Digital twins to personalize medicine
Journal article, 2019

Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient.

Author

Bergthor Bjornsson

Linköping University

Carl Borrebaeck

Lund University

Nils Elander

Linköping University

Thomas Gasslander

Linköping University

Danuta R. Gawel

Linköping University

Mika Gustafsson

Linköping University

Rebecka Jörnsten

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Eun Jung Lee

Yonsei University

Linköping University

Xinxiu Li

Linköping University

Sandra Lilja

Linköping University

David Martinez-Enguita

Linköping University

Andreas Matussek

Karolinska University Hospital

Region Jönköpings län

Per Sandstrom

Linköping University

Samuel Schafer

Linköping University

Margaretha Stenmarker

Region Jönköpings län

Sahlgrenska University Hospital

X. F. Sun

Linköping University

Oleg Sysoev

Linköping University

Huan Zhang

Linköping University

Mikael Benson

Linköping University

Linköping University Hospital

Genome Medicine

1756-994X (ISSN)

Vol. 12 1 4

Subject Categories

Other Computer and Information Science

Pharmaceutical Sciences

Information Science

DOI

10.1186/s13073-019-0701-3

PubMed

31892363

More information

Latest update

8/13/2020