IHD Data Science module accelerated an analytics project from months to weeks
Unnamed (pharma team) iHD Data Science module accelerated an analytics project from months to weeks — the customer is anonymised in the vendor’s own case study, not withheld by us. Named alongside Norstella in Norstella’s own account of this story: IHD Data Science.
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.
Published by Norstella on its own site — read the original case study on panalgo.com ↗
Related use cases
- 01MMIT used NorstellaLinQ to merge unstructured EMR data with structured data to detect disease screening patterns and drive commercialization strategy
- 02MMIT used NorstellaLinQ real-world data to narrow a target patient population and improve physician targeting
- 03MMIT used NorstellaLinQ to give a clearer real-time picture of high-risk patients and the physicians treating them
- 04Panalgo linked unstructured EMR data (via NorstellaLinQ) with closed claims data for an HEOR study on knee arthroplasty, delivering years of longitudinal data in 8 weeks
- 05"NorstellaLinQ: Better together — Getting the full patient picture" use case
- 06CRO used Citeline to validate site/investigator hypotheses for a Phase III oncology "trial rescue," uncovering protocol constraints and competitive-intensity insights