Cloud Computing Helps Unlock Wonders of Human Genome

Understanding the human genome can lead to a new era of precision medicine, where help doctors can provide more personalized care.

By Jacob Gedetsis

By Jacob Gedetsis March 3, 2022

Consumers today are used to personalization and customization. Whether it’s a hamburger, a pair of sneakers, or a new home, they want – nay, expect – products and services that are tailored to their unique needs and tastes.

But personalization isn’t just about preferences. In the case of medicine, it could be a matter of life and death.

“America is a diverse community – a group of people from different backgrounds, different races and ethnicities, different gender identities, and different ability levels,” Brian Ahmedani, director of psychiatry research and research scientist at Henry Ford Health System, told the National Institutes of Health (NIH). 

“So we should have health care that’s tailored to individuals based on who they are.”

Unfortunately, healthcare thus far has failed to deliver on the promise of precision medicine. Cloud computing and artificial intelligence (AI) might be able to change that as researchers use these technologies to better understand the human genome. The product of their work – genomic cloud solutions – represents an innovative path to personalized care.

What is Precision Medicine?

Researchers have spent the last decade trying to identify and treat disease through precision medicine. Whereas providers historically have taken a one-size-fits-all approach to healthcare, which targets treatment toward the “average person,” precision medicine – also called “personalized medicine” or “genomic medicine”– takes into account a patient’s individual genes, lived environment, and lifestyle.



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By customizing treatment to the individual, doctors hope to achieve faster, more effective care.

“In the next 30 years, for example, someone with type 2 diabetes will be immediately placed on the medicine that is best suited for their genetic predisposition, their ethnicity, their age, their sex and the duration of time they’ve had the disease,” Dr. Suneil Koliwad, professor at the University of California, San Francisco’s Diabetes Center, said in an interview with UCSF Magazine.

“They’re not going to have to try one therapy, and if that doesn’t work, try another, and another.”

Although the promise of precision medicine is enormous, so are the barriers to achieving it. Namely, the ability to capture, analyze and leverage genomic data. Combined with clinical, pharmaceutical and lifestyle information, such data can help providers discover early signs of sickness. It can then help them determine an individual’s risk of developing disease and prescribe targeted treatments that eradicate illness more quickly and effectively.

AI and cloud computing could be the sledgehammers that finally break down the barriers to precision medicine. NIH’s All of Us research program, for example, is a historic effort to collect and study data from 1 million or more people living in the United States.


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By using AI and cloud computing to analyze mountains of personal health information, it hopes to unlock a new era of customizable care and treatment.

“What makes an individual unique is a combination of so many things. Certainly a person's genome – his or her genetic ancestry – is critically important, but there is much more, including environmental exposures, cultural issues, personal experience, and many other factors,” Dr. Bruce Korf, chief genomics officer at the University of Alabama at Birmingham’s School of Medicine and principal investigator of the Southern All of Us Network, told NIH.

“Together these create a whole much greater than the sum of the individual parts. Now, for the first time, we have the ability to put this all together, and in my mind, that's what All of Us is all about – not looking at any one factor, but rather integrating multiple sources of information to paint a larger picture that will vastly increase our understanding of individual health.”

Genomics Cloud Solutions

Since its founding, All of Us has enrolled more than 366,000 participants and received more than 279,000 biosamples for genomic cloud sequencing, as well as amassed data from more than 233,000 electronic health records (EHRs) and more than 1.34 million completed surveys.

The program isn’t just designed to collect data, however. Rather, it’s intended to disrupt how researchers actually work with data. Specifically, NIH argues, researchers need to be able to process more data, more quickly.

Typically, researchers download datasets to a local computer, which works fine for small amounts of data, but fails at scale.

“That pattern doesn't work anymore. It means that you're copying data every time you want to work with it, and the data lives in many places, which makes it harder to monitor and control what happens to it, and harder to collaborate,” All of Us member David Glazer, research engineer at Verily, told NIH.

“So we are taking a very different approach: Instead of bringing the data to the researchers, we want to bring the researchers to the data. That’s a fundamentally different approach with a huge number of advantages, and it means we don’t just do things the way they’ve been done before.”


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He said cloud computing in genomics creates a better workflow. Through its cloud-powered Researcher Workbench, NIH provides scientists with digital workspaces to access, store, and analyze data for specific research projects. Precision medicine cloud computing allows researchers from across the globe to access these collaborative workspaces.

The cloud is especially powerful when it comes to parsing genetic data. Although genomic sequencing can provide researchers with huge amounts of data that will unlock the future of personalized medicine, sorting, saving, and understanding that data is a massive task. After all, just one human genome sequence produces approximately 200 gigabytes of raw data.

“Distributed big data is the No. 1 overwhelming challenge for life sciences today, the major obstacle impeding progress for precision medicine,” Maria Chatzou Dunford, co-founder and CEO of biomedical data company Lifebit, said in an interview with Labiotech.

“The cloud and associated technologies are already powering intelligent data-driven insights, accelerating research, discovery, and novel therapies. I have no doubt we are on the cusp of a genomics revolution.”

The Promise of Cloud Computing Precision Medicine

The potential of precision medicine is particularly powerful for patients with kidney disease. That’s because most people with kidney disease don’t realize they have it. And neither do their doctors.

Although kidney disease is one of the leading causes of premature death in the world, it can be difficult to diagnose in its early stages. Researchers equipped with AI are trying to change that.


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Among them, scientists at the University of Utah, which in February 2021 announced a partnership with RenalytixAI to fight kidney disease by combining technology with research. They believe that identifying genetic biomarkers will allow researchers to feed data to machine learning algorithms in order to enhance diagnosis, prognosis and monitoring of patients in the earliest disease stages.

“Now we have biomarkers and clinical features that, when combined with iterative machine learning, enable risk prediction formulas that give doctors the key answers needed: who is at highest risk versus not and what is the appropriate course of treatment,” Dr. Amit Sharma, U.S. vice president of medical affairs, Cardiovascular and Renal Division, at Bayer Pharmaceuticals, said in an interview with RenalytixAI.

RenalytixAI’s platform, KindeyIntelX, gives healthcare providers actionable insights through a unique patient risk score that indicates the near-term risk of kidney function decline or failure, which can be linked to specific guideline-driven clinical actions.


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After an easy blood test, KindeyIntelX runs the patient’s data through its machine-learning algorithm to generate the risk score. It utilizes a cloud computing infrastructure to ensure timely and secure retrieval of real-time data.

“This is critical since we only have approximately 15 minutes with each patient,” Sharma continued. “We need to be able to quickly review data and make an informed action plan. This risk prediction ‘score’ will enable us to focus more resources on those who need it most and enable us to prescribe the best therapeutic.”

KindeyIntelX is just one example of cloud-based medicine research that is giving overworked healthcare professionals the personalized information they need to better serve patients. Thanks to emerging technologies that are helping researchers harness the human genome, there are bound to be many, many more in the years and decades to come. With the improved understanding they provide, personalized medicine will become the rule instead of the exception — and will ultimately save lives as a result.

Jacob Gedetsis is a contributing writer. His work has appeared in The Kansas City Star, The Post Standard, and The Plain Dealer, among others. Find him on Twitter at @JacobGedetsis.

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