The pharmaceutical industry is in the middle of a meaningful shift in research strategy. For many years, research teams pursued blockbuster drugs—compounds designed to treat common conditions shared by large segments of the population. Novel treatments for high blood pressure, diabetes, elevated cholesterol, and other widespread ailments were the gold standard.

In a recent post on this blog, we examined how artificial intelligence (AI) and machine learning (ML) are reshaping the informed consent process in clinical trials—and why the regulatory and legal frameworks surrounding AI in that context are still catching up. That article focused on one corner of the clinical trial lifecycle. This one broadens the lens. Medical devices, and in particular software as a medical device (SaMD) is a different but related category.

In a recent episode of HBO Max’s The Pitt, an emergency-room attending physician shows medical students the time savings that can come from using a generative artificial intelligence (AI) tool to listen to a doctor–patient conversation and populate a medical record in seconds. But the same storyline highlights the downside: the tool invents details, confuses medications, and even swaps “neurology” for “urology”—mistakes that could put a patient at risk.