Digital twins to personalize medicine.

Bergthor BjörnssonCarl BorrebaeckNils ElanderThomas GasslanderDanuta R GawelMika GustafssonRebecka JörnstenEun Jung LeeXinxiu LiSandra LiljaDavid Martínez-EnguitaAndreas MatussekPer SandströmSamuel SchäferMargaretha StenmarkerX F SunOleg SysoevHuan ZhangMikael Bensonnull null

Published in: Genome medicine (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.

Keyphrases

high resolution
end stage renal disease
newly diagnosed
chronic kidney disease
ejection fraction
prognostic factors
case report
mass spectrometry
electronic health record
gestational age
big data
preterm birth