06/03/2025/
Executive Summary For decades, the pharmaceutical industry has faced the same recurring problems with clinical development: the struggle to fully...
With inTrigue, our flagship AI/ML methodology, Volv Global transforms disease management and treatment at the individual patient level.
We use high sensitivity, state-of-the-art machine learning technologies to detect digital biomarkers in human diseases, focussing on areas of significant unmet need or difficult-to-diagnose conditions.
Harnessing the power of inTrigue, we don’t just find patients—we understand them. Our advanced machine learning models provide detailed patient profiles, capturing the nuances of each individual’s health journey.
This deep profiling enables healthcare providers and researchers to tailor treatments and interventions with unprecedented precision. By focusing on personalised insights, we not only enhance the accuracy of diagnoses but also improve the overall effectiveness of care, leading to better health outcomes for patients.
inTrigue uses machine learning to learn digital biomarkers for any human disease as well as developing robust prediction models for difficult-to-diagnose conditions, where there is significant unmet need.
inTrigue generates data-driven insights longitudinally along the patient journey, enabling understanding of disease progression and establishing natural histories.
inTrigue enables precise patient-level insights for disease management, transforming disease management and treatment at the level of the individual, allowing a paradigm shift in targeting accuracy.
inTrigue insights may optimise outcomes across the healthcare ecosystem, removing the economic cost of late or incorrect diagnoses which lead to ineffective treatment programmes, long-term care costs, and deteriorating health.
Insights at your fingertips
inVolv is Volv Global’s secure platform for delivering actionable insights generated by inTrigue directly to partners and clients. It supports data-driven decision-making by providing tailored reporting and analytics for various stakeholders, in the form of interactive filters and visualisations such as charts and heatmaps.
Volv Global started in rare and difficult-to-diagnose diseases
Rare diseases manifest in less than one person among thousands. Doctors have less experience with them, and developers of therapies and payers have less patients to draw understanding from … leaving patients in a healthcare limbo.
Depending on definitions of “rare,” over 300 million people – or 3.5-5.9% of the world population – suffer from 6,000-10,000 rare diseases.
Navigating complexities
With very small patient populations, developing a true understanding of rare disease prevalence, epidemiology, progression, patient journey and outcomes is a complex task.
We had to bridge the diagnostic gap and create tailored machine learning algorithms to learn for themselves how to characterise and identify patients with disease.
Thousands of rare diseases and only 5% have a treatment, leaving 95% unaddressed
For many of these diseases, there is little knowledge and a need to master the complex disease biology
Small, heterogeneous patient populations present challenges for clinical development
"Pipeline herding" means development efforts are unevenly distributed, leaving an unmet needs gap
Not treating rare diseases is costing more than people realise, and we need to reduce healthcare costs overall
Understanding patient phenomenology, across all diseases.
inTrigue helps clinicians to recognise undiagnosed and misdiagnosed patients by profiling patient cohorts by biomarkers, phenotypes, and other clinical information.
inTrigue learns and models the patient journey, finding novel predictors that allow the detection of patients before the first symptoms appear.
inTrigue models patient outcomes to understand and segment patients by their needs for care.
inTrigue makes sense of heterogeneous patient populations, clustering and differentiating cohorts into meaningful sub-groups.
Volv Global powers solutions across stakeholders
inTrigue learns new biomarkers for diseases, enabling more accurate search and identification of patients for clinical trial planning and recruitment.
inTrigue analytics are a valuable resource for natural histories of diseases, and the generation of real-world evidence for regulatory approvals.
inTrigue provides new insights into disease progression, outcomes and endpoints based on proprietary machine learning analytics on real-world evidence.
inTrigue offers patient and disease insights that enable accurate profiling of patients who will benefit the most from specific treatments.
Bridging technology and treatment
Volv Global’s proprietary methods can efficiently extract meaningful insights from sparse, unstructured, messy or inaccurate data in EHRs and claims records, to help identify patients at risk of complex diseases.
The inTrigue methodology builds proprietary computational models using expert machine learning algorithms to detect biomarkers, phenotypes and other clinical features of patients in real-world, population-scale medical data databases such as electronic health and claims records.
inTrigue is customised for each project and learns from available data rather than existing knowledge or guidelines. Automated disease learning is carried out from first principles, producing a mathematical representation of the disease as a starting point in the inTrigue process.
inTrigue produces accurate models and thereby more compelling evidence than other methods. The inTrigue methodology includes independent validation by disease experts and continuous refinement.
Volv Global is a “no data” company. We do not work with identifiable patient data, we do not ingest data. We do not hold patient data, by design, relying on trustworthy data processors in different geographies.
inTrigue works across the entire healthcare ecosystem from GPs to academic centres to data partners and EMR providers. inTrigue algorithms are designed to learn once; and can then be adapted for use across ontologies and systems.
inTrigue can be integrated seamlessly with existing healthcare systems. As individual country systems and data are different, inTrigue learns the model in each country, adapting to differences in clinical thinking, language and data structure.
inTrigue success stories
Our technology has already made a significant difference in the lives of many patients.
Here are a few examples of how Volv Global technology has enabled earlier detection and transformed patient care:
Shaping the future today
Executive Summary For decades, the pharmaceutical industry has faced the same recurring problems with clinical development: the struggle to fully...
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Ready to shape the future of healthcare? Let’s explore how our machine learning solutions can accelerate diagnoses, refine patient journeys, and drive meaningful impact for those who need it most. We value your ideas and expertise, reach out now to unlock new possibilities together.