A pioneering project led by Dr Charles-Antoine Collins-Fekete and Professor Maria Hawkins from UCL Medical Physics & Biomedical Engineering has been awarded a Medical Research Council (MRC) Gap Fund with an outstanding score of 9/10. The funding will support a pilot deployment study of Octopath, an artificial intelligence (AI) platform designed to help pathologists deliver faster and more accurate cancer diagnoses.
Addressing a national challenge
Pathology services in the UK are facing increasing pressure, with a shortage of specialist pathologists and the rising complexity of modern cancer diagnostics leading to longer waiting times and delays to treatment. These challenges impact both patients and the NHS, creating unsustainable workloads and inefficiencies.
Octopath offers a potential breakthrough. Acting as a co-pilot for pathologists, the AI system rapidly analyses digital images of tissue samples and highlights key diagnostic features, helping clinicians interpret complex data more efficiently.
Bridging the gap between research and clinical use
While the Octopath prototype has shown high accuracy in research settings, it has yet to be validated in real-world clinical environments, a key step required before regulatory approval and NHS implementation.
The MRC funding will enable a multi-site clinical validation study, deploying Octopath across two NHS partner sites. The team will analyse anonymised samples from multiple cancer types, including colorectal, breast, and pancreatic cancers. The study will rigorously assess Octopath’s performance against expert pathologist assessments and gather feedback on usability and workflow integration.
Transformative impact for patients and the NHS
If successful, Octopath could help reduce diagnostic waiting times, streamline workloads, and support the delivery of more personalised cancer treatments. The project’s outcomes will also provide the evidence base needed for regulatory submission, future clinical trials, and potential commercialisation through a UCL spin-out.
The core team
- Dr Charles-Antoine Collins-Fekete, Project lead, University College London
- Prof Maria Hawkins, Project co-lead (UK), University College London
- Dr Zhuoyan Shen, Researcher co-lead, University College London
- Dr Konstantin Bräutigam, Research and Innovation Associate, Institute of Cancer Research
- Dr Adam Levine, Research and Innovation Associate, University College Hospital
- Prof Manuel Rodriguez-Justo, Research and Innovation Associate, University College Hospital
Image
Advanced Cell Detection – Octpath’s AI-powered solution revolutionises cell detection and classification in digital pathology. By leveraging cutting-edge machine learning algorithms, Octopath can accurately identify and label various cell types within complex tissue samples.
