AI is becoming a central player across life sciences and throughout product life cycles, and AI in pharmacovigilance is no exception to this shift. From early safety monitoring to post-marketing surveillance, pharmacovigilance automation is increasingly supported by advanced AI technologies.
AI is already embedded in safety operations to detect, assess, and help prevent adverse drug reactions. However, as adoption accelerates, one question becomes critical: how do we ensure that innovation does not outpace responsibility? This question is relevant across all domains, but it is particularly crucial in pharmacovigilance, where patient safety is directly impacted.
The answer emerging from regulators, industry bodies, and global organizations is clear: AI in pharmacovigilance must be governed by strong principles, anchored by human oversight.