponentially faster and more capable than classical ones, hold promise to reshape the entire industry, with proponents suggesting they could save the system hundreds of billions of dollars while improving patient care.
Earlier this year, academic medical giant Cleveland Clinic inked a decadelong partnership with IBM in which the computing giant provides two quantum computers, engineers and training for the clinic’s new research center studying genomics, emerging pathogens, virus-related diseases and public health threats. Until this deal, IBM had only installed quantum systems at its own facilities.
The joint venture is still in the planning stages, but projects are expected to get off the ground this year, Lara Jehi, chief research information officer at Cleveland Clinic, told Healthcare Dive.
To some industry watchers, the partnership proves established medical interests are taking serious interest in quantum’s near-term ability to tackle currently intractable problems in computing.
“I think we’re talking single digit years. We’re not talking decades,” Jehi said. But “particularly when you’re talking about healthcare, where nobody knows what the applications are, the whole thing is an exercise in learning.”
Today’s computers use bits, a stream of pulses that exist as either zero or one, to store data and solve problems. Quantum computers differ from traditional computers in that they use quantum bits called qubits — typically subatomic particles such as electrons or photons — which can exist as both zero, one, or zero and one at the same time.
The ability to be in multiple states at the same time, called superposition, along with a phenomenon called “entanglement,” in which two paired qubits exist in a single quantum state, allow quantum computers to perform numerous calculations at the same time and grants them tremendous computational processing power.
Because of this, quantum computers are adept at running simulations, especially those requiring large combinations of different variables. This ability makes them broadly applicable in the healthcare and pharmaceutical spaces.
In the near future, for pharmaceuticals, quantum could be applied to improve patient selection and design in clinical trials, more quickly generate new molecules with a desired set of biological properties, better predict drug response and speed a drug’s time to market, even for various diseases that can’t be treated yet, some experts say.
Clinical trials are one key area where quantum-enabled algorithms may have the biggest impact. Estimates vary, but it can take 10 years and billions of dollars to complete the process from drug discovery to commercialization.
Clinical trials are still conducted in a manual way, and there isn’t a lot of competition to make them more computationally savvy, despite the high price tag and slow timeline, according to experts.
That’s one key area where quantum could be leveraged earlier, as drugmakers have reams of data from trials that have already been completed. A handful of companies, including North Carolina-based Cloud Pharmaceuticals, California-based ApexQubit and XtalPi, are already using quantum technologies for drug discovery and development, many in partnership with quantum manufacturers like IBM and Google or pharmaceutical giants like GlaxoSmithKline or Pfizer.
Given the potential, McKinsey estimates global pharma spending on quantum computing in R&D to be in the billions by 2030.
”It’s the boring day-to-day stuff that’s really going to have the most ROI in the near term, just because of the nature of the math. But it’s arguably going to have greater economic impact,” Savoie said.
Similarly, quantum could optimize functions in healthcare administration for both payers and providers, in areas like patient matching and scheduling, assigning patients to beds, cutting down on unnecessary diagnostic testing, optimizing time on an MRI machine and imaging.
For example, adding quantum computing to a type of deep learning called generative adversarial networks, or GANs, can be used to fill out sparse data in imaging for rare diseases, Savoie said.
Take a situation where to train neural networks to identify a specific, rare form of lung cancer, researchers need 10,000 MRI scans of the cancer, but they don’t have enough data. Using quantum-enabled GANs, researchers can deep fake additional scans, adding realistic synthetic examples to that dataset and resulting in a highly accurate algorithm for identifying that rare cancer.
Quantum’s power also allows it to process imagery — which requires significantly more processing power than traditional datasets — at scale. This ability could allow clinicians to more quickly analyze images, such as CT scans, and identify any anomalies, resulting in a faster diagnosis and improved patient care.
“Multi-factor optimization problems — those are the types of things that quantum will be good at,” said Matt Kinsella, managing director at Maverick, the VC arm of $8 billion hedge fund Maverick Capital that has invested in quantum computing technology.
Looking farther out
Eventually, some say quantum technology could be used to design a drug without having to test it on any animals or patients, though developers are wary of putting a timeline on such futuristic applications.
“It’s a bit too early for us to go deep into specific applications or verticals,” a representative for Google’s quantum research team told Healthcare Dive. “For the next few years the team will really be focused on just building the first practical quantum computers.”
In 2019, Google’s computer — thought to be one of the most advanced in the world — used 53 qubits to complete a task in 200 seconds that researchers estimated would take more than 10,000 years on a classic machine.
Even the fastest quantum computers today have no more than 100 qubits, which (though extremely powerful) is still limited compared to what quantum machines will be capable of in the future, researchers say.
“There’ll be some really cool breakthrough stuff that’s going to happen in the early part of drug discovery, but that’s later on, because of the number of quibits it’s going to use,” Savoie said. “The change-the-world stuff, the stuff that’s really cool for a headline, is in that early discovery area.”
The number of qubits required to do something like “in silico” clinical trials, meaning that no humans, animals or even cells are required for testing a therapy or drug — instead, an individualized computer simulation develops and evaluates it — is likely in the tens of thousands or even millions of qubits, experts say.
Investors are enthused about the idea — one France-based startup in the space, Aqemia, has brought in almost $2 million in funding since its founding in 2019 —, but it’s quite far off and impossible with current technology, Kinsella said.
Creating completely simulated clinical trials would have major benefits over current “in vivo” trials in almost every aspect, including price, time, accuracy and human impact.
“That’s kind of a pie in the sky kind of thing. But it’s actually going to be real, we’re going to be able to do —eventually — some really good quantum chemistry that really helps in the early stages of drug development,” Savoie said. “But unfortunately the number of qubits for that one are a bit farther down the road.”
Another more futuristic application would be augmenting clinical decisionmaking, an area where physicians are already quite leery of algorithms. But quantum’s ability to process more factors more quickly means doctors could pull in more variables to determine which therapy would best help a patient, including socioeconomic, gender and even financial data.
That ability, to more speedily parse through accumulated medical data and identify correlations, could allow doctors to make decisions on a more granular basis. However, quantum-enabled algorithms if used today would still face the problems existing algorithms do, including a preponderance of unreliable clinical datasets.
”I think it’ll happen but I don’t see it happening now,” Cleveland Clinic’s Jehi said. “The accuracy of computational models based on clinical data that’s easily accessible hasn’t been that great.”
But despite the futuristic nature of quantum computing, experts expect the tech will start to be used in real-world settings in the next few years, resulting in major medical and cost benefits. And even leaders in the field can’t say for certain what exactly quantum could make possible beyond that.
“What probably gets me the most excited about quantum is — this is a broad statement — but we don’t even know what’s going to be possible and that’s what’s most exciting,” Kinsella said. “It’s quicker on the horizon than you might think.”