UCPH to train IT and health specialists of the future in a comprehensive pan-European research project

RAINBOW is a major European initiative aimed at educating a bunch of new healthcare professionals who understand both medical issues and have insights into the latest IT-based diagnostic tools. RAINBOW will also help develop new clinical methods that can make everyday life easier for health professionals. The doctor will be able to draw on a comprehensive platform of analytic and diagnostic tools and provide here-and-now answers to questions in close dialogue with the patient.

An impressive array of research-driven companies and universities in Europe are partners in the RAINBOW project, which has received public funding of 4 m Euro (equivalent to 30 m DKK) from the EU Horizon 2020 - Marie Skłodowska-Curie program supporting innovative education networks.

"The project proposal for RAINBOW has been formulated after long-term inquries and dicussions among researchers and clinicians at university hospitals as well as with manufacturers of clinical equipment across Europe," says Associate Professor Kenny Erleben, who is the project manager and focal point for the entire project.

"What is the future need for new expertise in diagnostics? Which disorders can especially benefit from using the latest big data methods? Where are the flaws in the communication between the technical IT experts who are to develop the tools and the doctors who will use them in practice?"

It is problems like these that the RAINBOW project will now address by bringing together the various experts - doctors, IT experts and data analysts, equipment manufacturers and educators - in a major network organization that will join forces and efforts through the next four years.

Kenny Erleben is a computer scientist and has for many years done research in numerical and visual modeling of human anatomy. Kenny is in charge of the Numerical Optimization and Simulation Lab at the Department of Computer Science at the University of Copenhagen, where he and his colleagues use computer simulation to model almost everything from the smallest internal organ seen through a microscope to the entire human skeleton or physiognomy.

During the next four years, Kenny, together with research colleagues Sune Darkner and Åsa Feragen, will be the focal point for RAINBOW's many participants and activities involving the recruitment and training of 15 new PhD students from a number of European countries. Copenhagen will be the organizational center for these activities. All project participants, including notably the 15 new PhD students, will have some travel activity when participating in workshops, courses, career labs and receiving guidance from different experts in different countries.

What are the project objectives?

In addition to educating future specialists who must have insight into medical science and be able to apply advanced computer-controlled technology, the project will provide cutting-edge and best of the best methods in providing disease forecasts, diagnosis, quick follow-up to the patient and individually designed treatment methods that take into account the patient's specific anatomy.

The project will involve cases and practical as well as clinical trials in order to improve methods for early diagnosis of diseases through scanning images and treatment of diseases and disorders. Examples of diseases are intestinal cancer, sclerosis, dental surgery and design, artificial hearts and obesity, as well as studies of brainwave dissemination in the brain tissue, use of eye surgery simulators (eg cataracts) and last but not least surgery that takes place through image-guided programs while the surgery is in progress. It can be anything from intestinal surgery to eye surgery.

Kenny says: "In future treatment systems, technical solutions that allow for a here and now response to diagnosis will increasingly serve as a support to the medical staff's personal assessment and efforts. But the computer-aided techniques will never replace the direct patient contact. The project and the new treatment methods that will result from it are primarily aimed at increasing the patient's quality of life. Decisions on individual treatment and approaches  will be taken in close dialogue between the patient and the doctor and not based on a general approach."

Patient-specific modeling represents the latest approach in computer-supported treatment methods – however, sufficiently large data sets are required

Creating an individual model of patient through, for example, a mobile scanner is well known and becoming practice at dental clinics, where you cannot use a one-size-fits-all approach. Here, prostheses or crowns should fit the person down to the smallest small unit. Modeling has also been known for some time in dealing with other physical diseases and disorders, but the use is not widespread yet.

The way in which data is registered and aggregated in the clinical environments is an important factor in computer-aided diagnostics. Only when an adequate amount of data and representativeness can be obtained will it possible to perform data-based modeling in a larger context - popularly called the Big Data method. Here, the RAINBOW partner companies can indeed contribute to creating new methods for solving multidisciplinary issues. As part of the bridge building, the 15 PhD students will travel to study both at universities and with the companies to strengthen their technical skills and insight and receive practical training in research and innovation.

Two supervisors and one industrial counsellor per student

One groundbreaking premise of the project is that each student is linked with an academic as well an industrial supervisor AND with a counellor with an industrial company. This provides a whole new type of business PhD curriculum, where there is a close interaction between the academic communities and a the company that manufactures clinical equipment.

The broad interdisciplinary academic network of the project, which will meet and share experiences along the way, is another precondition for strengthening the PhD students' knowledge and possibilities of testing hypotheses by researchers and producers.