AI That Holds Up to Scrutiny: Why Pharma Needs Verified Knowledge at its Core

As pharmaceutical companies integrate artificial intelligence across research, development, and commercial functions, one critical factor often goes underappreciated: the reliability and provenance of the content powering those models. While attention is often placed on algorithms and compute infrastructure, the quality of the underlying data, particularly scientific and medical content directly impacts model accuracy, explainability, and regulatory defensibility.

This session will explore why the use of verified peer-reviewed content is foundational for building AI that meets the scientific and policy standards expected in healthcare. With the EU AI Act and US policy discussions on AI/ML in drug development and evolving global frameworks placing growing emphasis on traceability and transparency, the stakes for using trusted content have never been higher.