Public Funding for Odin Medical Limited

Colorectal cancer (CRC) has the 4th highest incidence of all cancers in the UK and the 3rd highest worldwide. 1.4m new cases and 0.7m related deaths are reported each year. The incidence and number of deaths is estimated to rise by 60% by 2030\. The current global economic impact is estimated to be £100Bn. There are 230k people living in the UK with CRC, with 41k new incidents and 16k related deaths reported yearly. The gold standard in detection and diagnosis of CRC is colonoscopy. In a colonoscopy procedure the inner surface of the large intestine is inspected with a camera on a flexible tube, called the endoscope. The endoscopist can identify and diagnose lesions, which might require treatment. There are 2m colonoscopies conducted in the UK and 66m worldwide. It is a very common clinical procedure, however, there are a number of unmet clinical needs. The RESECT-AI project will use machine learning to support therapy in endoscopy procedures. The depth of invasion of cancer will be determined from endoscopic images to stratify patients to endoscopic resection or colorectal surgery, the residual tissue will be detected, and the risk of bleeding will be predicted post-resection. RESECT-AI will reduce cost to healthcare payers, improve patient outcomes and improve patient experience.

Colorectal cancer (CRC) is a worldwide disease. There are 1.3m new cases and 0.7m related deaths are reported each year. In the UK, CRC is the second most common cause of cancer related deaths with 41k new incidents and over 16k related deaths reported each year. 230k people are living in the UK with CRC. Colonoscopy is critical tools in the detection and diagnosis of CRC. During the procedure a doctor uses an endoscopic camera to inspect the lining of the bowel to locate, diagnose and treat polyps. However, diagnosis and resection of large complex polyps remains challenging. The B-Linc project will use machine learning to detect imaging biomarkers in endoscopy video that correspond to healthy and diseased tissue. A novel biomarker map visualization will be created to support the doctor to improve diagnosis and resection planning. B-Linc will reduce cost to healthcare payers, improve patient outcomes and improve patient experience.

Colorectal cancer (CRC) is a worldwide disease with 1.3m new cases and 0.7m related deaths reported each year and estimated global economic impact approaching £100 Billion per year. In the UK, CRC is the second most common cause of cancer related deaths, 41k new incidents and over 16k related deaths are reported each year. 230k people are living in the UK with CRC. Colonoscopy is an important tool for the identification and removal of pre-cancerous and cancerous polyps. However, even with direct inspection of the mucosa, it is highly operator dependent and studies show significant miss rate for polyps and cancers. Furthermore, when abnormal lesions are identified in vivo they are often poorly characterised/diagnosed despite the development of advanced imaging modalities. Computer Aided Detection and Diagnosis for Intelligent Endoscopy (CADDIE) will disrupt gastroenterology by using artificial intelligence to analyse colonoscopy video images in real-time. CADDIE will automatically detect and analyse cancerous and pre-cancerous polyps with the goal of better earlier detection and diagnosis of cancer leading to better patient outcomes.

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Colorectal cancer (CRC) is a worldwide disease with 1.3m new cases and 0.7m related deaths reported each year and estimated global economic impact approaching £100 Billion per year. In the UK, CRC is the second most common cause of cancer related deaths, 41k new incidents and over 16k related deaths are reported each year. 230k people are living in the UK with CRC. Colonoscopy is an important tool for the identification and removal of pre-cancerous and cancerous polyps. However, even with direct inspection of the mucosa, it is highly operator dependent and studies show significant miss rate for polyps and cancers. Furthermore, when abnormal lesions are identified in vivo they are often poorly characterised/diagnosed despite the development of advanced imaging modalities. Computer Aided Detection and Diagnosis for Intelligent Endoscopy (CADDIE) will disrupt gastroenterology by using artificial intelligence to analyse colonoscopy video images in real-time. CADDIE will automatically detect and analyse cancerous and pre-cancerous polyps with the goal of better earlier detection and diagnosis of cancer leading to better patient outcomes.