AI IVDR Medical Devices

Data types in this case study: Digital Pathology, histopathology, H&E, IHC

Case Study Highlights

In this case study we share our collaboration with the Precision Medicine Centre at Queen’s University, aimed at advancing AI-powered cancer diagnostics tools to improve pathology analysis' efficiency and accuracy. By partnering with the government and the NHS we are working towards enhancing traditional pathology with cloud-based IVD medical devices. These devices focus on specific cancer tests and utilize AI for analyzing whole slide images, streamlining the diagnostics process for conditions like Colorectal Cancer and Non-Small Cell Lung Cancer. This approach not only promises faster and more consistent test results but also leverages secure, scalable cloud technology for broader, more effective deployment.

NHS AI Lab - The Organisation

The NHS AI Lab creates an environment for collaboration and co-creation by bringing together programmes addressing barriers to developing and deploying AI systems in health and care. This will unlock the potential of AI to revolutionise healthcare whilst ensuring we can determine the right guidance and regulations to protect patients.


We are working in partnership with several government and NHS partners. We are also engaging with the people developing and using AI and members of the public potentially benefitting from it. To find out more, visit NHS AI Lab: Get involved.


The Artificial Intelligence (AI) in Health and Care Award aims to benefit patients by combining the power of artificial intelligence with the expertise of the NHS to improve health and care outcomes.


The Award has committed £123 million to accelerate the testing and evaluation of technologies most likely to meet the aims set out in the NHS Long Term Plan.

The Challenge

Tests carried out by pathologists on cancer biopsy tissue help determine the best clinical pathways for patients. Annually in the UK, around 43,000 patients are diagnosed with colorectal cancer, and 36,000 are diagnosed with non-small cell lung cancer. Rapid and accurate testing is critical, but testing is expensive, results can be slow, and inaccuracies may occur.


The following difficulties arise with the administration of these tests:


  • Slow test results - the current standard lab tests for MSI typically have a two-week turnaround time.
  • Challenges in conducting traditional manual PD-L1 scoring are recognised as time-consuming and difficult, leading to potential inconsistencies and inaccuracies.
  • High cost to the NHS, with an annual expenditure of £11.1m to £15.5m.
  • Inconsistent provision and availability of testing across regions.

The Difference Sonrai Makes

Every organization is unique, and generic solutions fall short in addressing their distinct challenges. Sonrai is purpose-built to tackle the complexities of precision medicine, offering tailor-made solutions that align with your specific needs.

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Do These Challenges Sound Familiar?

We are partnering with clients to develop a suite of medical device algorithms that enables AI to revolutionise pathology workflows and discover the right treatment for every patient.

The Strategy

Sonrai Analytics is developing a suite of transformational cancer diagnostics tools using AI-powered computational pathology to aid pathologists. This will enable faster and more accurate patient test results.


In collaboration with the Precision Medicine Centre (PMC) at Queen’s University, our expert teams are developing new Artificial Intelligence IVD medical devices. The cloud-based devices enable pathologists to upload whole slide images of resections and biopsies and analyse annotated regions of interest using Sonrai Analytics algorithms. The results of this analysis are used to assist and augment the existing manual and wet lab processes, improving consistency and turnaround times.


Our initial IVD medical devices will focus on MSI testing of Colorectal Cancer cases (for Lynch Syndrome testing) and Tumour Proportion Scoring for PD-L1 in Non-Small Cell Lunch Cancer samples. These will be implemented as applications in a CE-IVDR-approved platform, enabling viewing and annotation in a simple, intuitive manner and allowing the applications to be deployed natively in the cloud, with the benefits of scalability and speed cloud computing allows. The platform will also implement a best-in-class design to secure and control data.


Three IVD Medical Devices as clinical tools

At the end of the project, the devices will be ready for submission to a designated Notified Body for EU IVD Regulation (IVDR) conformity assessments.

Approved Icon
Apply CE mark in line with IVDR

After completing the project scope, Sonrai Analytics intends to submit these devices for conformity assessment, apply the CE mark in line with IVDR and release them to markets globally. 

Market Access
Unique Market Access in GB and NI

As Sonrai Analytics are a Northern Ireland-based legal manufacturer, we have unique access to the European and Great British markets.

Discover how companies worldwide grow with Sonrai. Explore all case studies.

Integrating Digital Pathology Data to uncover novel insights

The digitization of glass slides opens up the opportunity to apply computational pathology and AI technologies to interpret the pathology information within the resulting high resolution digital pathology images.

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AI in healthcare brings opportunities to assist scientists and healthcare professionals in improving patient care and outcomes.

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