Derleme
BibTex RIS Kaynak Göster
Yıl 2025, EARLY ONLINE, 1 - 8
https://doi.org/10.18621/eurj.1661091

Öz

Kaynakça

  • 1. Yuan B. What Personalized Medicine Humans Need and Way to It --also on the Practical Significance and Scientific Limitations of Precision Medicine. Pharmgenomics Pers Med. 2022;15:927-942. doi: 10.2147/PGPM.S380767.
  • 2. Mishra V, Chanda P, Tambuwala MM, Suttee A. Personalized medicine: An overview. Int J Pharm Qual Assur. 2019;10(2):290-294. doi: 10.25258/ijpqa.10.2.13
  • 3. Pritchard DE, Moeckel F, Villa MS, Housman LT, McCarty CA, McLeod HL. Strategies for integrating personalized medicine into healthcare practice. Per Med. 2017 ;14(2):141-152. doi: 10.2217/pme-2016-0064.
  • 4. Ginsburg GS, Willard HF. Genomic and personalized medicine: foundations and applications. Transl Res. 2009;154(6):277-287. doi: 10.1016/j.trsl.2009.09.005.
  • 5. Calcaterra V, Pagani V, Zuccotti G. Digital Twin: A Future Health Challenge in Prevention, Early Diagnosis and Personalisation of Medical Care in Paediatrics. Int J Environ Res Public Health. 2023;20(3):2181. doi: 10.3390/ijerph20032181.
  • 6. Geissler F, Heiß R, Kopp M, et al. Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. Rofo. 2021;193(4):437-445. doi: 10.1055/a-1253-8558.
  • 7. Shamanna P, Dharmalingam M, Sahay R, et al. Retrospective study of glycemic variability, BMI, and blood pressure in diabetes patients in the Digital Twin Precision Treatment Program. Sci Rep. 2021;11(1):14892. doi: 10.1038/s41598-021-94339-6.
  • 8. de Sio FS, Faber NS, Savulescu J, Vincent NA. Why less praise for enhanced performance? Moving beyond responsibility-shifting, authenticity, and cheating toward a natu re-of-activities approach. In: Jotterand F, Dubljevic V, editors. Cognitive Enhancement: Ethical and Policy Implications in International Perspectives. New York: Oxford Academic. 2016. pp. 27-41.
  • 9. Francis F. Our Posthuman Future: Consequences of the Biotechnology Revolution. Profile Books; 2003.
  • 10. Chu Y, Li S, Tang J, Wu H. The potential of the Medical Digital Twin in diabetes management: a review. Front Med (Lausanne). 2023;10:1178912. doi: 10.3389/fmed.2023.1178912.
  • 11. Hernandez-Boussard T, Macklin P, Greenspan EJ, et al. Digital twins for predictive oncology will be a paradigm shift for precision cancer care. Nat Med. 2021;27(12):2065-2066. doi: 10.1038/s41591-021-01558-5.
  • 12. Spitzer M, Dattner I, Zilcha-Mano S. Digital twins and the future of precision mental health. Front Psychiatry. 2023;14:1082598. doi: 10.3389/fpsyt.2023.1082598.
  • 13. Misra SC, Bisui S, Singh A. A study on the role of trust factor in adopting personalized medicine. Behav Inf Technol. 2020;39(7):771-787. doi:10.1080/0144929X.2019.1614225.
  • 14. Glaessgen EH, Stargel DS. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles. In: Paper for the 53rd Structures, Structural Dynamics, and Materials Conference: Special Session on the Digital Twin. American Institute of Aeronautics and Astronautics; 2012.
  • 15. Liu Y, Zhang L, Yang Y, et al. A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin. IEEE Access. 2019;7:49088-490101. doi:10.1109/ACCESS.2019.2909828.
  • 16. Currie GM, Rohren EM. Radiation Dosimetry, Artificial Intelligence and Digital Twins:Old Dog, New Tricks. Semin Nucl Med. 2023;53(3):457-466. doi: 10.1053/j.semnuclmed.2022.10.007.
  • 17. Bruynseels K, Santoni de Sio F, van den Hoven J. Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm. Front Genet. 2018;9:31. doi: 10.3389/fgene.2018.00031.
  • 18. Alber M, Buganza Tepole A, Cannon WR, et al. Integrating machine learning and multiscale modeling-perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. NPJ Digit Med. 2019;2:115. doi: 10.1038/s41746-019-0193-y.
