Pilot Deployment Study of Octopath solution in a clinical scenario

Context The UK's pathology services, which are essential for diagnosing cancer, are facing a critical challenge. An increasing shortage of specialist pathologists, combined with the growing complexity of modern cancer diagnostics, has created a significant bottleneck. This results in longer waiting times for patients to receive a complete pathological diagnosis, which can be a period of great anxiety and can delay the start of treatment. For the NHS, this strain leads to unsustainable workloads and inefficiencies. To ensure patients can fully benefit from the advances in personalised medicine, which rely on detailed and timely diagnostic information, we urgently need innovative solutions to support our expert pathology workforce. The Challenge the Project Addresses Our research team at University College London has developed a promising new technology, the Octopath platform, to help address this challenge. Octopath is an artificial intelligence (AI) tool designed to act as a co-pilot for pathologists. It uses state-of-the-art algorithms to rapidly analyse digital images of tissue samples, automatically highlighting key features that are crucial for understanding a patient's cancer. While our prototype has proven highly accurate in a research setting, it currently lacks the essential evidence to prove it is safe, effective, and reliable in a real-world clinical environment. This evidence gap is the single biggest barrier preventing the technology from gaining regulatory approval and being used to help patients. Aims and Objectives This project aims to bridge that critical gap between a research prototype and a validated medical device ready for NHS use. Our primary objective is to conduct a multi-site clinical validation of the Octopath platform. To achieve this, we will deploy our prototype system into two NHS partner sites across the UK. Working closely with clinical teams, we will use the platform to analyse a large collection of anonymised patient samples across several cancer types, including colorectal, breast, and pancreatic cancer. This will allow us to rigorously assess the platform's accuracy and performance against the gold standard of expert pathologist assessment, and to gather crucial feedback on its usability and how well it integrates into existing clinical workflows. Potential Applications and Benefits The successful completion of this project will unlock benefits for patients, the NHS, and the wider UK research community. For patients, the technology promises a faster, more consistent diagnostic process, reducing waiting times and enabling quicker access to the most effective, personalised treatments. For pathologists and the NHS, Octopath offers a way to manage workloads more efficiently, automate time-consuming tasks, and enhance diagnostic capabilities, ultimately leading to a more sustainable and resilient service. The robust data generated will provide the evidence required for MHRA/UKCA regulatory submission, support further trial recruitment and treatment personalization, prepare the technology for substantive follow-on funding, NHS commissioning, and potential commercialisation through a UCL spin-out.