What we do

We find more of the right patients

Volv Global’s inTrigue machine learning technology identifies undiagnosed and misdiagnosed patients across population scale electronic health records (EHRs) and real world data (RWD). This allows us to uncover more people living with a disease beyond those already diagnosed, ensuring that no patient is left unseen.

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

The importance of diagnosing the undiagnosed and the misdiagnosed

In today’s vast sea of medical data, many patients remain undiagnosed or misdiagnosed, leading to delayed treatments, wasted healthcare resources, and poor health outcomes. 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.

Find the
right patients

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.

Optimise the
patient journey

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.

Find more
patients

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

Impact across the product lifecycle

Clinical
Development

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.

Value, Access
& HEOR

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).

Medical
Affairs

Discover a more precise picture of patients, including biomarkers, phenotypes, and clinical features, to enhance diagnostic capability and support evidence-based medical communication.

Commercial
Excellence

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

How inTrigue finds more patients

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.

AI-Driven Patient Identification: scans vast medical datasets to detect previously overlooked or misdiagnosed patient segments.
Integrated Real-World Evidence (RWE): merges clinical, claims, and healthcare data for a holistic patient journey assessment.
Targeted Patient Engagement: supports personalised treatments and helps pharmaceutical companies accelerate clinical trial recruitment and streamline development.

Transforming Rare Disease Diagnosis with AI

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:

Accelerate rare disease detection– identify subtle patterns in patient records years before conventional methods.
Support precision medicine– enable personalised treatment pathways based on biomarker and phenotype insights.
Improve clinical trial efficiency– expand the patient pool with correctly identified candidates, reducing time-to-recruitment.
Enhance healthcare outcomes– shorten the diagnostic odyssey for patients while reducing costs for healthcare systems.

Explore our case studies to see how we’re already helping pharmaceutical innovators find more patients, faster.

What people ask

Questions About Finding The Right Patient

Volv Global’s inTrigue technology applies AI and machine learning to analyse electronic health records (EHRs), claims data, and real-world evidence. 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