Folkert Asselbergs

Prof Dr. Folkert W. Asselbergs is Professor of Precision medicine at Institute of Health Informatics and the institute of Cardiovasculair Science, University College London, Director of the NIHR BRC UCL/UCLH Clinical and Research Informatics Unit, consultant cardiologist and Professor of Precision Medicine at University Medical Center Utrecht, University of Utrecht, the Netherlands, associate editor European Heart Journal, section digital health and innovation, Chair Center for Circulatory Health, UMC Utrecht, and chair data infrastructure Dutch Cardiovascular Alliance (www.dcvalliance.nl). 

Professor Asselbergs published more than 500 scientific papers in the field of cardiovascular disease and his work has been funded by the Netherlands Heart Foundation, Netherlands Heart Institute, British Heart Foundation, leDucq Foundation, EU FP7, European Society of Cardiology, BBMRI, National Institutes of Health, Innovative Medicines Initiative, European Research Area Network on Cardiovascular Diseases and ZonMw.

His research program in complex genetics focuses on the discovery of genes influencing susceptibility to cardiovascular disease; the application of these findings for the validation of drug targets; and the use of genetic tests for treatment targeting (stratified medicine). Lately, he widened his research focus to precision medicine using linked data sources such as wearable information and routine care data obtained from electronic health records including free text. His ambition is to build a network for performing clinical trials within routine health care linked to national registries. 

Prof Asselbergs is member of a large number of consortia and (co-) founded several consortia of which igenetrain (www.igenetrain.net), and GENIUS-CHD (www.genius-chd.org), and CAPACITY-COVID ( https://capacity-covid.eu)  are the most prominent and recent ones. He is scientific coordinator of European IMI Bigdate@heart consortium (www.bigdata-heart.eu). Bigdata@heart aims to deliver clinically relevant disease cardiovascular phenotypes, scalable insights from real-world evidence including data from registries, wearables and electronic health records, and insight driving drug development and personalized medicine through advanced big-data analytics.