Volv Global Puts AI at the Heart of Rare Disease Diagnosis

Volv Global, healthcare AI company headquartered at Biopôle Épalinges (Vaud – Switzerland), has released two significant pieces of work in quick succession that together make a compelling case for rethinking how rare and hard-to-diagnose diseases are detected and funded.

The first is a a retrospective case study applying machine learning to real-world EHR data conducted in partnership with a leading global pharmaceutical company. Applying machine learning to 24 million de-identified UK primary care records, Volv Global’s inTrigue framework surfaced approximately 1,200 patients with records consistent with undiagnosed gastroenteropancreatic neuroendocrine tumours (GEP-NETs) — a rare cancer whose non-specific symptoms (fatigue, abdominal pain, flushing) are routinely attributed to IBS or diabetes. Patients typically wait nearly five years before receiving a confirmed diagnosis, and five-year survival rates for high-grade disease can be as low as 25%.

What makes the finding clinically striking is the age gap: patients identified by the model were 5 to 7 years younger on average than those already diagnosed. While the company is careful not to overstate this — prospective validation is the necessary next step — the implication is significant. Earlier detection in cancers with strong stage-dependent prognosis can meaningfully shift survival outcomes.

The second publication is broader in ambition. Drive For Change, a cross-industry white paper co-authored with leaders from Sanofi, Fondation Ipsen, Unitechpharma and patient advocacy organisation brave2change, confronts a stark statistic: approximately 95% of identified rare diseases still have no approved treatment. The paper argues this is not inevitable — it is the consequence of three fixable structural failures: chronic underestimation of patient populations, incomplete understanding of rare disease biology, and health technology assessment frameworks that systematically undervalue the full societal cost of these conditions.

Volv Global’s own data anchors the argument. In one case study, its methodology identified 3.2 times the expected patient count for a neuroendocrine tumour indication. In a prospective UK primary care pilot for Fabry and Pompe disease, diagnosis rates up to doubled over a period during which they had been flat for a decade.

“Rare disease drug development is stuck in a self-fulfilling loop: small estimated populations, fragile business cases, programmes shelved before they reach patients,” said Christopher Rudolf, CEO and Founder. “Drive For Change names the loop — and shows that with real-world data and modern AI, the addressable population is almost always larger than the sponsor believed.”

Volv Global is not merely a data analytics vendor but a company trying to reshape the economics of rare disease medicine — starting from its base in the Swiss Health Valley ecosystem, and working across more than 400 million patient records worldwide.

➡️ Source: Volv Global Press Releases | 📸 ©Volv Global