Beyond the black box: rethinking adverse event prediction in light of the FDA’s push for AI transparency

By Dr Nicola Davies

Artificial Intelligence (AI) is reshaping pharmacovigilance, promising faster detection of safety signals hidden within mountains of adverse event (AE) data. However, as the US Food and Drug Administration (FDA) sharpens its focus on transparency, credibility, and real-world monitoring, the days of relying on opaque algorithms are numbered. In this article, we explore why sponsors and safety teams must rethink their approach to AE prediction to ensure the very tools designed to protect patients don’t become risks themselves.