IVA's ‘100 list’ was launched in conjunction with its 100th anniversary in 2019. The selection committee consists of over 60 qualified individuals from academia, business, and the public sector.
This year, the Academy highlights a variety of research projects from Swedish universities, under the theme ‘Technology in the service of humanity - innovation through interdisciplinary science’. In total, 103 projects from 22 different universities and research institutes in Sweden were selected. Lund University had the third-highest number of projects after KTH Royal Institute of Technology and Chalmers University of Technology.
“This demonstrates our continued ability to conduct research with great potential for utilisation. We are incredibly proud of Lund's extensive research capacity and our ability to transform it into concrete societal benefits and commercial opportunities,” says Niclas Nilsson, Director of Innovation at Lund University's innovation office.
The selected Lund University projects cover a wide range of challenges, from availability of semiconductors and improved stroke diagnostics to better forensic analysis in police work.
For example, Hanna Isaksson and her colleagues have developed a new method to calculate bone strength and fracture risk by combining 2D diagnostics with 3D reconstruction of hips. The goal of the project is to implement the technology clinically for early risk identification. Sweden currently has the world's highest frequency of osteoporosis-related hip fractures, costing more than 2 billion annually and leading to a tripled risk of mortality.
Another project is led by Sang Hyun Pyo, who has developed bio-based surfactants from birch bark which is used, for example, in cleaning products and cosmetics. Birch bark is a natural resource and by-product of the Swedish pulp and forest industry.
Emma Hammarlund leads a research team, which includes members from Chalmers and Johns Hopkins University, which has developed a prototype for early cancer diagnosis through hair strand analysis. The technique combines geological methods used to trace long-ago event in Earth's history with machine learning. Cancer cells' higher metabolism means that different elements are metabolised faster than in other cells. According to Emma Hammarlund's hypothesis, this will be visible as chemical imprints in the hair strands.
"A cancer detected early reduces mortality and suffering – and saves society a lot of money," says Emma Hammarlund.