Yale researchers discovered a loophole in the FDA’s medical device regulation

US Food and Drug Administration

A recent study led by researchers at Yale University School of Medicine and Harvard Medical School found that a loophole in existing regulations allowed manufacturers to obtain FDA approval for unsafe medical devices.

This work was led by Kushal Kadakia, first author and MD candidate at Harvard Medical School, Harlan Krumholz80, first author, Harold H. Heinz, Jr. Professor of Medicine and director of the Center for Research and Outcomes Evaluation. Their study found empirical evidence that approved medical devices based on a device previously recalled through the 510(k) regulatory pathway were significantly more likely to undergo a Class I recall, the FDA’s most serious classification for recalls.

“Path 510(k) does not require medical devices to undergo new testing as long as they can show that they are significantly related to previously approved devices, known as predicates,” Kadakia said.

This path accelerates the approval of medical devices that may contain only minor changes from previously approved iterations and be used for the same purpose. fact, more than 95 percent Most new devices are cleared by the Food and Drug Administration through this pathway.

But because of a loophole in regulation, the predicates themselves may not be safe for human use.

“The way the law is written, if the FDA takes it off the market, it can’t be used as a predicate, but if the company takes it off the market, you retain the ability to reintroduce a new law that’s pretty much equivalent and still be used for that unsafe purpose,” he said. Krumholz.

The study focused on medical devices that were subject to a Class I recall. This type of recall is issued when a medical device has a reasonable probability of causing severe adverse health consequences, up to and including death.

Previous studies presented case studies showing damage caused by certified devices using retracted kickstands. Kadakia worked on two such studies of the catheter and sleep apnea device that have subsequently been subject to Class I recalls. This new study is unique in its scope.

“We’ve been able to go through several years and identify all the devices that have these recalls, rather than picking one or two,” Krumholz said. “We were able to look at a comprehensive group and give a more representative view.”

This approach is made possible by recent advances in machine learning and data science. Because the FDA’s database only contains decision letters, which list the reasons behind the authorization, it can be difficult to know which devices have been authorized with a particular device as a warrant. Without new computational tools, it would have taken a great deal of time to map medical device genealogies. However, the researchers were able to build these lineages in partnership with an AI company and then manually corroborate the AI ​​database results.

The researchers found a 6.4-fold increase in recall rates for approved medical devices with retracted braces compared to non-retracted braces. Because each device can contain tens of thousands of units and is used throughout the medical process, these recalls can have widespread effects.

The New and Untested Appliance Safety Act of 2012 was an earlier attempt to correct this problem, but it failed to secure enough votes. The researchers hope that this new study will energize the United States Congress to at least start debating the 510(k) path again.

“The original vulnerability retrieved is not an unknown quantity in Washington,” Kadakia said. “We have now systematically presented empirical evidence of how this vulnerability can be used to cause harm.”

The study authors also acknowledge that more work can be done with these new computational approaches.

“We were limited to analyzing one generation, but it would be interesting to look at the children of the children of the retrieved predicates and so on,” said Cesar Caraballo, a postdoctoral fellow at Yale University School of Medicine.

Krumholz hopes that more evidence will enhance Congress’ ability to enact prudent and empirically sound legislation. Kadakia explained that this is critical because medical devices receive much less research attention than drugs because they are integrated into the medical process rather than the point of care.

“If we can add unique device identifiers to claim forms, we can determine how much spending was allowed through the original loopback,” Kadakia said. “We can also determine if the reasons for new recalls and warrant withdrawals are similar.”

In fiscal year 2022, 149 medical device products were subject to Class 1 recalls.

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