  • 19. Iqbal JD, Krauthammer M, Biller-Andorno N. The Use and Ethics of Digital Twins in Medicine. J Law Med Ethics. 2022;50(3):583-596. doi: 10.1017/jme.2022.97. PMID: 36398633.
  • 20. Corral-Acero J, Margara F, Marciniak M, et al. The 'Digital Twin' to enable the vision of precision cardiology. Eur Heart J. 2020;41(48):4556-4564. doi: 10.1093/eurheartj/ehaa159.
  • 21. Gillette K, Gsell MAF, Bouyssier J, et al. Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology. Ann Biomed Eng. 2021;49(12):3143-3153. doi: 10.1007/s10439-021-02825-9.
  • 22. Schmidt A, Helgers H, Vetter FL, Juckers A, Strube J. Digital twin of mRNA-based SARS-COVID-19 vaccine manufacturing towards autonomous operation for improvements in speed, scale, robustness, flexibility and real-time release testing. Processes. 2021;9(5):748. doi: 10.3390/pr9050748.
  • 23. Laubenbacher R, Sluka JP, Glazier JA. Using digital twins in viral infection. Science. 2021;371(6534):1105-1106. doi: 10.1126/science.abf3370.
  • 24. Thamotharan P, Srinivasan S, Kesavadev J, et al. Human Digital Twin for Personalized Elderly Type 2 Diabetes Management. J Clin Med. 2023;12(6):2094. doi: 10.3390/jcm12062094.
  • 25. Abeltino A, Bianchetti G, Serantoni C, Riente A, De Spirito M, Maulucci G. Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction. Nutrients. 2023;15(5):1199. doi: 420 10.3390/nu15051199.
  • 26. Azzolin L, Eichenlaub M, Nagel C, et al. Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence. Europace. 2023;25(1):211-222. doi: 425 10.1093/europace/euac116.
  • 27. Rahmim A, Brosch-Lenz J, Fele-Paranj A, et al. Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology. Front Oncol. 2022;12:1062592. doi: 10.3389/fonc.2022.1062592.
  • 28. Wickramasinghe N, Ulapane N, Andargoli A, et al. Digital twins to enable better precision and personalized dementia care. JAMIA Open. 2022;5(3):ooac072. doi: 10.1093/jamiaopen/ooac072.
  • 29. Sahal R, Alsamhi SH, Brown KN. 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.
  • 30. Pinton P. Computational models in inflammatory bowel disease. Clin Transl Sci. 2022;15(4):824-830. doi: 10.1111/cts.13228. Epub 2022 Feb 5.
  • 31. Jung A, Gsell MAF, Augustin CM, Plank G. An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics. Mathematics (Basel). 2022;10(5):823. doi: 10.3390/math10050823.
  • 32. Barbiero P, Viñas Torné R, Lió P. Graph Representation Forecasting of Patient's Medical Conditions: Toward a Digital Twin. Front Genet. 2021;12:652907. doi: 10.3389/fgene.2021.652907.
  • 33. Voigt I, Inojosa H, Dillenseger A, Haase R, Akgün K, Ziemssen T. Digital Twins for Multiple Sclerosis. Front Immunol. 2021;12:669811. doi: 10.3389/fimmu.2021.669811.
  • 34. Eumi EM. A systematic review of Digital Twins in efficient pandemic management with challenges and emerging trends. Decision Analytics J. 2024;12:100502. doi: 10.1016/j.dajour.2024.100502
  • 35. TÜİK. Ölüm ve Ölüm Nedeni İstatistikleri, 2023 [Internet] https://data.tuik.gov.tr/Bulten/Index?p=Olum-ve-Olum-Nedeni-Istatistikleri-2023-53709 (Accessed: 01.12.224)
  • 36. Sel K, Osman D, Zare F, et al. Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact. J Am Heart Assoc. 2024;13(19):e031981. doi: 10.1161/JAHA.123.031981.
  • 37. OECD, Society at a Glance 2024: OECD Social Indicators, OECD Publishing, Paris. 2024. doi: 10.1787/918d8db3-en.
  • 38. Huang PH, Kim KH, 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.
  • 39. Thapa S, Bello A, Maurushat A, Farid F. Security Risks and User Perception towards Adopting Wearable Internet of Medical Things. Int J Environ Res Public Health. 2023;20(8):5519. doi: 10.3390/ijerph20085519.

