Case Study: Pharma Company Leverages IHD Data Science

A pharmaceutical company faced lengthy analytics-project timelines that slowed insight generation for observational studies. It adopted Panalgo's IHD Data Science module, which the page credits with "unprecedented time to insights," "cutting-edge machine learning," and "enhanced study design and execution." The visible content says the project timeline compressed from "months to mere weeks," but gives no specific figures, sample sizes, or further methodology — the full case study is only available as a PDF download.

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.