Press release: AI-Driven Patient Detection Surfaces Approximately 1,200 Likely-Undiagnosed GEP-NET Patients in UK Primary Care
Volv Global applied machine learning to 24M UK primary care records, surfacing ~1,200 undiagnosed GEP-NET patients, 5...
Millions of patients with rare and complex diseases remain misdiagnosed, underdiagnosed, or difficult to within routine healthcare data. Volv Global helps bring these patients into clearer view.
By finding these hidden patient populations, we help people with rare and difficult to diagnose diseases gain access to the right treatment earlier. At the same time, we significantly expand the pool of high quality real world evidence available to accelerate clinical research, drive innovation in precision medicine, and support the development of new therapeutics.
Why accurate diagnosis matters
Rare diseases are often with overlapping symptoms and inconsistent Patients can wait years for an accurate diagnosis, often receiving ineffective treatments in the meantime. This limits visibility into true patient populations, impacting trial recruitment and real-world evidence.
By leveraging AI driven patient identification and real world data (RWD), Volv Global ensures that overlooked patients receive the right care faster, more accurately, and at a lower cost.
Undiagnosed patients face unnecessary suffering, while misdiagnosed patients often receive inappropriate treatments. Accurate diagnosis ensures precision medicine by matching the right treatment to the right patient.
Incorrect diagnoses lead to the wrong tests, treatments, and years of suffering. Our approach helps streamline healthcare pathways, reducing wasted expenses and improving patient outcomes.
Accurately identifying entire disease cohorts improves clinical trial recruitment, rare disease research, and real world evidence generation, creating better insights for the entire healthcare ecosystem.
Volv Global powers solutions across stakeholders
Expand the pool of patients for clinical trial recruitment by identifying undiagnosed and misdiagnosed patients. Our AI-driven approach improves trial design, recruitment speed, and real-world evidence generation.
Gain a wider, more accurate picture of the patient journey and treatment outcomes. Generate health economics and outcomes research (HEOR) insights supported by robust real-world data (RWD).
Discover a more precise picture of patients, including biomarkers, phenotypes, and clinical features, to enhance diagnostic capability and support evidence-based medical communication.
Target patients more effectively with data-driven population insights, enabling market access strategies, earlier diagnosis, and stronger product lifecycle performance.
Industry-leading technology at work
inTrigue harnesses artificial intelligence (AI) and machine learning (ML) to analyse large-scale electronic health records (EHRs), claims data, and real-world evidence (RWE). By detecting hidden patient patterns that might otherwise remain undiagnosed, our platform delivers a comprehensive view of rare and difficult-to-diagnose diseases. This empowers providers and pharmaceutical companies to deliver earlier, more accurate, and more targeted interventions.
The millions of patients who remain undiagnosed or misdiagnosed every year, especially in the field of rare diseases. This , creates significant challenges for clinicians, pharmaceutical companies, and healthcare systems.
Volv Global’s inTrigue platform bridges this gap by combining AI, machine learning, and real-world data (RWD) to:
Explore our case studies to see how we’re already helping pharmaceutical innovators find more patients, faster.
What people ask
Using our proprietary technology inTrigue, Volv Global analyses population-scale EHR and insurance claims data to discern patterns in phenotypes and biomarkers for specific diseases – and then surface the patients who match. It detects subtle medical patterns that traditional methods often miss, allowing healthcare systems and research partners to find undiagnosed or misdiagnosed patients faster and with greater accuracy.
Misdiagnosed patients often receive inappropriate treatments or experience long delays in diagnosis. Correctly identifying them enables timely and accurate care, reduces unnecessary healthcare spending, and improves treatment effectiveness across entire patient populations.
By uncovering previously unidentified patients, Volv Global helps strengthen trial protocols, expand recruitment pools, and improve real-world evidence (RWE). This leads to better disease characterisation, faster recruitment timelines, and more reliable outcomes for HEOR and value assessment studies.
Yes. inTrigue integrates securely with hospital EHRs, claims databases, and research platforms. This enables real-time patient identification and early detection while fully supporting GDPR, HIPAA, and global data-protection standards.
Volv Global combines AI-driven analytics with deep clinical expertise to deliver accurate, ethically aligned insights. Unlike traditional modelling, inTrigue continuously learns from new data, enabling partners to find more of the right patients, enhance outcome prediction, and improve patient stratification for research and clinical care.
Shaping the future today
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