Since the onset of the COVID-19 pandemic, the Food and Drug Administration (“FDA”) has received more attention than perhaps ever before. While Americans anxiously awaited for approval of a COVID-19 vaccine, the FDA and its regulatory scheme were ever-present topics on the news and in social media. The American population’s newfound familiarity with the FDA is especially pertinent in a medical device litigation context. As litigators well know, jurors already enter a courtroom with preconceived notions of medical device companies, the FDA and the relationship between the two. So how will this newfound knowledge of the FDA influence juror opinions? Put another way, what would happen if a jury participating in a medical device trial failed to hear any reference to the FDA at all? Potentially, the results would be catastrophic to device manufacturers.
With each passing year, the long-predicted aspirational advantages of 3D printing in the life sciences industry become a reality. Forecasts of large scale printing operations at or near major hospitals are fulfilled. Visions of bioprinted organs have become a reality. 3D printing is reaching the lofty potential projected by the life sciences industry years ago. However, the topic of litigation risks with 3D printing in the life science industry is often overlooked. […]
Yet, the widespread use of additive manufacturing by companies and individuals outside of the life sciences industry also underscores the potential litigation risks with 3D printing.
Artificial intelligence (AI), once little-known outside of academic circles and science fiction films, has become a household phrase. That trend will continue to expand as the public becomes more exposed to AI technology in everyday products, ranging from their cars and home appliances to wearable devices capable of tracking the metrics of their everyday routines. Perhaps no facet of AI has sparked observers’ imaginations more than machine learning (ML), which is precisely as it sounds: the ability of computer programs to “automatically improve with experience.” Machine learning lies at the heart of the kind of independent and superhuman computer power most people dream of when they consider AI.
While the public’s imagination is free to run wild with the promises of ML—creating an appetite that will no doubt be met with an equal and opposite response from businesses around the world—traditional policy and law-making bodies will be left with the task of trying to adapt existing legal and regulatory frameworks to it. Therefore it bears consideration how existing products liability norms might apply to AI/ML-based products, if at all, and what sort of uncertainties may arise for product manufacturers, distributors, and sellers. No enterprise better illustrates the careful balance between the endless potential of AI against the unique risks of products liability concerns than the medical device industry. This article discusses the uses and unique benefits of AI in the medical device context, while also exploring the developing products liability risks.