Indegene built an ML patient-journey model to explain why patients switch androgen deprivation therapies.

The company could measure switching rates in its ADT portfolio but could not explain the drivers across fragmented clinical, access and prescribing data. Indegene built a Random Forest based patient journey platform on real-world data with patient-level risk scoring, a simulation layer for interventions and a GenAI natural-language interface. It found treatment gaps drove 52% of switches, 52% of switches happened within 60 days of initiation, and commercial payer patients switched at 53% versus 40% for Medicare.

Indegene is a healthcare commercialization and technology services firm, used by pharma for AI-assisted content and campaign creation, omnichannel HCP engagement and commercial analytics

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.