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Life Science Newswire Service™ (LS) > Blog > Life Science Magazines > Patient First Starts with Process First: Transforming R&D…
Life Science Magazines

Patient First Starts with Process First: Transforming R&D…

By Newsroom
Last updated: May 29, 2026
2 Min Read
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Join this live webinar to learn more.

Every Life Sciences company wants to accelerate time to market, but Novo Nordisk is actually doing it. Join us to hear directly from Stephanie Bova, CVP R&D at Novo Nordisk, on how the company is leveraging AI and Process Intelligence to accelerate drug development and improve operational execution across R&D.

As Stephanie notes, “Without Process Intelligence, Enterprise AI at scale is hopeful thinking”. Across Drug Discovery, Clinical Development, Regulatory Affairs, Quality, and Patient Safety, critical processes remain fragmented, manual, and difficult to orchestrate. This complexity limits the impact of AI initiatives and ultimately slows down patient outcomes.

In this webinar, you will discover how to enable real transformation. We will explore how leading pharmaceutical organizations can leverage Process Intelligence to create real time visibility across systems, teams, and functions. Learn how to uncover bottlenecks, reduce cycle times, improve execution, and drive intelligent, data driven operations across the R&D lifecycle.

Attendees will learn:

  1. The Novo Nordisk Impact Story: A featured customer perspective on their R&D transformation journey, including how they use AI to resolve bottlenecks, key lessons learned, and the business impact achieved.
  2. The Foundation for AI: Why process centric transformation and creating a “digital twin” of your operations is becoming the mandatory foundation for successful Enterprise AI adoption in R&D
  3. Industry-Wide Applications: Real world examples of how leading pharma organizations are transforming with Process Intelligence and AI across the broader R&D lifecycle.
  4. Live Demo: See how Celonis delivers end-to-end visibility, identifies bottlenecks, and enables AI-driven execution across a core Clinical Operations process.


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