CASE STUDIES
AI-assisted data stewardship for faster study start-up.
Unifying clinical, contracting, and enterprise data with Reltio, Pfizer adopts AI-supported stewardship to reduce manual work, improve decision quality, and support faster study start-up.
"We’re looking across the entire value chain to reduce time from drug discovery to commercialization. The goal is to get therapies to patients faster and drive revenue impact sooner."
Nishith Trivedi
Global MDM and Enterprise Data Governance Lead
25%
projected study start-up time reduction
80-90%
due diligence time reduction goal with AI agent
30-40%
goal to reduce data steward backlog from 250K+ records
Cumbersome research by investigators slowed study start-up and due diligence.
Pfizer needed a more connected view of investigators, providers, and related activity to support faster study start-up, stronger analytics, and more coordinated compliance work.
Pfizer’s teams worked across separate clinical, contracting, and enterprise data environments. This made it difficult to see a consistent view of investigators, providers, and related activity across the workflows that support study start-up, recruitment, analytics, and compliance.
Because teams could not see a full, consistent picture of the same person across clinical and enterprise workflows, critical work depended on manual interpretation and repeated research. Due diligence teams checked internal systems alongside state and federal sources, while compliance and medical teams struggled to connect activity, spend, and engagement context.
Pfizer wanted to unlock new cross-functional use cases and get therapies to patients faster. To do that, it needed a trusted data foundation that could connect profiles, reduce repetitive work, and support governed AI-assisted decisions in its highly regulated environment. Key goals to:
- Connect investigator and provider data across clinical and enterprise workflows.
- Reduce manual due diligence and repetitive cross-system research.
- Reuse trusted third-party and internal data across teams.
- Support faster study start-up with governed, AI-assisted stewardship.
“In a regulated industry, Pfizer cannot afford to get the identity of clinical investigators wrong. Accuracy matters because it affects patient and drug sample routing, site execution, spend reporting, and trust.”
Nishith Trivedi
Global MDM and Enterprise Data Governance Lead
Unified data gives Pfizer a strong foundation for faster study execution and AI agents.
Pfizer used Reltio to bridge clinical investigator data with enterprise provider and organization profiles, so the same person or entity could be understood across workflows. By focusing on investigators, organizations, sites, addresses, and affiliations, teams gained a more consistent foundation for due diligence, study start-up work, recruitment support, and compliance analysis. And the ability to create and adopt effective AI agents to increase productivity and speed.
Pfizer is also applying AI-assisted stewardship where it adds clear value—including cross-language comparisons, transliteration, web research, and recommendation reporting for human review. This helps teams work faster while keeping human judgment in the loop where accuracy is critical.
Why Pfizer chose Reltio.
Pfizer had a trusted foundation, but disconnected MDMs prevented unified clinical and enterprise profiles, increased manual work, and limited governed, AI-assisted decision-making in regulated workflows.
Unified, context-rich profiles.
Support study start-up, due diligence, analytics, and compliance with a more consistent view of investigators, providers, organizations, and related enterprise data.
Decreased manual research.
Reuse trusted internal and third-party data to reduce repetitive due diligence work and give teams faster access to the information they need across workflows.
Governed AI assistance.
Apply AI-assisted stewardship, transliteration, and recommendations—while keeping human review in the loop for sensitive decisions in this highly regulated environment.
Our solution for Pfizer’s clinical and enterprise data.
Bridge investigator and provider profiles.
Connect clinical investigator data with enterprise provider and organization profiles so the same entity can be understood across workflows.
Unify the domains that enable study start-up.
Bring investigators, organizations, sites, addresses, and affiliations together to support due diligence, recruitment, and compliance analysis.
Reuse trusted data already used in the business.
Make existing internal and licensed reference data easier to use, reducing repeated research across teams.
Add AI-assisted stewardship with human review.
Use cross-language comparison, transliteration, web research, and recommendation reporting to speed complex reviews—while keeping final approval with people.
Extend connected data into more workflows.
Support medical analytics, recruitment-related context, and compliance analysis with one consistent foundation.
Discover more success stories.
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