Digital Twins: From Personalised Medicine to Precision Public Health
Open accessAbstract
A digital twin is a virtual model of a physical entity, with dynamic, bi-directional links between the physical entity and its corresponding twin in the digital domain. Digital twins are increasingly used today in different industry sectors. Applied to medicine and public health, digital twin technology can drive a much-needed radical transformation of traditional electronic health/medical records (focusing on individuals) and their aggregates (covering populations) to make them ready for a new era of precision (and accuracy) medicine and public health. Digital twins enable learning and discovering new knowledge, new hypothesis generation and testing, and in silico experiments and comparisons. They are poised to play a key role in formulating highly personalised treatments and interventions in the future. This paper provides an overview of the technology’s history and main concepts. A number of application examples of digital twins for personalised medicine, public health, and smart healthy cities are presented, followed by a brief discussion of the key technical and other challenges involved in such applications, including ethical issues that arise when digital twins are applied to model humans.
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In healthcare, digital twins are a promising tool for drug target discovery.
“In healthcare, digital twins are a promising tool for drug target discovery 65,66 .”
From Multimodal biomedical AI (2022) · cites this paper as [66]
Section 3, “Digital Twins in Personalised Medicine” (page not provided), says digital twins are being explored for drug discovery and development. It does not specifically discuss discovering drug targets, so the claim is more specific than the source supports. (LLM, conf=0.86)
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- Authors
- Kamel Boulos, M. N., & Zhang, P.
- Affiliations
- Information Management School, Sun Yat-sen University, Guangzhou 510006, China
- Vanderbilt University (US)
- Venue
- Journal of Personalized Medicine
- Publisher
- MDPI AG
- Published
- 2021-07-29
- Volume
- 11
- Issue
- 8
- Pages
- 745
- ISSN
- 2075-4426 (ISSN-L)
- PMC
- PMC8401029
- OpenAlex
- W3184569878
- Cited by
- 530
- References
- 31
- Citations by year
- 2026: 95 · 2025: 156 · 2024: 123 · 2023: 99 · 2022: 52 · 2021: 4
- FWCI
- 5.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Personalized Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Keywords
- digital twin, personalized medicine, precision public health, electronic health records, in silico analysis, ethical considerations, virtual human model
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