A Closer Look at FDA's AI Medical Device Approvals

On October 5th, 2022, the FDA added 178 new devices to its list of (approved) “Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices.” The full list is conveniently available at that page for download as an Excel file, and I decided to take advantage of this to dig a little deeper into the data. Mostly I was interested in the pace of FDA approvals — which of course reflects both the number of applications and the speed of the FDA process. What I found was interesting, and not exactly what I expected.

Picking up the pace of approvals

Not too surprisingly considering the hype around AI — and its potential —  we can see that the pace of FDA approvals has picked up substantially in the last 10 years. While 2022 is not yet complete as of this writing, if it continues at the current pace it should just exceed 2021:

FDA AI-Powered Medical Device Approvals by Year

 
Column chart for FDA AI medical device approvals since 2017
 


Lonely at the top

With a bit more digging, we can also see that the number of companies receiving at least one approval is on the upswing, as well:

Number of companies receiving at least one FDA approval by year

 
Line chart of the count of companies receiving FDA approval by year
 


Despite the increase in the number of companies playing in the space, success in FDA medical AI approvals also seems to be becoming more concentrated.

For example, in 2022 so far, just 10 of the 55 companies winning at least one approval (18%) were responsible for more than half of total approvals. Five years ago, that percentage was 55%:


Percent of Companies Winning Approval Each Year Getting 50% of Approvals

 
Bar chart showing the concentration of FDA medical AI device approvals
 

Your grandfather’s medical AI?

The most surprising point hidden in the dataset was that a lot of the action in medical AI isn’t coming from Big Tech companies known for AI like Apple or Amazon or Google/Verily but from much much older Big Med Tech industrial companies, with GE (founded 1892) and Siemens (founded 1847) taking the number 1 and 2 spots, respectively.

[Note that I’ve counted related company divisions as a single unit. For example: GE Medical Systems, GE Healthcare Japan, and GE Healthcare are just counted as “GE”.]

Here are the companies taking the top 5 spots for “number of approvals in 2022 so far,” with number of approvals in parentheses (and note that Philips and Canon tied for 4th place with 4 approvals):

Top 6 Companies for FDA Al Approvals in 2022 (so far)

 
Donut chart for Top 5 Companies for FDA AI Approvals in 2022
 

The average age of these top six companies is 89 years old! Leaving out Hyperfine and Aidoc, that figure rises to 130. Not exactly startups.

Nonetheless, the oldsters are being crowded out gradually as the median age of companies getting approvals goes down:

Median and mean age of companies receiving FDA approval

 
Line chart of Median and mean age of companies receiving FDA approval
 



Sustaining innovation rules medical AI

So we’ve established that some pretty ancient companies are among the dominant players in medical AI. But is the tide shifting towards the startups (i.e. towards disruption)?

I’ll define an “older” company as >= 20 years old.

Certainly we can see that the percentage of companies winning at least one approval each year that are older is decreasing:

Percentage of companies winning at least one approval that are >=20 years old vs younger

 
Stacked bar chart showing percent of companies winning at least one FDA approval the are >= 20 years old
 

This may reflect the increasing simplicity and economy of AI tools available, and the increasing number of coders who understand how to use them: the cost in time and money of playing in the AI space is going down, and that means younger and smaller companies can join the game.

At the same time, older companies gain the benefit of those decreasing costs, too, and they have more resources with which to deploy them. Here’s a chart showing the percentage of approvals going to older vs younger companies:


Percentage of FDA approvals going to companies >= 20 years old vs younger

 
Stacked column chart showing percent of companies 20+ getting FDA approvals vs <20 years old
 

What the last two graphs shows us is that while younger companies are increasingly in the game, the older companies (with presumably greater resources) are more than holding their own in terms of productivity. They make up a smaller percentage of companies winning at least one approval each year, but are taking an increasing share of those approvals.

So using FDA approvals as the metric, it doesn’t look like there’s much disruptive innovation going on in AI-powered med tech: we don’t see established medical device makers like GE being pushed aside (at least not yet). Instead we see:

  1. increasing numbers of new companies entering the space and winning FDA approvals

  2. continued dominance by established med tech players as they add AI on to their existing products to improve performance and appeal to their best existing customers.

In other words, classic sustaining innovation.

Does this mean that AI isn’t causing disruption related to healthcare? No, not at all. But, as I’ve explained in previous articles on disruption within healthcare and disruption to healthcare, it shows that the same technology (AI) can be used to

  1. sustain current healthcare practices (e.g. GE and Siemens and Canon, along with some youngsters, making hospital-based imaging cheaper, more useful, and more accurate)

  2. enable players outside traditional healthcare to shift low-hanging fruit to another part of the healthcare system (e.g. Walmart Health)

  3. allow companies completely outside healthcare to shift other low-hanging fruit completely outside healthcare (e.g. ResApp)

Thoughts about the above? Inside knowledge you’d like to share? Feel free to contact me privately.






Further Reading







blogJoel Selanikiodisruption, FDA, regulationComment