Gastro-Intestinal Real-time Detection

Every year there are about 4200 new diagnoses of colorectal cancer in Norway, and about 1500 people die from this disease yearly. An important preventive step is colonoscopy examinations. In such examinations, there can be more than 30% variance between endoscopists, depending on the experience of the performing doctor. Studies show that even the best experts might overlook 20% of findings even during the best of conditions. Through many years of research at Simula Research Laboratory, we have developed artificial intelligence the helps the doctors spot polyps that would otherwise have been missed. In the GIRD project, we have developed to maturity and prepared for regulatory approval of the final device. This will raise the quality of the novice doctors to the level of the best experts when it comes to spotting polyps during examinations. The FORNY-support from the Research Council of Norway has enabled us to collect market data, perform health-economic modelling and make the technology ready for the market through the startup company Augere Medical. The project has helped us pass several important hurdles on the way to the market: 1) business development and robust plans for sales and market penetration, 2) documentation needed for regulatory approval as a medical device, 3) protection of IP and 4) clinical validation of the product. Through the FORNY project, the company is now in a phase where capital is being raised to finish the development of the regulatory approved device. At the same time, large, multicentre clinical trials are planned and the company is preparing for commercial upscaling.

Project impact: -De-risked the regulatory uncertainties and developed a regulatory strategy that allows for quick time to market while being commercially flexible. - De-risked the remaining market questions. Chaand health economic effect for the target markets. - De-risked IPR questions. Developed an IPR strategy. Submitted and got positive search results for a patent application for key technology aspects. - Collected a unique dataset that allows for an AI-system able to detect the hardest-to-detect polyps. -Prepared an in-silico trial that can be used for regulatory clinical documentation of the system. Expected impact for users of the final system: - The system will help clinicians to find more of the polyps that have a malignancy potential. This will lead to fewer cancers developed and thus, higher quality of life, longer productivity for the exposed patients and large savings in treatment costs for the hospitals.