Digital twins to personalize medicine
Review article, 2020
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
University of Gothenburg
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Eun Jung Lee
Linköping University
Yonsei 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
Sahlgrenska University Hospital
Region Jönköpings län
X. F. Sun
Linköping University
Oleg Sysoev
Linköping University
Huan Zhang
Linköping University
Mikael Benson
Linköping University
Linköping University Hospital
Genome Medicine
1756994x (eISSN)
Vol. 12 1 4Subject Categories
Other Computer and Information Science
Pharmaceutical Sciences
Information Science
DOI
10.1186/s13073-019-0701-3
PubMed
31892363