The complexity of market access
has outgrown its tools.

Kintiga, a leading pan-European market access consulting firm, recognised that the scope and timelines of the EU Joint Clinical Assessment framework requires a new approach to dossier compilation. Quoting Dr. Lydia Frick: “Let robots do the boring work!”

After a comprehensive workflow assessment, the clinical evidence section stood out as a prime point of AI leverage: highly repetitive work, requiring an almost super-human level of attention to detail and stamina. Semi-automating this work did not only promise significant gains in efficiency, but also much-needed agility when new data cuts arrive just before a deadline.

Together with the Kintiga team of medical writers, we built EPRI, the first-ever AI tool for endpoint result interpretation. With EPRI, medical writers can now compile clinical evidence sections in a fraction of the time, ensure consistency throughout and create a coherent value story.

Under the EU JCA framework, the requested PICOs arrive late in the cycle. Teams have to react fast, often without the benefit of seeing how comparator selection will play out across member states.

To get ahead of the cycle, we built a PICO prediction system that takes a label or indication and extrapolates from there — first identifying precedence drugs across European HTA history, then mapping standard of care per country, then synthesising a per-country PICO prediction, and finally consolidating those into the most likely EU-level question.

This does not replace expert analysis and judgement, but it gives them a headstart.