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Chromition's technology is a digital pathology platform that enables rapid diagnosis of cancer. This project will validate the technology in a clinical setting with the end point of accelerating diagnosis and transforming the way histopathology is conducted within the NHS.

Our high-throughput method enables the recognition of meaningful diagnostic patterns of multiple biomarkers in tissue sections. Specifically, tissue biopsies are stained with fluorescent biomarker conjugates, viewed with commercial multispectral microscopy imaging equipment and analysed using pattern recognition software to identify patterns. The method will give greater diagnostic insight than current methods, in less time and with lower costs.

Optical colonoscopy (OC) is the main bottleneck for bowel cancer diagnosis. Video Capsule Endoscopy (VCE) can replace many investigative OCs. It can be on par or better in medical accuracy. It can be on par or better in economics. It is superior in patient-experience. However, to fulfil all of these claims at scale, VCE has to be delivered via primary care and in a standardized, digitally enabled, and highly automated way.

We propose to create a digital health platform with automated video analysis that can scale from small scale deployments to population screening programs

More than 13,000 UK cancer patients wait too long for treatment due to a diagnostic bottleneck. Detection of metastases in stained lymph-node sections requires large amount of reading time from pathologists; the main liability of the diagnostic bottleneck.

DeepMed IO proposes the implementation of a Deep Learning system for automatic identification of metastatic regions increasing diagnostic accuracy and speed. The system will be implemented as an embeddable module in the accompanying software of Whole Slide Imaging systems as well as a mobile App enabling access to cutting-edge AI diagnostic technology and telemedicine even to remote and underdeveloped regions