Cleveland Clinic and IBM Unveil Landmark 10-Year Partnership to Accelerate Discovery

Expediting the future of healthcare

double exposure artistic rendering of scientist and nurse, representing translational research

Artificial Intelligence. Quantum computing. Hybrid cloud. These terms can seem daunting.


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All are key to Cleveland Clinic’s new partnership with IBM. But what do they really mean and how will they help us better serve patients? Lara Jehi, MD, Cleveland Clinic’s Chief Research Information Officer, shares more on this ground-breaking collaboration.

Appreciating the scale of data and technology

It is estimated that by 2025, the amount of data generated each day by the world will be equivalent to 400 times more bytes (the data unit) than stars in the observable universe. Storing all of that data in regular computer hard drives would require more than a trillion computers. And that is just from one day.

So, some of the data is stored in internet servers, and that’s the “cloud.” Different types of clouds — depending on storage or ability to share across organizations — are what make some clouds “hybrid” and accessing all of this data referred to as “cloud computing.”

“Artificial intelligence” or “AI” is a branch of computer science that tries to replicate human intelligence through different algorithms. There are now many applications for AI in medicine: you show the machine thousands of chest X-rays, for example, and you tell it where a lung cancer is found on each of these chest X-rays, it eventually learns how to find the lung cancer itself.

But with today’s computing technology, it takes a really long time for the machine to review enough data to learn. Researchers often feel like they are trying to light a dark, mile-long hallway with candles.


“Quantum computing” turns those tiny candles into a bright lightbulb because it significantly accelerates how quickly data can be analyzed. It is in its infancy, and there is still a lot to learn about how to use it and how to control it in medicine. It’s the technology of the future.

Empowering big data medical research

Cleveland Clinic and IBM have announced a planned 10-year partnership to establish the Discovery Accelerator, a joint Cleveland Clinic – IBM center with the mission of fundamentally advancing the pace of discovery in healthcare and life sciences through the use of high performance computing on the hybrid cloud, artificial intelligence and quantum computing technologies.

The collaboration is anticipated to build a robust research and clinical infrastructure to empower big data medical research in ethical, privacy preserving ways, discoveries for patient care and novel approaches to public health threats such as the COVID-19 pandemic. Through the Discovery Accelerator, researchers plan to use advanced computational technology to generate and analyze data to help enhance research in the new Global Center for Pathogen Research & Human Health, in areas such as genomics, single cell transcriptomics, population health, clinical applications, and chemical and drug discovery.

Asking critical medical questions

“This partnership takes our strength — asking critical medical questions — and joins it with IBM, a leader in developing the technology to answer these questions through data. It means that our researchers, particularly those at Cleveland Clinic’s Global Center for Pathogen Research & Human Health, will have access to top-notch computer technology and tools, including an on-site quantum computer that has never before been used in healthcare, nor used outside of an IBM facility. This technology and tools will allow us to complete our scientific discoveries in record times,” says Dr. Jehi.

It takes on average 13 to 17 years for a discovery made by a scientist in a lab to translate into an effective medication that doctors can safely prescribe. “With quantum computing, and this partnership overall, we will be able to accelerate that timeline,” Dr. Jehi says. “The journey from discovery to therapy requires many steps that all rely on generating and analyzing a lot of data. For example, we analyze the genetic information of organisms that cause disease, then study how and why we get sick, then design new drugs and then test these drugs for safety and efficacy. This is particularly relevant in situations like the COVID-19 pandemic.”


For some diseases such as cancer, this would support accelerated drug design to expedite developing treatments. Simulated clinical trials should enable scientists to design better, faster trials.

The technology will also help scientists to sequence and analyze DNA, which has become essential in treating cancer patients with more personalized therapies. The tumor DNA is key in determining how that cancer will respond to treatments.

Being able to do all this computation in the context of clinical care and link it to the patient’s clinical data will help physicians know how to use the information.

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