100 million SEK for personalized medicine in Diabetes
“This is excellent news and a fantastic opportunity to achieve our goal of offering more effective treatments for diabetic patients. I can’t think of a better environment and partners for working towards this goal” says Professor Maria Gomez who leads the project at Lund University Diabetes Centre.
Diabetes, a disease caused largely by unhealthful lifestyles set against a backdrop of genetic predisposition, often leads to life-threatening complications that are costly to treat and impose severe suffering. Even in the most advanced health care settings, prevention and treatment of diabetes is suboptimal. There are many ways in which this urgent problem might be addressed, for example by characterizing the complex diabetes phenotype more precisely and by identifying biomarkers that predict risk factor susceptibility, treatment response, and rate and extent of diabetes progression. Here we outline a carefully integrated, interdisciplinary programme of research that seeks to address these objectives through the discovery, validation, integration and translation of prognostic, predictive and safety biomarkers related to diabetes. We will begin by elucidating a novel reclassification of diabetes by integrating several extremely well characterized cohorts comprised of diverse tissue collections and prospective epidemiological studies, and thereafter mining predictive networks comprised of multi-omic biomarkers for diabetes phenotypes. The candidate biomarkers that emerge and withstand independent replication will be carried forwards for functional validation using in vivo and in vitro models; the most proposing biomarkers will be clinically validated using innovative clinical trials.
Partnering companies are: Region Skåne, Follicum AB, Pfizer, Johnson & Johnson Innovation and Novo Nordisk.
There is no panacea, but characterizing the complex diabetes phenotype more precisely and identifying biomarkers that predict risk factor susceptibility, treatment response, and rate and extent of diabetes progression are promising strategies. Lund University Diabetes Centre, LUDC, has outlined a plan to build a "truly collaborative research ecosystem” by partnering with industry:
“We propose a carefully integrated, interdisciplinary research program to address these challenges through discovery, validation, integration and translation of prognostic, predictive and safety biomarkers. We will begin by elucidating a novel diabetes reclassification by integrating several outstanding cohorts comprised of diverse tissue collections and prospective epidemiological studies, and thereafter mine predictive networks comprised of multi-omic biomarkers. The strongest biomarker candidates will be functionally annotated using in vivo and in vitro models, with the top-ranking variants being carried forwards for clinical validation in innovative randomized trials.”