What challenges did Pangaea Data face before AI implementation?

Strict privacy regulations limit partnerships and restrict data sharing. Characterizing patients was time-consuming, occupying up to 52% of clinicians' workdays. High rates of undiagnosed, misdiagnosed, or miscoded patients across conditions. Manual reviews or NLP-based solutions proved inefficient and led to poor outcomes.

What was the impact of the AI solution?

6x more cancer patients identified, totaling 200,000. Reduced treatment costs from £10,000 to £5,000 per patient. Saved £1 billion annually for the NHS. Increased revenue by 6x for pharmaceutical companies using the solution.

Source

MicrosoftLive sourceProductionEvidence: High85/100

Pangaea Data optimizes patient characterization for clinical trials

Use case typeTherapeutics discoveryUpdated Jun 13, 2026

Pangaea Data partnered with Microsoft Azure to address inefficiencies in clinical trials and ensure data privacy. By leveraging Azure services, including Virtual Machines, Container Instances, Blob Storage, Health Data Services, and AI tools like Text Analytics for Health and OpenAI, they implemented a solution to characterize patients efficiently while preserving data privacy. This enabled clinicians and pharmaceutical companies to identify undiagnosed and misdiagnosed patients across 7,000 conditions. Key achievements included a collaboration between two pharmaceutical companies and the UK’s NHS, leading to improved trial efficiency, cost reductions, and significant financial savings. Through this partnership, Pangaea Data also expanded globally using the Azure Marketplace and Microsoft’s co-sell program.

Organization: Pangaea Data
Industry: Healthcare
Location: United Kingdom
Published: October 2023

Reported outcomes

quantified impactOther quantified impact

6xrevenue

Strategic outcomes

Customer experience & trustImproved privacy-preserving patient characterizationNew product / capabilityIdentified undiagnosed patients across conditionsEcosystem & partnershipsCollaborated with Microsoft and NHSMarket & geographic expansionExpanded globally via Azure Marketplace

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 6 x increase

MicrosoftOct 17, 2023Customer storyInferred claimHigh evidence strength

6x more cancer patients identified, totaling 200,000.

Last evidence check: Jul 22, 2026

Normalized claim

Revenue: 6 x increase

MicrosoftOct 17, 2023Customer storyInferred claimHigh evidence strength

Increased revenue by 6x for pharmaceutical companies using the solution.

Last evidence check: Jul 22, 2026

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Pangaea Data, UK NHS
Provider: Microsoft
Maturity: Production
Linked source: Microsoft

Deployed Azure services (Virtual Machines, Container Instances, Blob Storage, Health Data Services)

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1patient characterization
2clinical trials optimization

Strict privacy regulations limit partnerships and restrict data sharing.
Characterizing patients was time-consuming, occupying up to 52% of clinicians' workdays.
High rates of undiagnosed, misdiagnosed, or miscoded patients across conditions.
Manual reviews or NLP-based solutions proved inefficient and led to poor outcomes.

Deployed Azure services (Virtual Machines, Container Instances, Blob Storage, Health Data Services).
Used Azure Text Analytics for Health and OpenAI for patient characterization.
Built solution on Azure ensuring privacy-preserving data processing.
Partnered with Microsoft’s Pegasus Program and utilized Azure Marketplace for scalable deployment.

Technologies

Azure AI Azure ML Azure OpenAI Defender

6x more cancer patients identified, totaling 200,000.
Reduced treatment costs from £10,000 to £5,000 per patient.
Saved £1 billion annually for the NHS.
Increased revenue by 6x for pharmaceutical companies using the solution.

Architecture

Pangaea locally deployed its solution using ARM templates behind the firewall of the data's environment. The product utilizes Azure services (Virtual Machines, Container Instances, Blob Storage, Key Vaults, Microsoft Defender, and Health Data Services) for privacy-preserving processing of patient data. AI tools like Text Analytics for Health and OpenAI enhance patient characterization while leveraging the Microsoft Commercial Marketplace and co-selling strategies.

Sources & evidence2

Evidence: High85/100Evidence strength