Trial Tokenization and Linking to Real World Data: Extending the effectiveness and safety analysis of a new focal seizure treatment

A biopharmaceutical company needed to evaluate a newly approved anti-seizure medication used alongside other treatments for focal seizures, running a 36-week Phase IV study across 175 patients at 40 sites, with patient retention as the primary efficacy measure, seizure-frequency reduction as a secondary measure, and tolerability also assessed. The study used trial tokenization to link trial data to real-world data, extending the analysis beyond the initial trial. The page states a substantial number of patients remained on therapy and experienced reduced seizure frequency, but does not give specific percentages on the visible page; authors listed include Ashley L. O'Donoghue PhD, Nayantara Biswas MA, and Tenzin Dechen MPH.

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

Datavant is the tokenization and linkage infrastructure behind most of the US real-world-data ecosystem — it de-identifies and connects patient records across health-data partners without exposing PII.

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.