Webinar

Reducing missed evidence with AI‑enabled literature mining

AI Summer Series Webinar

Artificial intelligence (AI)-enabled literature mining is playing a growing role in how regulatory teams manage expanding evidence volumes—helping distinguish signal from noise without sacrificing traceability or rigor. When applied responsibly and combined with human oversight, AI-assisted approaches can support more comprehensive, reproducible literature searches and reduce the risk of missed evidence that can lead to downstream regulatory rework. Watch the recording to see how AI-assisted literature mining can improve search quality, surface relevant evidence earlier, and support more defensible regulatory literature searches.

Key highlights

  • Improving search quality and sensitivity: How AI‑assisted literature mining can help reduce noise, surface relevant evidence more effectively, and lower the risk of missing critical publications.
  • Traceability and defensibility in practice: How AI‑supported approaches can enable reproducible, well‑documented searches that stand up to regulatory review.
  • Reducing downstream rework: Where earlier, higher‑quality evidence identification can help minimize late‑stage revisions and regulatory remediation.
  • Human oversight and responsible use: How teams are combining AI tools with scientific and regulatory expertise to maintain rigor, transparency, and confidence in submission‑ready outputs.

Moderator:
Chris Englerth, Director of Global Consulting Services, Cencora

Speakers:
Shilpa Patil, Senior Scientist, Cencora
Angela Vogt-Eisele, Director, Clinical Development Services, Global Medical Writing, Cencora

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