FDA’s Culture Is Genetically Dominant Over 23andMe’s Business Model


(Page 2 of 2)

to develop and rigorously validate a test, get it approved by the FDA, and then market it at an incredible markup. That’s what 23andMe tried to do in this run. They invited the FDA in the front door, and at least so far, haven’t been very good about serving them tea. We’ll find out more about why later.

But I posit the data culture that permeates technology companies is at the root of the frosty relationship between the FDA and 23andMe. It makes it very hard to pivot from a model based on loss leadership and data mining to one based on regulatory submission.

That “traditional” submission to the FDA would be of a very specific kind of analysis based on randomized controlled trials. It is designed to keep bad things from happening to people, not to make sure good things happen to people. As one of my favorite papers lays out, parachutes would not receive FDA approval as a gravity-resisting device.

Modern tech culture doesn’t work that way. Bayes’ rule is about probability. It’s a different way of knowing that you know something, and it’s one in which there is far more tolerance for uncertainty than the FDA is accustomed to. And there’s been statements by FDA officials that they are deeply uncomfortable with that. Note in particular Janet Woodcock’s statement that causal inference needs a “level of rigor”—and the date in late April. It’s right before 23andMe cut off communication with the FDA.

The FDA isn’t saying that 23andMe needs to shut down, or stop giving people data, or stop providing spit kits. It’s saying their causal inference doesn’t hit the level of rigor that allows it to pursue a technology business model in the health regulatory space. That’s a gamble 23andMe was always taking, that the FDA wouldn’t know how to regulate it in time for it to make money. It’s not an overreach, or a screw job on patients. It’s just business.

And I hope this isn’t the end of it. We need DTC screening. It helped me. It’ll help many others. But until the FDA learns how to deal with Bayes’s rule and its discomforts—and until DTC companies figure out a business model that isn’t based on massive loss leadership—we’re going to keep coming back to this clash of culture and business models. Both sides need to make some changes if we’re going to avoid doing this over, and over, and over.

[Editor’s note: this post first appeared on John Wilbanks’s personal website.]

Single PageCurrently on Page: 1 2 previous page

John Wilbanks is a data commons expert and advocate who has spent his career working to advance open content, open data, and open innovation systems. He is a senior fellow at FasterCures and chief commons officer at Sage Bionetworks. Follow @wilbanks

Trending on Xconomy