105339Augmented Pathology using Artificial IntelligenceClosedCollaborative R&DInnovate UKMedical science is openly discussing a future where cancer is a chronic disease, the vision being inspired by newly developed extremely specific and effective drugs. An example is Herceptin (trastuzumab) that prevents both cancer cell proliferation and stimulates the immune response. Cancer patients treated with Herceptin without actually being HER2 positive (false positive) risk serious side effects, while the drug is ineffective. Safe and resource-optimal use of the new drugs therefore requires increased precision in the diagnostic work. Prioritization of medical expenses will not suffice to finance the increased cost of cancer with the new efficient drugs, as cancer incidence is expected to increase by 50% by 2025. To make new treatments available for the many patients benefitting from them, rationalization and automation of time-consuming, and labour-intensive, workflows is required. While that future will be a tribute to the technological development, it will require tools to effectively address the practical and economic challenges that follow. Visiopharm's image analysis in digital pathology solution is one of the tools. The solution will help society get the greatest health and economic benefits from their investments in new and upcoming, highly effective but very expensive drugs. Using image analysis Visiopharm has developed automated digital pathology for fast and accurate diagnosis of tissue samples. Trials have shown good concordance with pathologist and opportunity to reduce inconclusive cases. Overall, the solution fulfils three urgent needs in the cancer diagnosis. Increasing data and processing quality requirements as well as new cancer specific drugs have resulted in the need for standardized and more accurate quantification. The solution includes resources for standardization of workflows, and patented technology, reducing variability and accuracy. The technology replaces a time-consuming manual work process. The solution is designed to optimize the use of pathology resources, allowing for workload redistribution where the technical aspects of image analysis can be taken by technicians.