Most companies want to avoid FDA warning letters.  To help medical device companies identify violations that might lead to a warning letter, this post will dive deeply into which specific types of violations are often found in warning letters that FDA issues.

Background

As you probably know, FDA has a formal process for evaluating inspection records and other materials to determine whether issuing a warning letter is appropriate.  Those procedures can be found in chapter 4 of FDA’s Regulatory Procedures Manual.  Section 4-1-10 of that chapter requires that warning letters include specific legal citations, in addition to plain English explanations of violations.  The citations are supposed to make reference to both the statute and any applicable regulations.

As a consequence, to understand the content of the warning letters, we need to search for both statutory references as well as references to regulations.  Because statutes are deliberately drafted to be broader in their language, references to the regulations tend to be more meaningful.
Continue Reading Unpacking Averages: Violations Found in Medical Device Warning Letters

Since the passage of the Medical Device Amendments of 1976, FDA has regulated in vitro diagnostic (IVD) tests as medical devices, subject to a full suite of FDA requirements.  During that time, FDA has also asserted that it has the authority to regulate in-house tests developed and performed by CLIA-certified, high-complexity clinical laboratories (generally referred to as laboratory-developed tests or LDTs) but chose as a matter of enforcement discretion not to regulate LDTs.  Over time, the Agency chipped away slowly at LDT enforcement discretion, carving out certain kinds of tests (e.g., direct-to-consumer LDTs) and thus making them subject to regulation, but by and large did not take broad steps to regulate LDTs.

Continue Reading The VALID Act: Senate Action Brings FDA Regulation of LDTs Closer to Fruition

Much like the ambiguous landscape involving cannabidiol (CBD) products on the consumer market, an influx of delta-8 THC containing products for consumption has highlighted a recurrent regulatory issue surrounding the legality of hemp derived products at the federal level. The Agricultural Improvement Act of 2018 (the “2018 Farm Bill”), which, among other things, offered a federal definition of hemp and removed it from the list of Schedule I controlled substances, specifically carved out hemp derived products with less than 0.3% delta-9-tetrahydocannabinol (THC) on a dry weight basis, thereby allowing products that meet this definition to flood the consumer markets.

Continue Reading Recent FDA Enforcement Action Colors Regulatory Landscape for Delta-8 THC Products

Overview

In this month’s post, in the medical device realm I explore what kinds of inspection citations most often precede a warning letter.  In this exercise, I do not try to prove causation.  I am simply exploring correlation.  But with that caveat in mind, I think it’s still informative to see what types of inspectional citations, in a high percentage of cases, will precede a warning letter.  And, as I’ve said before, joining two different data sets – in this case inspectional data with warning letter data – might just reveal new insights.
Continue Reading Unpacking Averages: Device Inspection Citations That Frequently Precede Warning Letters

This month’s post focuses on how timely FDA decisions are in categorizing new diagnostics under the Clinical Laboratory Improvements Amendments of 1988 (CLIA). The answer is that, on average, the agency does okay, but they also sometimes may miss their own guideline by a wide margin.  I use the word “may” there because the FDA data set is inadequate to support a firm conclusion.  I’ll explain more about that below, but this is another case of FDA releasing incomplete data that frustrates data analytics.

Continue Reading Unpacking Averages: Assessing FDA’s Performance Categorizing New Diagnostic Tests Under CLIA

I recommend against relying on any data I provide in today’s post.  I hope the data are at least somewhat accurate.  But they are not nearly as accurate as they should be, or as they could be, if FDA just released a key bit of information they have been promising to share for years.

One of the ways data scientists can provide insights is by grafting together data from different sources that paint a picture not seen elsewhere.  What I want to do is join the clinical trial data at www.clinicaltrials.gov with the data maintained by FDA of approved drugs, called drugs@FDA.  But I can’t, at least not with much accuracy.

Continue Reading Unpacking Averages: Connecting Published Clinical Trials with FDA Drug Approvals

The United States Food and Drug Administration (FDA) for many years has been trying to increase the participation of minorities in clinical trials to help ensure that regulated products are tested and labeled in an appropriate cross-section of Americans.  Clinical evidence has shown that there are significant differences among the races that impact the safety and effectiveness we can expect from a particular drug or device, and consequently FDA has concluded testing and labeling to identify those racial differences are important.  The question for today is, how are we doing in achieving racial diversity in clinical trials involving drugs?

Continue Reading Unpacking Averages: Assessing the Racial Composition of Drug Clinical Trial Subjects

On January 11, 2022, the Centers for Medicare and Medicaid Services (“CMS”) published an anticipated proposed National Coverage Determination (“NCD”) decision memorandum that begins the process of determining whether the Medicare program will cover FDA-approved monoclonal antibodies directed against amyloid for the treatment of Alzheimer’s Disease. (https://www.cms.gov/medicare-coverage-database/view/ncacal-decision-memo.aspx?proposed=Y&NCAId=305).

The proposed decision, which is subject to public comments that are due to CMS by February 10, 2022, does not endorse nationwide Medicare coverage for these drugs. Instead, CMS chose an alternate pathway known as Coverage with Evidence Development (“CED”).  If the proposal is adopted by CMS, it would set in motion a detailed regulatory process that includes temporary Medicare coverage for the drug but only for certain Medicare beneficiaries who are enrolled in an additional clinical trial intended to test whether these drugs will have a significant benefit for Medicare beneficiaries.  CMS expects to issue a decision by April 11, 2022 to approve or reject the CED process after reviewing comments from interested parties.
Continue Reading CMS “Splits the Baby” on Aduhelm—Medicare Coverage but Only with Evidence Development for Now

It is common for FDA and others to show a map of the United States with the states color-coded by intensity to showcase the total number of inspections done in that state.  Indeed, FDA includes such a map in its newly released dashboard for FDA inspections.  In reviewing that map with the U.S. map color-coded to reflect where medical device establishments are located, do you notice anything?  Not to destroy the suspense for you, but it turns out that FDA tends to inspect where medical device inspection facilities are located.  Really.

We wanted to get beneath those numbers in two ways.  First, it’s much more informative to look at the data at a county level because there’s actually quite a bit of variation county by county.  Second, and more importantly, we wanted to normalize the inspection data by the number of facilities.  In other words, by looking at inspections per facility, we can get a better sense of the inspection frequency in each county.

Continue Reading Unpacking Averages: Likelihood of FDA Medical Device Inspections

This month, we’re going to look at a visualization that uses network techniques. Visualizing a network is a matter of nodes and edges. If the network were Facebook, the nodes would be people, and the edges would be the relationships between those people. Instead of people, we are going to look at specific device functionalities as defined by the product codes. And instead of relationships, we are going to look at when device functionalities (i.e., product codes) are used together in a marketed device as evidenced by a 510(k) submission.

Continue Reading Unpacking Averages: Popular Ways to Combine Device Functionality