Using Artificial Intelligence to Find New Ways of Treating Cardiometabolic Diseases
In a collaboration between Novo Nordisk A/S and University of Copenhagen, Rikke Linnemann Nielsen’s new postdoc project will use artificial intelligence as an analytical method to increase our understanding of cardiometabolic diseases and discover new targets for treatment.
Cardiometabolic diseases, including type 2 diabetes, have a genetic and thereby a hereditary component. Gaining more knowledge about the genetics will result in greater understanding of the disease and help us predict a person’s risk of developing a cardiometabolic disease, and ultimately we can use the knowledge to develop better treatment options.
Rikke Linnemann Nielsen aims to gain such knowledge in her postdoc project, in which she will use artificial intelligence to analyse big data sets. Artificial intelligence is particularly suitable for larger and more complex data sets, given that the method does not have the same limitations as more traditional analytical methods.
“Current methods in the field of genome research test associations of individual genetic variants in large cohorts. These methods are limited, because they do not take into account the complex interactions in biological systems across cells, tissues and organs or environmental factors such as lifestyle or medical treatment,” says Rikke Linnemann Nielsen, who received her PhD in Bioinformatics from the Technical University of Denmark in 2020.
Today, bigger and bigger datasets are available that require advanced analytical methods.
“Data that can explain cardiometabolic diseases can now be generated in large quantities from multiomics data, images and genetic and clinical data. These types of data can provide new insight into disease, but require integrated methods and the use of machine learning techniques to discover biomarkers in the underlying disease biology,” explains Rikke Linnemann Nielsen.
Three data sets and three sub-projects will provide new knowledge about disease development and treatment response
“The machine learning (AI) methods will be used on three different data sets that contain information on genetics, multiomics, images and clinical characteristics from following patients or human cellular models over a period of time. All three sub-projects will provide new knowledge about disease development and treatment response across different cardiometabolic diseases using advanced data-driven methods,” says Rikke Linnemann Nielsen.
Given her PhD in Bioinformatics and her experience in using machine learning to analyse similar data sets, she is the perfect person for the project.
Rikke Linnemann Nielsen will work on the project in collaboration with Ramneek Gupta, Director of Computational Biology at Novo Nordisk Research Centre Oxford, United Kingdom, Jonas Kildegaard, Director of Translational Science, Novo Nordisk A/S, and Professor Torben Hansen at the Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen.
She will also pay a research visit to the translational bioinformatics expert Marylyn Ritchie, Professor at the Department of Genetics and Director of the Center for Translational Bioinformatics at University of Pennsylvania School of Medicine, United States.
“The cross-sectional collaboration also allows me to gain insight in both academic and industrial research to inspire me for the next career steps after the postdoc,” concludes Rikke Linnemann Nielsen, who is looking forward to getting started on this ambitious project.
Rikke Linnemann Nielsen
Tel: +45 30797011
Danish Diabetes Academy
Managing Director Tore Christiansen
Tel: +45 29 64 67 64
/By Project Manager Nina Jensen, Danish Diabetes Academy