Duane Morris will host the third session of its Wearable Webinars Series, Product Liability and IP Strategies for Wearables, on Tuesday, November 4, 2025, 12:00 p.m. to 12:30 p.m. Eastern.
Agatha Liu, Ph.D., will cover how wearables with diagnostic, monitoring or therapeutic claims fall under the FDA’s software as a medical device framework, including predetermined change control plans, good machine learning practices and real-world performance monitoring of adaptive algorithms.
The U.S. Food and Drug Administration’s recent release of two draft guidance documents on the use of artificial intelligence in drug development, biologics and medical devices has sparked both excitement and skepticism. As AI increasingly permeates these fields, the regulatory landscape is just beginning to take shape—and these proposed guidelines take a step in that direction by raising awareness of important questions about the future of AI innovation in life sciences. For therapeutic, medical device and diagnostics companies—whether already implementing AI or just beginning to explore its potential—the message is clear: The landscape is evolving, and future success will require thoughtful consideration of compliance, patient safety and privacy protection from the earliest stages of AI adoption.
Read the full Alert on the Duane Morris LLP website.
With the advent of generative AI models like Med-PaLM and ChatGPT, providers can now type complex medical questions into a chat box and receive sophisticated (and hopefully accurate) answers. This ability surpasses previous AI applications in the potential to serve patients, but also in the potential to run afoul of laws like corporate practice of medicine (CPOM) rules, the False Claims Act (FCA), and FDA regulations. These concerns — on top of the risk of a generative AI model fabricating answers, known as “hallucinations” — mean that providers should proceed with extreme caution before implementing generative AI tools into their practices.
Read the full article by Matthew Mousley on the Wharton Healthcare Quarterly website.
The U.S. Food and Drug Administration (FDA) has issued a draft guidance intended to promote the development of safe and effective medical devices that use a type of artificial intelligence (AI) known as machine learning (ML). The draft guidance further develops FDA’s least burdensome regulatory approach for AI/ML-enabled device software functions (ML-DSFs), which aims to increase the pace of innovation while maintaining safety and effectiveness.
