Yale researchers discover loophole in FDA regulation of medical devices

Researchers at Yale School of Medicine and Harvard Medical School found that a loophole in existing regulation has allowed manufacturers to acquire US Food and Drug Administration approval for unsafe medical devices.

Stephanie Hu

01:50 on 26 January 2023

US Food and Drug Administration

A recent study led by researchers at Yale School of Medicine and Harvard Medical School found that a loophole in existing regulation has allowed manufacturers to acquire US Food and Drug Administration approval for unsafe medical devices.

This work was led by Kushal Kadakia, first author and MD candidate at Harvard Medical School, and Harlan Krumholz ’80, senior author, Harold H. Hines, Jr. Professor of Medicine and Director of the Center for Outcomes Research and Evaluation. Their study found empirical evidence that medical devices approved based on a previously recalled device through the 510(k) regulatory pathway were significantly more likely to be subject to a Class I Recall, the FDA’s most serious designation for recalls.

“The 510(k) pathway 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 pathway accelerates the approval of medical devices that may have only minor changes from previously approved iterations and are being used for the same purpose. Actually, over 95 per cent of new devices are approved by the FDA through this pathway.

However, due to a loophole in the regulation, the predicates themselves may not be safe for human use.

“The way the law is written, if the FDA pulled it off the market, it can’t be used as a predicate, but if the company pulled it off the market, you retain the ability to reintroduce a new one that is essentially equivalent to and still used for the uncertain purpose,” Krumholz said.

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

Previous research had provided case studies showing harm caused by entities authorized using revoked predicates. Kadakia worked on two such studies of a catheter and a sleep apnea device that were later the subject of Class I recalls. However, this new study is unique in its scope.

“We were able to go across multiple years and identify all the devices that had these recalls, rather than picking one or two,” Krumholz said. “We were able to look at a comprehensive group and provide a more representative view.”

This approach was made possible by recent advances in machine learning and data science. Because the FDA’s database only contains decision letters that state the rationale behind an approval, it can be difficult to determine which devices have been approved with a particular device as a predicate. Without the use of new computational tools, mapping the lineages of medical devices would have been time-consuming. However, the researchers were able to construct these lineages in partnership with an AI company and then manually confirm the AI ​​database results.

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

The Safety of Untested and New Devices Act of 2012 was an earlier attempt to correct this problem, but failed to secure enough votes. The researchers hope that this new study can reinvigorate the US Congress to at least begin the discussion of the 510(k) pathway again.

“The revoked predicate loophole is not an unknown quantity in Washington,” Kadakia said. “We have now provided empirical evidence in a systematic way of how this loophole is being used to cause harm.”

The study authors also acknowledge that more work can be done using these new calculation methods.

“We limited it to a one-generation analysis, but it would be interesting to look at children of children of recalled predicates and so on,” said César Caraballo, a postdoctoral researcher at the Yale School of Medicine.

Krumholz hopes that more evidence will strengthen Congress’s ability to pass smart and empirically sound legislation. This is especially critical since medical devices receive far less research attention than drugs because they are embedded throughout the medical process rather than at the point of care, Kadakia explained.

“If we were able to add unique device identifiers to claim forms, we could quantify the amount of spend that was approved through the predicate recall hole,” Kadakia said. “We were also able to determine whether the causes of the new recalls and the recalls of the predicates are the same.”

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

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