Digital twins in personalized medicine: Insights from a systematic review

Yıl 2025, EARLY ONLINE, 1 - 8
https://doi.org/10.18621/eurj.1661091

Öz

Objectives: Digital twins (DTs) are increasingly recognized as valuable tools in the advancement of personalized medicine (PM).

Methods: This systematic review explores the current landscape of DT applications across medical domains, focusing on their feasibility, benefits, challenges, and potential future roles. Following PRISMA guidelines, literature was sourced from PubMed and Scopus using clearly defined inclusion and exclusion criteria, resulting in 14 studies eligible for full-text review.

Results: Findings show that DTs are being utilized in various specialties such as cardiology, geriatrics, radiology, and oncology, offering advantages in cost reduction, treatment precision, and patient outcomes. However, key challenges remain, including data privacy, technical integration, ethical considerations, and the need for interdisciplinary collaboration.

Conclusions: This systematic review offers a comprehensive synthesis of how DTs are being integrated into PM and highlights areas requiring further empirical research to support wider implementation.

Etik Beyan

As this study is a systematic review, ethical committee approval is not required. There are no human or animal elements in our study. Data were obtained from open sources on the internet.

Kaynakça

  • 1. Yuan B. What Personalized Medicine Humans Need and Way to It --also on the Practical Significance and Scientific Limitations of Precision Medicine. Pharmgenomics Pers Med. 2022;15:927-942. doi: 10.2147/PGPM.S380767.
  • 2. Mishra V, Chanda P, Tambuwala MM, Suttee A. Personalized medicine: An overview. Int J Pharm Qual Assur. 2019;10(2):290-294. doi: 10.25258/ijpqa.10.2.13
  • 3. Pritchard DE, Moeckel F, Villa MS, Housman LT, McCarty CA, McLeod HL. Strategies for integrating personalized medicine into healthcare practice. Per Med. 2017 ;14(2):141-152. doi: 10.2217/pme-2016-0064.
  • 4. Ginsburg GS, Willard HF. Genomic and personalized medicine: foundations and applications. Transl Res. 2009;154(6):277-287. doi: 10.1016/j.trsl.2009.09.005.
  • 5. Calcaterra V, Pagani V, Zuccotti G. Digital Twin: A Future Health Challenge in Prevention, Early Diagnosis and Personalisation of Medical Care in Paediatrics. Int J Environ Res Public Health. 2023;20(3):2181. doi: 10.3390/ijerph20032181.
  • 6. Geissler F, Heiß R, Kopp M, et al. Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. Rofo. 2021;193(4):437-445. doi: 10.1055/a-1253-8558.
  • 7. Shamanna P, Dharmalingam M, Sahay R, et al. Retrospective study of glycemic variability, BMI, and blood pressure in diabetes patients in the Digital Twin Precision Treatment Program. Sci Rep. 2021;11(1):14892. doi: 10.1038/s41598-021-94339-6.
  • 8. de Sio FS, Faber NS, Savulescu J, Vincent NA. Why less praise for enhanced performance? Moving beyond responsibility-shifting, authenticity, and cheating toward a natu re-of-activities approach. In: Jotterand F, Dubljevic V, editors. Cognitive Enhancement: Ethical and Policy Implications in International Perspectives. New York: Oxford Academic. 2016. pp. 27-41.
  • 9. Francis F. Our Posthuman Future: Consequences of the Biotechnology Revolution. Profile Books; 2003.
  • 10. Chu Y, Li S, Tang J, Wu H. The potential of the Medical Digital Twin in diabetes management: a review. Front Med (Lausanne). 2023;10:1178912. doi: 10.3389/fmed.2023.1178912.
  • 11. Hernandez-Boussard T, Macklin P, Greenspan EJ, et al. Digital twins for predictive oncology will be a paradigm shift for precision cancer care. Nat Med. 2021;27(12):2065-2066. doi: 10.1038/s41591-021-01558-5.
  • 12. Spitzer M, Dattner I, Zilcha-Mano S. Digital twins and the future of precision mental health. Front Psychiatry. 2023;14:1082598. doi: 10.3389/fpsyt.2023.1082598.
  • 13. Misra SC, Bisui S, Singh A. A study on the role of trust factor in adopting personalized medicine. Behav Inf Technol. 2020;39(7):771-787. doi:10.1080/0144929X.2019.1614225.
  • 14. Glaessgen EH, Stargel DS. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles. In: Paper for the 53rd Structures, Structural Dynamics, and Materials Conference: Special Session on the Digital Twin. American Institute of Aeronautics and Astronautics; 2012.
  • 15. Liu Y, Zhang L, Yang Y, et al. A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin. IEEE Access. 2019;7:49088-490101. doi:10.1109/ACCESS.2019.2909828.
