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Unpacking Averages: How Old Are Medical Devices on the US Market?

This month, I explore just how old medical devices are as measured by the date they were cleared or approved by the FDA, using the Global Unique Device Identification Database....more

Unpacking Averages: Is It Too Soon to Study the Postmarket Experience of AI-Driven Medical Devices?

I may be jumping the gun here, but I’m anxious to understand how the new flurry of AI medical devices is performing in the marketplace, or more specifically, whether the devices are failing to perform in a way that...more

Unpacking Averages: Intended Use Words Most Common to Devices That Require Clinical Trials

When I was working on my Masters in data science, one of the projects I did was to create an algorithm that would take an intended use statement for a medical device and predict whether FDA would require a clinical trial.  It...more

Unpacking Averages: Assessing the Products Included in FDA's Voluntary Malfunction Summary Reporting Program

At the end of 2022, FDA published a draft guidance on Voluntary Malfunction Summary Reporting (VMSR) Program for Manufacturers. The draft guidance explains several aspects of the VMSR Program, including FDA’s approach to...more

Unpacking Averages: Adverse Events for Device-Lead Combination Products

Combination products present a tremendous opportunity to improve health outcomes, because they leverage multiple disciplines.  If we were, for example, to focus on drugs alone with little thought to how they might be...more

Unpacking Averages: Analyzing FDA’s Performance in Finalizing Guidance Documents

FDA’s January 3, 2024, Federal Register notice soliciting comments on the agency’s plan to implement best practices for guidance development got me thinking.  What do the data show regarding FDA’s performance in moving...more

Unpacking Averages: Device Manufacturers Should Use the Newly Released Demographic Data in MDRs to Ensure Their Devices Are Not...

As you may know, we have been submitting FOIA requests asking FDA to share data from its various programs.  In October, FDA granted our April FOIA request in which we asked the agency to add back demographic data fields that...more

Unpacking Averages: Analyzing FDA Device-Related Citizens Petitions by Topic

Those who have been reading this blog know that I like to analyze collections of documents at FDA to discern, using natural language processing, whether, for example, the agency takes more time to address certain topics than...more

Unpacking Averages: Sample Size for Clinical Trials Used to Obtain FDA Medical Device Clearance

Our latest focus is trying to bring data to bear on common questions we get asked by clients. Last month the topic was: how well does my device need to perform to get premarket clearance from FDA? This month it is: how big...more

Unpacking Averages: FDA’s Extraordinary Delay in Resolving Citizen Petitions

This month I wanted to take a data-driven look at FDA’s treatment of citizen petitions, and specifically as a starting point how quickly the agency resolves those petitions.  Make no mistake, I have an interest in this...more

Unpacking Averages: How Accurate Do Class II Medical Devices Need to Be to Obtain 510(k) Clearance?

It’s common for a client to show up at my door and explain that they have performance data on a medical device they have been testing, and for the client to ask me if the performance they found is adequate to obtain FDA...more

FDA Oversight of AI Software Developed by Health Care Providers

Introduction - Hardly a day goes by when we don’t see some media report of health care providers experimenting with machine learning, and more recently with generative AI, in the context of patient care. The allure is...more

Unpacking Averages: Analyzing the Relationship Between MDRs and Recalls

Recently Colleen and Brad had a debate about whether Medical Device Reports (“MDRs”) tend to trail recalls, or whether MDRs tend to lead to recalls. Both Colleen and Brad have decades of experience in FDA regulation, but we...more

Unpacking Averages: Searching for Bias in Word Embeddings Trained on FDA Regulatory Documents

This post explores how bias can creep into word embeddings like word2vec, and I thought it might make it more fun (for me, at least) if I analyze a model trained on what you, my readers (all three of you), might have written....more

Unpacking Averages: Understanding the Potential for Bias in a Sepsis Prediction Algorithm, a Case Study

Would it surprise you if I told you that a popular and well-respected machine learning algorithm developed to predict the onset of sepsis has shown some evidence of racial bias? How can that be, you might ask, for an...more

Unpacking Averages: Creating an Industry-Specific Index to Track the FDA Regulatory Environment

The regulatory environment at the US Food and Drug Administration (“FDA”) has a tremendous impact on how companies operate, and consequently data on that environment can be quite useful in business planning. In keeping with...more

Unpacking Averages: The Difference Between Data and the Truth: Comparing FDA’s UDI Database with FDA’s 510(k) Database

It is certainly easy, when writing code to accomplish some data science task, to start taking the data on face value. In my mind, the data can simply become what they claim to be. But it’s good to step back and remember the...more

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...more

Unpacking Averages: Using Natural Language Processing to Extract Quality Information from MDRs

Over the spring and summer, I did a series of posts on extracting quality information from FDA enforcement initiatives like warning letters, recalls, and inspections. But obviously FDA enforcement actions are not the only...more

Unpacking Averages: Assessing FDA’s Focus on Enforcing 510(K) Requirements on Imports

A private equity client asked us recently to assess a rumor that FDA was on the warpath in enforcing the 510(k) requirement on medical devices from a particular region. Such a government initiative would significantly deter...more

Unpacking Averages: Assessing Whether FDA’s Breakthrough Device Designation Is Helpful

You might be thinking, that’s an odd title: obviously FDA’s breakthrough device designation is helpful.  However, after looking at the data, my conclusion is that I would avoid the breakthrough device designation for any...more

Unpacking Averages: Common Root Causes Driving Medical Device Recalls

Recalls have always been a bit of a double-edged sword. Obviously, companies hate recalls because a recall means their products are defective in some manner, potentially putting users at risk and damaging the brand. They...more

Unpacking Averages: Violations Found in Medical Device Warning Letters

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...more

Unpacking Averages: Device Inspection Citations That Frequently Precede Warning Letters

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...more

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

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...more

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