SPS04 - From Pilot to Production: A Pfizer and Vivpro AI Case Study on Scaling AI-Enabled Document Generation Across R&D
Information
As life sciences organizations move beyond AI experimentation, the real challenge is not proving potential, it is scaling responsibly, sustainably, and measurably. This session presents a practical case study from Pfizer and Vivpro AI on how AI-enabled document generation is evolving into an enterprise-scale, governed production capability across R&D.
Rather than focusing on vision alone, this session will walk through the actual operating model used to scale: how cross-functional alignment was achieved, how quality and compliance expectations were embedded by design, and how change management enabled adoption across teams. Attendees will gain transparent insights into what worked well, what did not, and what the team would approach differently if starting again.
The speakers will share strategies for measuring value for R&D document generation with a focus on business impact.
Participants will leave with transferable patterns and practical guidance for moving from successful AI pilots to sustainable enterprise deployment of AI-enabled document generation for several document types across the medicinal product development lifecycle. This session is designed for leaders and practitioners seeking real-world lessons, implementation frameworks, and actionable insights they can apply within their own organizations.
AI-generated summary
Pfizer and Vivpro AI presented a case study on scaling AI-enabled document generation across R&D using the Regain platform, emphasizing practical implementation, cross-functional alignment, quality, compliance, and crucial change management strategies.
Takeaways
- Scaling AI in R&D: Pfizer successfully transitioned from AI pilots to enterprise-scale production of AI-enabled document generation across its R&D portfolio, addressing thousands of report types and significant FTE hours.
- Regain Platform Capabilities: The Regain platform offers a unified, AI-powered solution for document authoring, enabling guided generation, structured content, collaborative workflows, and integration with various data sources and templates, ensuring compliance and quality.
- Strategic Implementation: A phased approach from pilot evaluation (using challenging reports and cross-functional teams) to controlled go-live with mandatory adoption, followed by iterative capability building, was key to successful scaling.
- Crucial Role of Change Management: Effective change management, including AI fluency training, bespoke user support, dedicated guidances, a change champion network, and continuous metric tracking, was identified as essential for user adoption and sustainable deployment.
- Leadership Buy-in for AI: Gaining leadership support requires demonstrating real-world use, repeatable and measurable business impact (e.g., time savings, increased productivity), and ensuring the solution meets regulatory standards.
Buzzwords
- AI-enabled document generation
- Scaling AI
- Change management
- R&D lifecycle
- Generative AI
Memorable Quotes
- Pravin Jadhav: creativity should stay with people while heavy lifting is done by the machines, where content generation structure and scale can be handled by technology.
- Helen Kotze: The tools can be the best tool you can have, but unless you've got teams on board who are wanting to use that technology, it doesn't implement on scale.
- Helen Kotze: No option to opt out of using the technology.
- Helen Kotze: being ready for change management and the ability to scale as early on as absolutely possible is crucial to ensure success.
- Jogarao Gobburu: Real-world use. The second one is repeatable and measurable. The third is regulatory grade.
