Digital twins to personalize medicine

Digital twins to personalize medicine

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...

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Main Authors: Bergthor Björnsson, Carl Borrebaeck, Nils Elander, Thomas Gasslander, Danuta R. Gawel, Mika Gustafsson, Rebecka Jörnsten, Eun Jung Lee, Xinxiu Li, Sandra Lilja, David Martínez-Enguita, Andreas Matussek, Per Sandström, Samuel Schäfer, Margaretha Stenmarker, X. F. Sun, Oleg Sysoev, Huan Zhang, Mikael Benson, on behalf of the Swedish Digital Twin Consortium
Format: Article
Language:English
Published: BMC 2019-12-01
Series:Genome Medicine
Online Access:https://doi.org/10.1186/s13073-019-0701-3
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spelling doaj-813cc408ddb94ef6ad9e11849ee4ab052021-01-03T12:05:22ZengBMCGenome Medicine1756-994X2019-12-011211410.1186/s13073-019-0701-3Digital twins to personalize medicineBergthor Björnsson0Carl Borrebaeck1Nils Elander2Thomas Gasslander3Danuta R. Gawel4Mika Gustafsson5Rebecka Jörnsten6Eun Jung Lee7Xinxiu Li8Sandra Lilja9David Martínez-Enguita10Andreas Matussek11Per Sandström12Samuel Schäfer13Margaretha Stenmarker14X. F. Sun15Oleg Sysoev16Huan Zhang17Mikael Benson18on behalf of the Swedish Digital Twin ConsortiumDepartment of Surgery and Clinical and Experimental Medicine, Linköping UniversityDepartment of Immunotechnology, Lund UniversityDepartments of Oncology, and Clinical and Experimental Medicine, Linköping UniversityDepartment of Surgery and Clinical and Experimental Medicine, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityBioinformatics, Department of Physics, Chemistry and Biology, Linköping UniversityMathematical Sciences, University of Gothenburg and Chalmers University of TechnologyCentre for Personalized Medicine, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityBioinformatics, Department of Physics, Chemistry and Biology, Linköping UniversityDivision of Clinical Microbiology, Department of Laboratory Medicine, Karolinska Institutet, Karolinska University HospitalDepartment of Surgery and Clinical and Experimental Medicine, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityFuturum–Academy for Health and Care, Department of Pediatrics, Region Jönköping CountyDepartments of Oncology, and Clinical and Experimental Medicine, Linköping UniversityDivision of Statistics and Machine Learning, Department of Computer and Information Science, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityCentre for Personalized Medicine, Linköping UniversityAbstract 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.https://doi.org/10.1186/s13073-019-0701-3
collection DOAJ
language English
format Article
sources DOAJ
author Bergthor Björnsson
Carl Borrebaeck
Nils Elander
Thomas Gasslander
Danuta R. Gawel
Mika Gustafsson
Rebecka Jörnsten
Eun Jung Lee
Xinxiu Li
Sandra Lilja
David Martínez-Enguita
Andreas Matussek
Per Sandström
Samuel Schäfer
Margaretha Stenmarker
X. F. Sun
Oleg Sysoev
Huan Zhang
Mikael Benson
on behalf of the Swedish Digital Twin Consortium
spellingShingle Bergthor Björnsson
Carl Borrebaeck
Nils Elander
Thomas Gasslander
Danuta R. Gawel
Mika Gustafsson
Rebecka Jörnsten
Eun Jung Lee
Xinxiu Li
Sandra Lilja
David Martínez-Enguita
Andreas Matussek
Per Sandström
Samuel Schäfer
Margaretha Stenmarker
X. F. Sun
Oleg Sysoev
Huan Zhang
Mikael Benson
on behalf of the Swedish Digital Twin Consortium
Digital twins to personalize medicine
Genome Medicine
author_facet Bergthor Björnsson
Carl Borrebaeck
Nils Elander
Thomas Gasslander
Danuta R. Gawel
Mika Gustafsson
Rebecka Jörnsten
Eun Jung Lee
Xinxiu Li
Sandra Lilja
David Martínez-Enguita
Andreas Matussek
Per Sandström
Samuel Schäfer
Margaretha Stenmarker
X. F. Sun
Oleg Sysoev
Huan Zhang
Mikael Benson
on behalf of the Swedish Digital Twin Consortium
author_sort Bergthor Björnsson
title Digital twins to personalize medicine
title_short Digital twins to personalize medicine
title_full Digital twins to personalize medicine
title_fullStr Digital twins to personalize medicine
title_full_unstemmed Digital twins to personalize medicine
title_sort digital twins to personalize medicine
publisher BMC
series Genome Medicine
issn 1756-994X
publishDate 2019-12-01
description 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.
url https://doi.org/10.1186/s13073-019-0701-3
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