A study of the transformation of digital twins into personalized medicine

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Introduction. To date, digital twins are the most promising area for the development of modern healthcare. With their help, it is possible to radically change approaches to the diagnosis, treatment and prevention of diseases. In medicine, the concept of digital twins involves the creation of a “digital patient”, which allows you to simulate the course of the disease, predict outcomes and select optimal therapeutic treatment algorithms, taking into account the individual characteristics of the body. This transformation of the healthcare system entails revolutionary changes in established medical thinking with an emphasis on a personalized approach, which requires a revision of the basic principles of evidence-based medicine.

The purpose of the study: to conduct a systematic analysis of the current state and prospects of using digital twin technologies in personalized medicine based on a review of scientific literature for the period 2019 – 2024.

Materials and methods. The present study is a narrative review of the literature with elements of a scoping review, covering the results of research on medical digital twins over the past ~ 5 years (2019 – 2024). According to the search results, more than 150 sources were selected, of which about 60 were recognized as relevant based on reading the full texts. The final bibliography includes 23 of the most significant sources that fully meet the selection criteria. It should be noted that the choice of a narrative review with elements of a scoping review is due not to the desire for an exhaustive meta-analysis, but to a synthetic understanding of heterogeneous trends in a field where methodological limitations such as the fragmentation of empirical data and the predominance of conceptual work inevitably affect the depth of conclusions.

Results. The development of the concept of digital twins in medicine has gone through several key stages. The transition from simple to intelligent models reflects a paradigm shift in traditional medicine, where the patient is viewed as a dynamic system. Professional circles continue to form an opinion about their effective use in healthcare. Today, it is known about the successful use of digital twins in such branches of medicine as diagnostics, therapy, surgery, rehabilitation, pharmacy, prevention, as well as in systems to support clinical decision-making.

Conclusion. The conducted analysis of the MDC transformation study demonstrates their significant potential for use in personalized medicine, bringing tangible benefits in improving the accuracy of diagnosis and prognosis, individualizing treatment, ensuring continuous monitoring of patients’ health status and supporting clinical decision-making.

About the authors

Pavel V. Seliverstov

S.M. Kirov Military Medical Academy of the Russian Ministry of Defense

Author for correspondence.
Email: seliverstovpv@yandex.ru
ORCID iD: 0000-0001-5623-4226
SPIN-code: 6166-7005

Candidate of Medical Sciences, Associate Professor, 2nd Department (advanced medical therapy), Responsible for Coordinating Scientific Work at the Department

Russian Federation, Akademika Lebedeva Street, 6, Saint-Petersburg, 194044

Evgeniy V. Kryukov

S.M. Kirov Military Medical Academy of the Russian Ministry of Defense

Email: szgc@yandex.ru
ORCID iD: 0000-0002-8396-1936
SPIN-code: 3900-3441

Doctor of Medical Sciences, Professor, Academician of the Russian Academy of Sciences, Head

Russian Federation, Akademika Lebedeva Street, 6, Saint-Petersburg, 194044

Vladimir B. Grinevich

S.M. Kirov Military Medical Academy of the Russian Ministry of Defense

Email: szgc@yandex.ru
ORCID iD: 0000-0002-1095-8787
SPIN-code: 1178-0242

Professor, Head of the 2nd Department of Therapy for Advanced Training

Russian Federation, Akademika Lebedeva Street, 6, Saint-Petersburg, 194044

Evgeny V. Ivchenko

S.M. Kirov Military Medical Academy of the Russian Ministry of Defense

Email: szgc@yandex.ru
ORCID iD: 0000-0001-5582-1111
SPIN-code: 5228-1527

Doctor of Medical Sciences, Professor, Deputy Head of the Academy for Scientific Work

Russian Federation, Akademika Lebedeva Street, 6, Saint-Petersburg, 194044

Evgeny P. Minakov

Federal State Budgetary Military Educational Institution of Higher Education “A.F. Mozhaysky Military Space Academy” of the Ministry of Defense of the Russian Federation

Email: szgc@yandex.ru
SPIN-code: 4819-0765

Doctor of Technical Sciences, Professor of the Department of Management of Organizational and Technical Systems for Space Purposes

