Transforming Oncology Forecasting at a Clinical-Stage Biotech

A clinical-stage biotech with a broad oncology pipeline faced forecasting challenges ahead of a pivotal Phase III launch. It engaged J+D Forecasting to overhaul its approach, moving "from fragmented, finance-led models to a scalable, best-practice forecasting framework," adopting a patient-flow methodology using Onco+, upskilling internal teams via hands-on coaching, and building a platform "to prioritize assets and support commercialization." The page does not disclose specific quantitative results — full metrics require downloading the case study.

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.