10085538AI Digital Diagnostics Platform to Streamline the Diagnosis of Blood CancersClosedCollaborative R&DInnovate UKThis project aims to address an unmet need in the diagnosis of blood cancers (e.g. lymphoma, myeloma, leukemia). It focuses on the development of Spotlight Pathology's novel AI diagnostic tools tailored specifically towards identifying subtle yet crucial differences in cell counts which indicate cancer. It utilises state-of-the-art image analysis and machine learning methods to detect and classify sub-populations of cells in biopsies scanned using widely available high-throughput slide scanners. Training the AI will be both low-impact and low-cost and it will operate on existing digital pathology platforms, integrating seamlessly into existing clinical pathways. Significant advances will be made on the current state-of-the-art, allowing for the earlier detection of blood cancer cases and the stratification of patients to appropriate treatments, ultimately improving clinical outcomes, reducing misdiagnoses (~25% of all cases) and the alleviation of workload on a depleting and over-stretched workforce. The AI tools will be trained in collaboration with Leeds Teaching Hospital Trust using a large set of 2000 digital biopsies for AI training to match clinical diagnosis accuracy and generate the pre-clinical evidence necessary to begin regulatory approval, build partnerships and engage early adopters. Additionally, a health economics assessment will be conducted to conveying the value proposition to future customers. These project outputs will improve the competitiveness and productivity of Spotlight Pathology. Adoption of the solution in blood cancer diagnosis, driven by demand for improved diagnostic accuracy and a large push for digitisation in healthcare, creates significant value across healthcare systems globally, including: * Initial referrals increase to 82% accuracy equivalent to expert haematopathologist, from the 40% accuracy of a general pathologist * Increasing the rate and accuracy of blood cancer diagnosis, increasing clinical capacity and easing workload of over-stretched services. * Increases levels of diagnosis standardisation across geographical regions. * Reducing the referral of non-malignant cases, saving costs of £1.2m in the UK per year.