AI + Covid-19 Vaccine

Short & Sweet AI

How fast can you develop a vaccine? Never has this challenge been put to the test quite so intensely as in 2020.

In fact, Jason Moore, who heads Bioinformatics at UPenn thinks that if the virus had hit 20 years ago, the world might have been doomed. It’s only thanks to modern technology that we now have a safe vaccine. He said, “I think we have a fighting chance today because of AI and machine learning.”

So, how did AI help to make the Covid-19 vaccine a reality? The short answer is a combination of computational analysis and the system of AlphaFold. I talk more about how researchers developed the vaccine so fast in this episode of Short and Sweet AI.

In this episode find out:

• How AI was used to learn more about Covid-19 through data analysis
• How AI helped researchers develop the vaccine so quickly
• Where we would be without AI and machine learning

Important Links & Mentions

• Deep Mind, Gaming, + the Nobel Prize
• AlphaFold: Using AI for Scientific Discovery
• Alpha Fold: the making of a scientific breakthrough

Resources:

• IEEE Spectrum - What AI Can–and Can’t–Do in the Race for a Coronavirus Vaccine
• Wired.com - AI Can Help Scientists Find a Covid-19 Vaccine
• Washington Post - Artificial Intelligence and Covid-19: Can the Machines Save Us?

Episode Transcript:

Friends tease me because I’m so fascinated with artificial intelligence that I will claim AI is the reason we have a safe Covid-19 vaccine so quickly. And they’re right, it is one of the reasons. In fact, Jason Moore, who heads Bioinformatics at U Penn thinks if this virus had hit 20 years ago, the world might have been doomed. He said “I think we have a fighting chance today because of AI and machine learning.

How did AI help to make the Covid-19 vaccine a reality? The short answer is through computational analysis and Alpha Fold.

But first, a little background on vaccines. A vaccine provokes the body into producing defensive white blood cells and antibodies by imitating the infection. In order to imitate an infection, you need to find a target on the virus. Once you find the target you need to understand its 3D shape to make the vaccine against it. But it’s really hard to figure out all the possible shapes before you find the one, unique 3D shape of the target, unless…unless of course you use AI.

In the case of the Covid-19 vaccine, Google’s machine learning neural network called Alpha Fold saved the day. Alpha Fold predicted the 3D shape of the virus spike protein based on its genetic sequence. And did it really fast, as early as March 2020, three months after the pandemic started. Without AI, it would have taken months and months to come up with what the best possible target protein could be, and it might have been wrong. But with AI, researchers were able to race ahead to ultimately develop the mRNA vaccine.

It’s common knowledge that it can takes years or even decades to develop a vaccine. Before Covid-19, using other approaches, the quickest vaccine to be developed took 4 years. As of September 2020, there were 34 different Covid-19 vaccines being tested in humans. That’s an astonishing number in so short a time.

Neural networks excel at analyzing massive amounts of data to find patterns that humans might not spot. Computers use machine learning to sort and analyze incredible amounts of data to learn and train over time. And that’s been AI’s second big contribution to conquering Covid-19. It’s called computational analysis. It involves using AI to gather insights from huge sources of experimental, and well as real world data, on the virus.

At the outset of the pandemic The Allen Institute for AI started an online repository of research articles about Covid-19. Today it has over 30,000 academic articles. Researchers can use this data set for the machine learning algorithms to train on, so they better understand the virus.

For example, as early as April 2020, computational scientists harnessed neural networks to sort through medical records by the thousands. The machines were able to confirm the lack of smell and taste is one of the earliest symptoms of Covid infection. There existed isolated reports of anosmia, which is the medical term for loss of smell and taste, but computer data analysis validated the finding. The CDC then added these to their list of Covid symptoms which helped identify when a person had the infection.

In another instance, medical charts from 96 hospitals in several different countries were analyzed with machine learning. What emerged was insight that many Covid patients had really off the chart readings of blood clotting. This alerted doctors to use blood thinners in patients hospitalized with Covid.

As scientists explain, the human brain becomes pretty quickly overwhelmed by the endless combinations of things, but when you use AI, the machines can find and directly move in on important findings, very quickly and effectively. AI is routinely depicted as evil in fiction, social media, and by Hollywood, and yet, its revolutionized how vaccines are created. It’s also become a workhorse of this pandemic as a powerful technology for processing massive amounts of information. Maybe, the machines will save us.