Using digital twins in viral infection
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Personalized computer simulations of infection could allow more effective treatments
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A main challenge for viral-infection digital twins is that many biological phenomena, such as infections within the body, the immune response to viral pathogens, and some treatments, are poorly understood.
“Among the main challenges for this type of DT is the fact that many biological phenomena are poorly understood, such as infections within the body and the immune response to viral pathogens, as well as some treatments.”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [53]
In “Using digital twins in viral infection,” the paper identifies limited understanding of infection spreading within the body and immune responses as challenges for digital twins. It describes therapies as complex, but does not say that treatments themselves are poorly understood. (LLM, conf=0.83)
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Barresi, G., Gaggioli, A., Sternini, F., Ravizza, A., Pacchierotti, C., & Michieli, L. D. (2023) · Studies in big data · doi:10.1007/978-981-99-3989-3_4 · Cited by 11 · see citing works
Digital twins of nonlinear dynamical systems: a perspective
Lai, Y. (2023) · The European Physical Journal Special Topics · doi:10.1140/epjs/s11734-023-00996-1 · Cited by 11 · see citing works
Concept and framework of digital twin human geographical environment
Xu, B., Xiao, X. P., Wang, Y. P., Kang, Y., Chen, Y., Wang, P., & Lin, H. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.123866 · Cited by 10 · see citing works
Kulkarni, S., Lin, B., & Radhakrishnan, R. (2025) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2025.109081 · Cited by 10 · see citing works
Digital twins for cardiovascular diseases: towards personalised and sustainable care
Vallée, A. (2025) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2025.2569027 · Cited by 11 · see citing works
Engineering and public health: converging disciplines for resilient solutions
Cummings, C. L., Wells, E., & Trump, B. D. (2024) · Environment Systems & Decisions · doi:10.1007/s10669-024-09981-y · Cited by 10 · see citing works
Sandrone, S. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.0932-24.2024 · Cited by 10 · see citing works
Digital Twins in Urological Oncology: Precise Treatment Planning via Complex Modeling
Checcucci, E., Oing, C., Amparore, D., Porpiglia, F., & Rescigno, P. (2024) · European Urology Oncology · doi:10.1016/j.euo.2024.10.005 · Cited by 10 · see citing works
Applications of pharmacometrics in drug development
Xiong, Y., Samtani, M. N., & Ouellet, D. (2024) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2024.115503 · Cited by 9 · see citing works
Digital Twins of the Soil Microbiome for Climate Mitigation
Mukhtar, H., Wunderlich, R. F., & Lin, Y. (2022) · Environments · doi:10.3390/environments9030034 · Cited by 9 · see citing works
Unveiling the potential of Digital Twin technology for Higher Education
Addanki, K., & Corrin, L. (2023) · ASCILITE Publications · doi:10.14742/apubs.2023.635 · Cited by 8 · see citing works
Chen, Y., Yang, M., & Hua, Q. (2025) · Pharmacological Research · doi:10.1016/j.phrs.2025.107734 · Cited by 8 · see citing works
Visioli, G., Romaniello, A., Spinoglio, L., Albanese, G. M., Iannetti, L., Gagliardi, O. M., Lambìase, A., & Gharbiya, M. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252011074 · Cited by 8 · see citing works
Predictive Radiation Oncology – A New NCI–DOE Scientific Space and Community
Buchsbaum, J. C., Jaffray, D. A., Ba, D. E., Borkon, L. L., Chalk, C., Chung, C. D., Coleman, M. A., Coleman, C. N., Diehn, M., Droegemeier, K. K., et al. (2022) · Radiation Research · doi:10.1667/rade-22-00012.1 · Cited by 8 · see citing works
Digital Twins for Organ Preservation Devices
Buhagiar, A. J., Freitas, L., Scott, W. E., III, & Larsen, P. G. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19762-8_3 · Cited by 7 · see citing works
A Digital Twin Generic Architecture for Data-Driven Cyber-Physical Production Systems
Iliuţă, M.-E., Pop, E., Caramihai, S. I., & Moisescu, M. A. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-24291-5_6 · Cited by 8 · see citing works
Inaugural Editorial - Digital Twin
Tao, F., Qi, Q., & Liu, A. (2021) · Digital Twin · doi:10.12688/digitaltwin.17471.1 · Cited by 7 · see citing works
Cockrell, C., Schobel, S., Lisboa, F., Yoram Vodovotz, B., & An, G. C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.22.517524 · Cited by 9 · see citing works
AI-driven aging digital twins: A roadmap for clinical translation in precision geriatrics
Li, C., Zuo, K., Duan, R., Ouyang, X., Zhang, L. Y., Zeng, L., & Ge, L. (2025) · Ageing Research Reviews · doi:10.1016/j.arr.2025.102931 · Cited by 6 · see citing works
Digital Twins and Health Care: an Umbrella Review
Afshar, M., Moradkhani, A., Soheili, M., Tavakkol, M., Moradi, Y., & Kohan, H. G. (2025) · Journal of Medical Systems · doi:10.1007/s10916-025-02322-9 · Cited by 6 · see citing works
- Authors
- Laubenbacher, R., Sluka, J. P., & Glazier, J. A.
- Affiliations
- University of Florida (US)
- Indiana University Bloomington (US)
- Venue
- Science
- Published
- 2021-03-12
- Volume
- 371
- Issue
- 6534
- Pages
- 1105-1106
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC8170388
- OpenAlex
- W3135755054
- Cited by
- 169
- References
- 14
- Citations by year
- 2026: 25 · 2025: 38 · 2024: 32 · 2023: 30 · 2022: 37 · 2021: 7
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM122424, R01GM127909)
- National Institute of Allergy and Infectious Diseases (R01AI135128)
- National Institute of Biomedical Imaging and Bioengineering (U01EB024501, U24EB028887)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- digital twin, viral infection, personalized medicine, treatment optimization
- MeSH terms
- Artificial Intelligence, Computer Simulation, Humans, Models, Biological, Software, Virus Diseases, Precision Medicine, Patient-Specific Modeling
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