Lucida Medical awarded £2.25M SBRI Healthcare contract to scale AI innovation in prostate cancer diagnosis across the NHS
Lucida Medical has been awarded £2.25 million in funding from the Small Business Research Initiative (SBRI) Healthcare to advance the use of artificial intelligence (AI) in the diagnosis of prostate cancer in the UK National Health Service (NHS). The initiative is supported by the Accelerated Access Collaborative (AAC) and delivered in partnership with the Health Innovation Network.
The funding will support implementation of Lucida Medical’s AI technology, Prostate Intelligence (Pi), in up to 15 hospitals in partnership with the Cancer Alliances of West Yorkshire and Harrogate, South Yorkshire, Greater Manchester, East of England, and Somerset, Wiltshire, Avon and Gloucestershire.
Prostate cancer is the most common cancer in UK men. Early detection can enable successful treatment in almost all men, but currently around 50% of prostate cancers in the UK are diagnosed at a late stage, once the cancer has spread. The NHS aims to diagnose patients within 28 days of GP referral under the Faster Diagnosis Standard (FDS). However, limited radiology capacity and the complexity of interpreting MRI scans can make this challenging.
Lucida Medical’s AI solution, Pi, was designed to support radiologists by automating scan analysis, helping to speed up diagnosis and improve access to timely care. Validated using NHS data, it has demonstrated 95% sensitivity and 67% specificity for identifying clinically significant prostate cancer (csPCa). In other words, the system correctly identifies 95 out of 100 people who have the prostate cancer and correctly reassures 67 out of 100 people who don’t have it. The technology is already in clinical use in the NHS and is the only commercial AI solution of its kind to achieve expert-level performance on UK patient data.
Dr Rhidian Bramley, Clinical Lead for Diagnostics at Greater Manchester Cancer Alliance and Consultant Radiologist at The Christie NHS Foundation Trust, said: “This technology will support our radiologists across Greater Manchester to diagnose prostate cancer sooner allowing us to identify men who need treatment most urgently. It shows how the right use of AI can bring real improvements to patient care and experience.”
Initial analysis suggests that integrating Pi could save up to 21 days per patient, enabling far more to benefit from diagnosis within 28 days. This will be piloted at Leeds Teaching Hospitals NHS Trust to enable men requiring a biopsy to receive it on the same or next day following an MRI, significantly reducing wait times.
Dr Oliver Hulson, Consultant Radiologist at the Leeds Teaching Hospitals, added: “Working with Lucida Medical through this SBRI Healthcare initiative will allow us to implement a RAPID (Rapid Access to Prostate Imaging and Diagnosis) diagnostic pathway, utilising the Pi AI tool to triage patients for a biopsy much sooner than our standard practise.”
The technology may also enable more men to avoid a painful and costly biopsy and could increase the detection of early-stage cancers by 4–8%, representing up to 4,480 additional cases per year.
Associate Professor Tristan Barrett (Cambridge University Hospitals) and Professor Nikhil Vasdev (East and North Hertfordshire Teaching NHS Trust) stated: “We welcome this opportunity to use AI to improve detection and diagnosis of prostate cancer. New technology and innovation have a key role to play alongside expert clinical care, in enabling earlier diagnosis and ultimately in saving lives.”
The work will be independently evaluated by Hardian Health. Dr Hugh Harvey, Managing Director and Project Lead, commented: “The potential for earlier diagnosis, accelerated referrals and early rule-out of prostate cancer holds immense promise for a more efficient care pathway, which may lead to cost savings as well as improved outcomes.”
Dr Antony Rix, CEO and Co-founder of Lucida Medical, acknowledged the importance of working closely with clinical and research partners in the programme, stating: “With this funding, we will use Pi to improve diagnostic accuracy, reduce unnecessary biopsies, and help quickly discharge cancer-free patients, focusing resources where they’re needed most.”
This work was commissioned and funded by the NHS Cancer Programme, with the support of SBRI Healthcare and the Accelerated Access Collaborative (AAC). The views expressed in the publication are those of the author(s) and not necessarily those of the NHS Cancer Programme or its stakeholders.
