What became of the genetics revolution?

What became of the genetics revolution?

What the genetics revolution can teach the next one

Healthcare has already lived through one data revolution: genomics. Sequencing a genome went from a billion-dollar, years-long undertaking to a few hundred dollars and a few hours. But getting the data wasn’t the hard part for long. Making sense of it was. Dr. Euan Ashley, who chairs Stanford's Department of Medicine and led the team that performed the first clinical interpretation of a human genome back in 2009, has spent fifteen years living that gap firsthand. As healthcare heads into its next data revolution—wearables, continuous monitoring, AI interpretation—his experience with the last one is a useful preview of what's about to repeat, and what won't.

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Five Key Takeaways

1. AI reproduced a year of research work in about thirty minutes.

Ashley ran his own genome, sequenced back in 2009, through Claude with a short prompt. It matched work that had once taken his team months for about five dollars in computing cost.

2. That speed is built on decades of infrastructure.

The AI relied on databases, tools, and reference standards the genomics community spent years building by hand, an effort that is now scaling with these tools.