Russian Federation, Zhdanovskaya Street, 13, Saint-Petersburg, 197198

References

  1. Katsoulakis E., Wang Q., Wu H. et al. Digital twins for health: a scoping review. npj Digit Med. 2024; 7: 77. doi: 10.1038/s41746-024-01073-0
  2. Tortora M., Pacchiano F., Ferraciolli S.F. et al. Medical Digital Twin: A Review on Technical Principles and Clinical Applications. J. Clin. Med. 2025; 14 (2): 324. doi: 10.3390/jcm14020324
  3. Тайц Б.М. «10П медицина» в решении вопросов снижения смертности, увеличения продолжительности и повышения качества жизни пожилого населения. Клиническая геронтология. 2021; 27 (11–12): 76–9. https://doi.org/10.26347/1607-2499202111-12076-079 [Taitz B.M. «10P Medicine» in addressing the issues of reducing mortality, increasing life expectancy, and improving the quality of life for the elderly population. Clinical Gerontology. 2021; 27 (11–12): 76–9 (in Russian)].
  4. Glaessgen EH, Stargel DS. The digital twin paradigm for future NASA and U.S. Air Force vehicles. In: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Honolulu, HI. 2012. doi: 10.2514/6.2012-1818
  5. Селиверстов П.В., Гриневич В.Б., Крюков В.Б., Минаков Е.П. Роль цифровых двойников в терапевтическом сопровождении пациентов. Врач. 2025; 36 (6): 13–9. https://doi.org/10.29296/25877305-2025-06-03 [Seliverstov P.V., Grinevich V.B., Kryukov V.B., Minakov E.P. The Role of Digital Twins in the Therapeutic Support of Patients. Vrach. 2025; 36 (6): 13–9 (in Russian)].
  6. Viceconti M., Hunter P. The Virtual Physiological Human: Ten Years After. Annu Rev Biomed Eng. 2016; 18: 103–23. doi: 10.1146/annurev-bioeng-110915-114742
  7. Dogba M.J., Dossa A.R., Breton E., Gandonou-Migan R. Using information and communication technologies to involve patients and the public in health education in rural and remote areas: a scoping review. BMC Health Serv Res. 2019; 19 (1): 128.
  8. Карпов О.Э., Храмов А.Е. Информационные технологии, и искусственный интеллект в медицине. М.: ДПК Пресс, 2022; 480. ISBN 978-5-91976-232-4. [Karpov O.E., Khramov A.E. Information Technologies and Artificial Intelligence in Medicine. Moscow: DPK Press, 2022; 480 (in Russian)].
  9. Гриневич В.Б., Крюков В.Б., Минаков Е.П., Селиверстов П.В. Концепция применения цифровых двойников для прогнозирования значений ведущих показателей состояния здоровья пациентов. Врач. 2025; 36 (9): 83–6. https://doi.org/10.29296/25877305-2025-09-16 [Grinevich V.B., Kryukov V.B., Minakov E.P., and Seliverstov P.V. The concept of using digital twins to predict the values of leading indicators of patients’ health. Vrach. 2025; 36 (9): 83–6 (in Russian)].
  10. Селиверстов П.В., Шаповалов В.В., Кравчук Ю.А., Саликова С.П., Шаваева Ф.В., Исаева П.А., Салманова М.М., Арсланбекова Р.М. Информационные технологии на основе искусственного интеллекта в эру персонализированной оценки здоровья. Молекулярная медицина. 2025; 23 (3): 11–8. [Seliverstov P.V., Shapovalov V.V., Kravchuk Yu.A., Salikova S.P., Shavaeva F.V., Isaeva P.A., Salmanova M.M., Arslanbekova R.M. Information Technologies Based on Artificial Intelligence in the Era of Personalized Health Assessment. Molecular Medicine. 2025; 23 (3): 11–8 (in Russian)].
  11. Sun T, He X, Li Z. Digital twin in healthcare: Recent updates and challenges. Digit Health. 2023; 9: 20552076221149651. doi: 10.1177/20552076221149651
  12. Grieves M. Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary Perspectives on Complex Systems. Springer. 2017; 85–113. doi: 10.1007/978-3-319-38756-7_4
