TY - JOUR
T1 - Building digital twins of the human immune system
T2 - toward a roadmap
AU - Laubenbacher, R.
AU - Niarakis, A.
AU - Helikar, T.
AU - An, G.
AU - Shapiro, B.
AU - Malik-Sheriff, R. S.
AU - Sego, T. J.
AU - Knapp, A.
AU - Macklin, P.
AU - Glazier, J. A.
N1 - Funding Information:
Our recommendations have emerged through ongoing discussions within the IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics, supported by the Interagency Modeling and Analysis Group, an initiative by several US Federal agencies, and the Multiscale Modeling Consortium established by the US National Institutes of Health. We emphasize that the content of this article represents solely the views of the authors, not those of the Working Group or supporting government entities. R.L. was partially supported by NIH Grants Nr. 1U01EB024501-01, 1R01AI135128-01, 1R01GM127909-01, and NSF Grant Nr. CBET-1750183. G.A. is supported by NIH Grant No. UO1EB025825 and DARPA Grant No. HR00111950027. J.A.G. and T.J.S. are supported by NSF Grants Nr. 188553, 186890, and 1720625 and NIH grants Nr. U24 EB028887 and R01 GM122424. T.H. was partially supported by NIH grant 2R35GM119770-06.
Funding Information:
Our recommendations have emerged through ongoing discussions within the IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics, supported by the Interagency Modeling and Analysis Group, an initiative by several US Federal agencies, and the Multiscale Modeling Consortium established by the US National Institutes of Health. We emphasize that the content of this article represents solely the views of the authors, not those of the Working Group or supporting government entities. R.L. was partially supported by NIH Grants Nr. 1U01EB024501-01, 1R01AI135128-01, 1R01GM127909-01, and NSF Grant Nr. CBET-1750183. G.A. is supported by NIH Grant No. UO1EB025825 and DARPA Grant No. HR00111950027. J.A.G. and T.J.S. are supported by NSF Grants Nr. 188553, 186890, and 1720625 and NIH grants Nr. U24 EB028887 and R01 GM122424. T.H. was partially supported by NIH grant 2R35GM119770-06.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient’s immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.
AB - Digital twins, customized simulation models pioneered in industry, are beginning to be deployed in medicine and healthcare, with some major successes, for instance in cardiovascular diagnostics and in insulin pump control. Personalized computational models are also assisting in applications ranging from drug development to treatment optimization. More advanced medical digital twins will be essential to making precision medicine a reality. Because the immune system plays an important role in such a wide range of diseases and health conditions, from fighting pathogens to autoimmune disorders, digital twins of the immune system will have an especially high impact. However, their development presents major challenges, stemming from the inherent complexity of the immune system and the difficulty of measuring many aspects of a patient’s immune state in vivo. This perspective outlines a roadmap for meeting these challenges and building a prototype of an immune digital twin. It is structured as a four-stage process that proceeds from a specification of a concrete use case to model constructions, personalization, and continued improvement.
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U2 - 10.1038/s41746-022-00610-z
DO - 10.1038/s41746-022-00610-z
M3 - Review article
C2 - 35595830
AN - SCOPUS:85130503166
SN - 2398-6352
VL - 5
JO - npj Digital Medicine
JF - npj Digital Medicine
IS - 1
M1 - 64
ER -