Tech Transfer and Societal Impact
All three of our Grand Challenge research areas have a common ultimate focus on research that delivers improvements to the quality, safety, and efficiency of healthcare. This takes many different forms, with major target areas including: the delivery of individual patient diagnostics and therapeutic recommendations in cancer; delivery of medical imaging and AI-based pathology both locally, and through mobile microscopy and cloud computing, globally; the delivery of accurate genomic diagnostics in rare disease; and the delivery of the public health promises of genomic prediction.
Stakeholders range from our direct clinical colleagues and patients in Helsinki, to the government and population at large, and in some cases to global impact in public health. Each of the three major research areas are directly focused on public health impact, so we consider societal impact a direct goal, rather than indirect benefit, of all FIMM research. With continued success, FIMM research output will: help cancer patients receive more effective drugs and combinations of drugs; provide new tools for digital pathology that can be used locally and globally in the developing world; develop and deliver through the Finnish healthcare system diagnostics and predictors of disease outcome and therapeutic response based on individual genome and health history; and introduce public health recommendations driven from epidemiologic registry and genomic insights.
‘New business from research ideas’ projects funded by Business Finland
FIMM researchers led by Dr. Johan Lundin have developed a small, low-cost mobile microscope device that can attain laboratory-level microscopic definition. The project has received significant funding to support further development of the device and the remote diagnostics process. Clinical studies on the use of mobile microscopy for point-of-care diagnostics were started in 2016 in collaboration with Helsinki Innovation Services and the Karolinska Institutet. The device is being tested both in field conditions in Tanzania and Kenya, as well as in some Finnish hospitals. Combined with the remarkable progress of automated, AI-based pathology image analysis, delivery of these hand-held devices, which connect to cloud computing through mobile phones, will make it possible to deploy cutting-edge real-time diagnostics in infectious disease and cancer in remote and under-resourced areas where even stable power, let alone advanced microscopy, is not currently available. This could have obvious and very significant global health impact.
Current heart disease prediction methods based on environmental and life-style factors are insufficient, failing to detect over half the highrisk individuals. KardioKompassi® was developed by researchers at FIMM, led by doctors Ripatti and Widen, to meet the need for better and more accurate prediction tools. This next-generation web tool enables patients and doctors to use genomic data to predict and prevent cardiovascular disease. It uniquely combines traditional medical approaches with multiple recently discovered genetic risk factors. KardioKompassi is currently being used in the Finnish population-based GeneRISK-study, which has recruited 7,350 participants. Not only has the study developed improved predictors that identify individuals at high-risk who can be better treated in advance of cardiac events, this study has returned prediction information and has already assessed that returning this new information, provided from a combination of genetic and lifestyle factors, in an easy to interpret fashion has led to individuals then working themselves to improve their risk profiles through weight-loss and smoking cessation.
The VEIL.AI service enables potentially sensitive individual-level information to be used in various research and development projects as well as commercial applications. VEIL.AI processes information without affecting the value of collected data sets, but ensuring that individuals can no longer be identified. The application thus enables the information to be utilised for new purposes and by new users.
In addition to the above-mentioned concepts, FIMM researchers have recently received funding for two other commercialising projects.
Some of the novel digital microscopy technologies developed at FIMM have been transferred to a spinoff company Fimmic Oy (AIforia). The company, founded in 2013, commercialises information management systems for digital microscopy. Fimmic’s WebMicroscope® Platform has thousands of end-users and it is used in several different applications, such as cancer research, drug development and medical education. Fimmic’s next generation WebMicroscope with Deep Learning Analytics brings fast and accurate diagnostics support to medical microscopy, replacing the previous slow, manual and inconsistent workflow. The company was recently listed among the hottest startups in Finland.