  13. Stahlberg E.A, Abdel-Rahman M., Aguilar B. et al. Exploring approaches for predictive cancer patient digital twins: opportunities for collaboration and innovation. Front Digit Health. 2022; 4: 1007784. doi: 10.3389/fdgth.2022.1007784
  14. Venkatesh K.P., Brito G., Kamel Boulos M.N. Health digital twins in life science and health care innovation. Annu Rev Pharmacol Toxicol. 2024; 64: 159–70. doi: 10.1146/annurev-pharmtox-022123-022046
  15. Минаков Е.П., Гриневич В.Б., Крюков Е.В. и др. Базы данных потенциальных цифровых двойников программно-моделирующего комплекса прогнозирования ведущих показателей состояния пациентов. Врач. 2025; 10: 28–33. doi: 10.29296/25877305-2025-10-05 [Minakov E.P., Grinevich V.B., Kryukov E.V., et al. Databases of potential digital twins of the software and modeling complex for predicting leading indicators of patients’ condition. Vrach. 2025; 10: 28–33 (in Russian)].
  16. Moingeon P., Chenel M., Rousseau C. et al. Virtual patients, digital twins and causal disease models: paving the ground for in silico clinical trials. Drug Discov Today. 2023; 28 (7): 103605. doi: 10.1016/j.drudis.2023.103605
  17. Björnsson B., Borrebaeck C., Elander N. et al. Digital twins to personalize medicine. Genome Med. 2019; 12: 4. doi: 10.1186/s13073-019-0701-3
  18. Vallée A. Digital twins for healthcare systems. Front Digit Health. 2023; 5: 1253050. doi: 10.3389/fdgth.2023.1253050
  19. Laubenbacher R., Mehrad B., Shmulevich I., Trayanova N. Digital twins in medicine. Nat Comput Sci. 2024; 4 (3): 184–91. doi: 10.1038/s43588-024-00607-6
  20. Coorey G., Figtree G.A., Fletcher D.F. et al. The health digital twin to tackle cardiovascular disease a review of an emerging interdisciplinary field. npj Digit Med. 2022; 5: 126. doi: 10.1038/s41746-022-00640-7
  21. Huang P.H., Kim K.H., Schermer M. Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study. J. Med. Internet Res. 2022; 24 (1): e33081. doi: 10.2196/33081
  22. Sahal R., Alsamhi S.H., Brown K.N. Personal Digital Twin: A Close Look into the Present and a Step towards the Future of Personalised Healthcare Industry. Sensors (Basel). 2022; 22 (15): 5918. doi: 10.3390/s22155918
  23. Machado T.M., Berssaneti F.T. Literature review of digital twin in healthcare. Heliyon. 2023; 9 (10): e19390. doi: 10.1016/j.heliyon.2023.e19390
  24. Chang H.C., Gitau A.M., Kothapalli S. et al. Understanding the need for digital twins’ data in patient advocacy and forecasting oncology. Front Artif Intell. 2023; 6: 1260361. doi: 10.3389/frai.2023.1260361
  25. De Benedictis A., Mazzocca N., Somma A. et al. Digital Twins in Healthcare: An Architectural Proposal and Its Application in a Social Distancing Case Study. IEEE J. Biomed Health Inform. 2023; 27 (10): 5143–54. doi: 10.1109/JBHI.2022.3205506
  26. Карась С.И. Виртуальные пациенты как формат симуляционного обучения в непрерывном медицинском образовании (обзор литературы). Бюллетень сибирской медицины. 2020; 19 (1): 140–9. https://doi.org:10.20538/1682-0363-2020-1-140-149 [Karas S.I. Virtual patients as a format of simulation training in continuing medical education (literature review). Bulletin of Siberian Medicine. 2020; 19 (1): 140–9 (in Russian)].
  27. В России создадут стандарт для цифровых медицинских двойников. Медвестник. 2024. URL: https://medvestnik.ru/content/news/V-Rossii-sozdadut-standart-dlya-cifrovyh-medicinskih-dvoinikov.html [V Rossii sozdadut standart dlya cifrovyh medicinskih dvoinikov. Medvestnik. 2024. URL: https://medvestnik.ru/content/news/V-Rossii-sozdadut-standart-dlya-cifrovyh-medicinskih-dvoinikov.html (in Russian)]

Supplementary files

Supplementary Files
Action
1. JATS XML

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).