Developing Effective Patent Strategies for Personalized Medical Devices in Europe and the US

Market reports indicate the global medical device industry for Q3 2024 saw an increase in merger and acquisition (M&A) activity in terms of value year-over-year. Although deal value decreased compared to...

As the FTC continues to crack down on pharmaceutical manufacturers’ allegedly improper listing of patents in the FDA Orange Book, counsel for Teva and Amneal presented oral arguments in the Court of Appeals for the Federal Circuit on November 8,...

Software is increasingly used as a medical device, transforming the healthcare industry with the goal of improving patient outcomes. However, developing software as a medical device involves navigating complex and evolving regulatory frameworks. Regulatory frameworks can complicate the already complex problem of innovation in software and can often run roughshod over the distinctions between software, artificial intelligence, machine learning, and deep learning. Development in each of these areas is known to progress in leaps and pauses and can occur at any point from data collection to testing, design, development, or deployment. Yet as human involvement leads to opportunities for technological improvements, human touchpoints can also lead to mistakes and biases.