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. 2019 Dec 31;12(1):4.
doi: 10.1186/s13073-019-0701-3.

Digital twins to personalize medicine

Bergthor Björnsson  1 , Carl Borrebaeck  2 , Nils Elander  3 , Thomas Gasslander  1 , Danuta R Gawel  4 , Mika Gustafsson  5 , Rebecka Jörnsten  6 , Eun Jung Lee  4   7 , Xinxiu Li  4 , Sandra Lilja  4 , David Martínez-Enguita  5 , Andreas Matussek  8   9 , Per Sandström  1 , Samuel Schäfer  4 , Margaretha Stenmarker  10   11 , X F Sun  3 , Oleg Sysoev  12 , Huan Zhang  4 , Mikael Benson  13   14   15 ; Swedish Digital Twin Consortium
Affiliations

Digital twins to personalize medicine

Bergthor Björnsson et al. Genome Med. .

Abstract

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.

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Conflict of interest statement

The authors are members of the SDTC, and MB is associated with DigiTwin (https://www.digitwins.org).

Figures

Fig. 1
Fig. 1
The digital twin concept for personalized medicine. a An individual patient has a local sign of disease (red). b A digital twin of this patient is constructed in unlimited copies, based on computational network models of thousands of disease-relevant variables. c Each twin is computationally treated with one or more of the thousands of drugs. This results in digital cure of one patient (green). d The drug that has the best effect on the digital twin is selected for treatment of the patient
See this image and copyright information in PMC

References

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