Your AI is only as good as the evidence it reads. Many organizations run their own AI agents over key sources such as PubMed, ClinicalTrials.gov and drug labels. But access to data is not the same as answers you can trust. The evidence behind a scientific question is spread across many sources (such as literature, trials, regulatory documents and internal knowledge), and it isn't always ready for AI-driven evidence synthesis.

Join this expert-led live presentation and Q&A to learn what it takes to prepare scientific evidence for reliable AI use, including organizing scientific meaning through content enrichment, expanding coverage and strengthening confidence in the answers. See how these approaches are delivering measurable business and scientific outcomes across R&D, medical affairs, health economics and outcomes research, and beyond.

Who should attend

Enterprise AI & Data executives and functional leaders in Pharma interested in:

• Drug discovery and R&D - Medical affairs and medical information
• HEOR and market access

What you’ll learn

• How organizations are achieving measurable results from AI-driven scientific inquiry. Examples include shortening the path to an investigational new drug application by three years, and integrating news, literature and other data streams into a share-of-voice tracking capability for medical affairs.
• What it takes to get from data to decisions: why bringing content in-house is only the first step, and the gaps in coverage, content enrichment and traceability that stall AI projects.
• How IQVIA AI Scientific Navigator, an AI-ready content foundation, helps your AI, agents and teams get reliable, evidence-backed answers to scientific questions.