What we do

We detect diseases at an earlier stage

Volv Global’s inTrigue machine learning technology detects incidence of disease earlier than currently possible, by analysing vast amounts of medical data to detect subtle patterns among biomarkers.

This ensures that people on the path to developing diseases can have start their healthcare journey early by receiving early interventions. This improves patient outcomes, reduces healthcare burdens and improves quality of life.

Why early detection matters

The importance of early diagnosis

Early detection of diseases can significantly alter the course of treatment and improve prognosis. Patients diagnosed early often have better health outcomes, fewer complications, and a higher quality of life. By uncovering patients at the earliest disease stages, we ensure timely medical interventions.

Improved
patient outcomes

Early treatment, before serious onset of disease, can hinder disease progression and reduce long-term complications for patients.

Enhanced
clinical trials

Clinical trials benefit from a larger patient cohort. Identifying suitable candidates earlier, before conventional treatment, bolsters clinical trial recruitment and leads to more effective trials.

Personalise
the patient journey

Early diagnosis ensures an optimal patient journey, in which patients receive the right treatments saving years of patient suffering and reducing long-term healthcare costs by prioritising medical resources by need.

Volv Global’s inTrigue powers solutions across stakeholders

Impact across the product lifecycle

Clinical
Development

Earlier triage of patients into a clinical trial before they are given traditional therapies.

Value, Access
& HEOR

Earlier triage of patients, potentially saving years of incorrect treatment.

Medical
Affairs

Physician support for diagnosis of patients before the development of traditional symptoms.

Commercial
Excellence

Find patients before the development of traditional symptoms.

Industry-leading technology at work

How inTrigue enables earlier detection

inTrigue employs sophisticated AI and machine learning algorithms to sift through vast amounts of medical data, identifying subtle patterns that indicate the early presence of diseases. Our technology surpasses traditional methods, ensuring that no potential patient is overlooked.

AI-Driven Insights: detects early signs of disease by analysis of electronic health records, claims data, and other medical records.

Pattern Recognition: identifies subtle indicators and correlations that might be missed by conventional diagnostics.

Comprehensive Data Analysis: combines structured and unstructured data for a holistic view of patient health.

What people ask

Questions about diseases detection at an earlier stage

A: Volv Global’s inTrigue uses advanced AI and machine learning to analyse large-scale medical data, including biomarkers, EHRs, and real-world evidence. It identifies subtle health patterns that signal early disease development—enabling earlier intervention and improved patient outcomes.

A: Early detection helps prevent disease progression, enables timely treatment, and reduces healthcare costs. Volv Global’s technology improves patient quality of life and assists providers in correctly diagnosing more patients before symptoms become severe.

A: Volv Global’s solutions benefit clinical development, medical affairs, HEOR, and commercialisation teams by enabling early patient triage, supporting data-driven trial recruitment, and improving the evidence base for access and reimbursement decisions.

A: inTrigue continuously learns from real-world data and clinical feedback, refining its predictive accuracy over time. This adaptive learning approach ensures high precision and sensitivity, allowing healthcare systems to detect diseases earlier than traditional diagnostics.

A: Volv Global operates under strict GDPR and HIPAA compliance, ensuring all data is anonymised and securely handled. Its AI models follow ethical AI principles, maintaining transparency, fairness, and accountability throughout every prediction process.

Shaping the future today

Real-world impact

MASH/NASH: Why Therapeutic Breakthroughs Demand a New Era of Patient Identification

- 05/12/2025

Bridging gaps across the CLL care pathway – Part 2: Knowing When To Treat

- 20/11/2025

Bridging gaps across the CLL care pathway – Part 1: From Signal to Stratification

- 04/11/2025

Cracking the Multiple Myeloma Code: Why Systemic Change is Needed to Match Therapeutic Breakthroughs

- 21/10/2025

Unlocking the Future of Type 1 Diabetes Care: Why Earlier Diagnosis Must Match Innovation in Treatment

- 15/10/2025

Beyond Quick Fixes: How Predictive Modelling Can Redefine Clinical Trial Enrolment

- 21/08/2025

Beyond Initial Treatment: Navigating Recurrence Risk and Clinical Decisions in Cancer Survivors

- 08/07/2025

Unlocking the Full Impact of Breakthrough Therapies in Breast Cancer Through Earlier Detection

- 27/06/2025

Progressive Pulmonary Fibrosis: Solving the Puzzle of Poor Disease Control

- 23/06/2025

We detect diseases at an earlier stage

The importance of early diagnosis

Improved patient outcomes​

Enhanced clinical trials

Personalise the patient journey

Impact across the product lifecycle​

Clinical Development

Value, Access & HEOR

Medical Affairs

Commercial Excellence