Systematic indication expansion for new drug assets

The APAC division of a top-20 pharma company wanted to identify and prioritize alternative indications for one of its most promising drug assets in the APAC market. Clarivate used its proprietary knowledge graph (covering Cortellis Drug Discovery Intelligence and MetaBase) with network algorithms, disease-similarity analysis, and a trained machine-learning classifier to rank thousands of candidate indications by biological relevance to the asset's mechanism of action, narrowing to 10 for literature validation and 5 for commercial/patient-impact assessment in APAC. The client moved the asset into Phase 2 trials for the two prioritized indications, and the case study states all primary and key secondary endpoints were met in both trials, progressing the asset to pivotal trials for both indications.

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

Clarivate owns Cortellis, the curated competitive-intelligence and pipeline-tracking platform standard in pharma portfolio-management teams.

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.