Big data and artificial intelligence (AI) technologies helped people spot first signs of the coronavirus in late 2019. Then these technologies helped track the spread of what would become known as COVID-19. Now they’re helping scientists find a vaccine.
Even if these technologies are nascent and criticized for not addressing many basic human needs, there’s a growing number of applications and examples of AI accelerating human response, especially to life-threatening outbreaks such as COVID-19.
“Something like this crisis shows how AI can potentially do a world of good,” said Oren Etzioni, CEO of AI2, in a Wired article about companies, libraries and institutes using AI and machine learning to analyze thousands of research papers about COVID-19.
“The scientific literature on the coronavirus is growing exponentially,” he said, making it harder for humans to absorb and find clues.
The advancement and proliferation of big data and AI technologies are making it possible even for small organizations to sift through vast amounts of data and suggest options for solving problems across different industries. Big data and AI technologies helped the small software-as-a-service company BlueDot see the first warning signs more than a week before COVID-19 was officially identified by the World Health Organization.
“They were among the first in late December to flag some unusual cases of pneumonia associated with a live market in Wuhan, China,” said David Shaywitz, MD, PhD in a podcast interview with The Forecast.
Shaywitz studied medicine at Harvard and earned a PhD in biology at MIT, and was recently a visiting scientist in the department of biomedical informatics at Harvard Medical School. He co-hosts the podcast on digital health called TechTonics and is the founder of Astounding HealthTech, which advises senior biopharma research and development leaders about digital and data. He said BlueDot is an example of data technologies and human curation working together, similar to the approach taken by cancer data company Flatiron, acquired by Roche for $2.1B in 2018.
“Their algorithms distilled an extensive amount of news and other information into a couple of daily highlights, which then human curators sorted out to see what might be interesting,” he said.
According to CNBC, BlueDot used machine learning (ML) and natural language processing to sift through hundreds of thousands of sources, including statements from official public health organizations, digital media, global airline ticketing data, livestock health reports and population demographics. Technology can analyze and organize vast amounts of information so much faster than humans. Then humans can focus on fewer pieces of relevant information to find meaning.
“We didn’t know at that moment that this was going to become something of this magnitude,” said Kamran Khan, founder and CEO of BlueDot and professor of medicine and public health at the University of Toronto, in an interview with CNBC Make It.
Khan sees this technology speeding the spread of knowledge faster than diseases spread themselves. Being able to track, locate and conceptualize how infectious diseases spread can help healthcare experts get ahead of the curve and find ways to lower or stop the loss of human lives.
For example, BlueDot analyzed which areas saw the highest volume of travelers from Wuhan. Eleven of the cities at the top of their list were the first places to receive COVID-19 cases. An early warning can help government, health and safety officials act promptly to mitigate the spread of the virus.
Technology for Fighting Coronavirus
As government and business leaders sync to fight the coronavirus and prepare for future virus attacks, Shaywitz said there are some practical technologies that are helping now. He said telecare, telecommuting and tele-education are all playing a role in our national response to COVID-19. These approaches will grow increasingly important in daily life around the world.
“Technologies are immensely powerful,” he said. “We need to come up with pragmatic use cases that deliver palpable benefits people can appreciate.”
He’s also keen on drug and vaccine development. He said it’s very difficult to make a drug from scratch because chemistry, biology and the human body are very complicated. That’s where many startups are hoping AI, ML and other big data technologies will help.
“The genome sequence of this virus was determined and shared within a month,” he said. “Next, this information must be utilized effectively.”
Shaywitz said companies are using data from previous viruses along with information about the new virus in a race to create a vaccine. The first early stage clinical trials have already started, and the best-case hope would be for this to be available for patients in 12-18 months. One study, for example, was recently kicked off in Seattle by Moderna.
“That's unimaginably fast,” he said, adding that the company's proprietary analytics may have helped them "know what part of the virus to pick out and use for a vaccine.”
He expects technology to keep increasing the pace, noting cloud computing is making it possible for almost anyone to have unlimited, secure, safe compute and storage. He said cloud computing is good for data-intensive startups, describing it as "table stakes."
“A few years ago, when I was chief medical officer at DNAnexus, it was clear the cloud was enormously empowering,” Shaywitz said. “It's taken a little while, but at least the healthcare ecosystem seems to have got the message – even five years ago, many medical centers were visibly anxious about moving the cloud.”
He said now, while healthcare organizations may be taking a range of approaches to cloud, almost everyone recognizes it's essential. Cloud is readily available, easier to manage than ever before and less of a roadblock to research and analysis.
“It seems so clearly advantageous now that the discussion has moved onto the next series of challenges.”
Ken Kaplan is Editor in Chief for The Forecast by Nutanix. Find him on Twitter @kenekaplan.
Jason Lopez contributed to this story.
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