Professor Folkert Asselbergs
Professor of Precision Medicine, Consultant Cardiologist, Director BRC Clinical Research Informatics Unit at University College London (UCL)
Professor Folkert W. Asselbergs is a Professor in cardiovascular genetics and consultant cardiologist at the department of Cardiology, University Medical Center Utrecht; Professor of Precision medicine at the Institute of Cardiovascular Science and Institute of Health Informatics, University College London; Director BRC Clinical Research Informatics Unit, University College London Hospital; Manager Research Center for Circulatory Health, UMC Utrecht; and chair data infrastructure Dutch Cardiovascular Alliance (www.dcvalliane.nl).
Folkert has published more than 300 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.
Folkert’s 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.
Folkert is a member of a large number of consortia and has (co-) founded several consortia of which igenetrain (www.igenetrain.net), and GENIUS-CHD (www.genius-chd.org) are the most prominent ones. He is scientific coordinator of European IMI Bigdata@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 insights driving drug development and personalized medicine through advanced big-data analytics.