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Egg companies made $1.22 billion in profit off a $6 carton — now they’re buying their way out of a price-fixing case with 53 million donated eggs

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Meet the Zillennials: The luckiest micro-generation in the workforce, born between 1993 and 1998

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Economists have found an answer to slowing cognitive decline: Avoid retiring early, study finds
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A.I. fast-tracks health care innovations, says Moderna’s chairman

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Jenna Schnuer
Jenna Schnuer
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Jenna Schnuer
Jenna Schnuer
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November 9, 2021, 11:30 AM ET
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Considering the number of health care advances that Noubar Afeyan has helped drive forward, it’s quite something to see that he remains excited by what comes next. But thanks to machine learning and other technologies, the advances are coming fast and furious.

Through Flagship Pioneering, the life sciences venture capital company and biotech incubator that Afeyan founded in 2000, he has helped build more than 60 science and technology startups, including Moderna, now a household name thanks to its COVID-19 vaccine. The CEO of Flagship Pioneering, Afeyan holds more than 60 patents.

As became clear when he was interviewed by Fortune CEO Alan Murray at the Fortune Brainstorm A.I. conference, Afeyan continues to be deeply invested in the many ways technology can help cure illness and disease around the world.

“Life science has always been about data,” said Afeyan, “in that we’re studying systems that precede us.”

What has changed is that researchers have gotten better at measuring that data both more precisely and in diverse ways, which has in turn led to creating more data.

After that? “Machine learning advances in the recent past simply have given us better models to do that with and that has increased, if you will, our leap size…the size of the steps we can take,” said Afeyan.

That leap includes a flip in the starting point for testing drugs in clinical trials. The model for new drugs has always required breaking out the single problem protein to build a drug against. Thanks to machine learning, researchers are at the start of being able to “do a drug discovery or drug development using data from an entire human or, better yet, millions of humans,” said Afeyan.

That’s a process that Afeyan and other researchers couldn’t even imagine doing just a year ago. “We’re in an exponential period,” he said. “Three years from now we’ll laugh at what we’re doing today.”

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