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Unpacking Averages: Finding Medical Device Predicates Without Using FDA’s 510(k) Database

The motivation for this month’s post was my frustration with the techniques for searching the FDA’s 510(k) database.  Here I’m not talking about just using the search feature that FDA provides online. Instead, I have downloaded all of the data from that database and created my own search engine, but there are still inherent limitations in what the data contain and how they are structured.  For one, if you want to submit a premarket notification for an over-the-counter product, it really isn’t easy to find predicates that are specifically cleared for over-the-counter without a lot of manual work.

To see if I could find an easier way, I decided to use the database FDA maintains for unique device identifiers, called the Global Unique Device Identification Database (GUDID).  You can search that database using the so-called AccessGUDID through an FDA link that takes you to the NIH where the database is stored. That site only allows for pretty simple search, so for what I needed to do, I downloaded the entire database so I could work directly on the data myself.

While the UDI database is enormous at this juncture (over 3 million products), what I found left me with questions about just how comprehensive and complete the data are.  At the same time, it seems like a good way to supplement the information that can be gleaned from the 510(k) database.

Findings

I want to summarize my findings at a high level, so I am not reporting on individual products that are over-the-counter, but rather in which product codes I found them.

The chart may be a little bit hard to understand.  For the top category, general hospital, there are 45 product codes that contain over-the-counter products.  There may be many products in each individual code.  But as I said, my goal was to summarize at a higher level.  We can drill down in each of those clinical areas and in each of the product codes to see the specific products.

Methodology

Getting to that level took quite a bit of work because there was a lot of noise to filter out.   For example, if you’re focused on a 510(k) clearance, there are often many different products listed as stemming from one clearance.  That’s perfectly okay, and indeed it’s useful to know the full range of products linked to a given clearance, but if you’re using the database as I was to understand the scope of clearances, it means that there’s quite a bit of filtering required.

I chose first to filter based on those products that are still in commercial distribution, not because it was legally necessary for finding a predicate, but devices that are no longer on the market make for a tougher sell at FDA.  I then filtered for devices that the manufacturer identified as over-the-counter.  That left me with just about 160,000 products.

I then filtered for products that had an FDA clearance listed.  This would exclude any products that were exempt, perhaps because they are class I or exempt class II.  It is technically possible to have a predicate that FDA has not cleared but is nonetheless lawfully on the market, but that’s a rare circumstance.  After that filter, I had about 40,000 products left.

In the end, I identified the product codes that had at least one such OTC product.  There were 395 different product codes across the therapeutic areas.

Interpretation

Much of the chart makes intuitive sense.  General Hospital seems like a category that would have more over-the-counter products than some of the other therapeutic areas.  Seems like we are moving to more and more over-the-counter products in cardiology, which undoubtedly is producing a big public health benefit.  Likewise, it appears that laboratory tests must be moving over-the-counter given that clinical chemistry and clinical toxicology ranked as highly as they do.

Conclusion

GUDID is comprised of raw data entered by manufacturers without any FDA review.  The 510(k) database, in contrast, is data entered by FDA review staff based on what a manufacturer provides.  As a quality measure, if you drill down and pick a potential predicate in the GUDID as over-the-counter, it would probably be prudent to search for it in the 510(k) database and read the PDF summary of safety and effectiveness to ensure that it likewise indicates over-the-counter status.  But if you’re willing to do that, seems like the GUDID is a great way of casting a wider net to find potential over-the-counter predicates.