Gain Real-Time Insights on High-Risk Patient Populations with Real-World Data

A multiple myeloma pharmaceutical manufacturer struggled to identify high-risk patients with specific genetic markers and lacked visibility into treating physicians. Norstella integrated EHR, lab, and claims data to build detailed profiles of newly diagnosed and relapsed patients. The engagement delivered "more than 2,000 actionable field alerts," matched patients to specialty providers "with a 90% success rate," and identified 800 newly diagnosed patients, enabling higher patient conversions through improved physician engagement.

The customer is anonymised in Norstella’s own case study — not withheld by us.

Norstella is a holding company merging several pharma-intelligence brands — Citeline (trial intelligence), Evaluate (forecasting), MMIT (payer/formulary data) and Panalgo (real-world analytics) — into one data asset.

This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.