  • 16. Currie GM, Rohren EM. Radiation Dosimetry, Artificial Intelligence and Digital Twins:Old Dog, New Tricks. Semin Nucl Med. 2023;53(3):457-466. doi: 10.1053/j.semnuclmed.2022.10.007.
  • 17. Bruynseels K, Santoni de Sio F, van den Hoven J. Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm. Front Genet. 2018;9:31. doi: 10.3389/fgene.2018.00031.
  • 18. Alber M, Buganza Tepole A, Cannon WR, et al. Integrating machine learning and multiscale modeling-perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. NPJ Digit Med. 2019;2:115. doi: 10.1038/s41746-019-0193-y.
  • 19. Iqbal JD, Krauthammer M, Biller-Andorno N. The Use and Ethics of Digital Twins in Medicine. J Law Med Ethics. 2022;50(3):583-596. doi: 10.1017/jme.2022.97. PMID: 36398633.
  • 20. Corral-Acero J, Margara F, Marciniak M, et al. The 'Digital Twin' to enable the vision of precision cardiology. Eur Heart J. 2020;41(48):4556-4564. doi: 10.1093/eurheartj/ehaa159.
  • 21. Gillette K, Gsell MAF, Bouyssier J, et al. Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology. Ann Biomed Eng. 2021;49(12):3143-3153. doi: 10.1007/s10439-021-02825-9.
  • 22. Schmidt A, Helgers H, Vetter FL, Juckers A, Strube J. Digital twin of mRNA-based SARS-COVID-19 vaccine manufacturing towards autonomous operation for improvements in speed, scale, robustness, flexibility and real-time release testing. Processes. 2021;9(5):748. doi: 10.3390/pr9050748.
  • 23. Laubenbacher R, Sluka JP, Glazier JA. Using digital twins in viral infection. Science. 2021;371(6534):1105-1106. doi: 10.1126/science.abf3370.
  • 24. Thamotharan P, Srinivasan S, Kesavadev J, et al. Human Digital Twin for Personalized Elderly Type 2 Diabetes Management. J Clin Med. 2023;12(6):2094. doi: 10.3390/jcm12062094.
  • 25. Abeltino A, Bianchetti G, Serantoni C, Riente A, De Spirito M, Maulucci G. Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction. Nutrients. 2023;15(5):1199. doi: 420 10.3390/nu15051199.
  • 26. Azzolin L, Eichenlaub M, Nagel C, et al. Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence. Europace. 2023;25(1):211-222. doi: 425 10.1093/europace/euac116.
  • 27. Rahmim A, Brosch-Lenz J, Fele-Paranj A, et al. Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology. Front Oncol. 2022;12:1062592. doi: 10.3389/fonc.2022.1062592.
  • 28. Wickramasinghe N, Ulapane N, Andargoli A, et al. Digital twins to enable better precision and personalized dementia care. JAMIA Open. 2022;5(3):ooac072. doi: 10.1093/jamiaopen/ooac072.
  • 29. Sahal R, Alsamhi SH, Brown KN. 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.
  • 30. Pinton P. Computational models in inflammatory bowel disease. Clin Transl Sci. 2022;15(4):824-830. doi: 10.1111/cts.13228. Epub 2022 Feb 5.
  • 31. Jung A, Gsell MAF, Augustin CM, Plank G. An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics. Mathematics (Basel). 2022;10(5):823. doi: 10.3390/math10050823.
  • 32. Barbiero P, Viñas Torné R, Lió P. Graph Representation Forecasting of Patient's Medical Conditions: Toward a Digital Twin. Front Genet. 2021;12:652907. doi: 10.3389/fgene.2021.652907.
  • 33. Voigt I, Inojosa H, Dillenseger A, Haase R, Akgün K, Ziemssen T. Digital Twins for Multiple Sclerosis. Front Immunol. 2021;12:669811. doi: 10.3389/fimmu.2021.669811.
  • 34. Eumi EM. A systematic review of Digital Twins in efficient pandemic management with challenges and emerging trends. Decision Analytics J. 2024;12:100502. doi: 10.1016/j.dajour.2024.100502
  • 35. TÜİK. Ölüm ve Ölüm Nedeni İstatistikleri, 2023 [Internet] https://data.tuik.gov.tr/Bulten/Index?p=Olum-ve-Olum-Nedeni-Istatistikleri-2023-53709 (Accessed: 01.12.224)
  • 36. Sel K, Osman D, Zare F, et al. Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact. J Am Heart Assoc. 2024;13(19):e031981. doi: 10.1161/JAHA.123.031981.
  • 37. OECD, Society at a Glance 2024: OECD Social Indicators, OECD Publishing, Paris. 2024. doi: 10.1787/918d8db3-en.
  • 38. Huang PH, Kim KH, 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.
  • 39. Thapa S, Bello A, Maurushat A, Farid F. Security Risks and User Perception towards Adopting Wearable Internet of Medical Things. Int J Environ Res Public Health. 2023;20(8):5519. doi: 10.3390/ijerph20085519.
Toplam 39 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Birinci Basamak Sağlık Hizmetleri
Bölüm Meta-Analysis
Yazarlar

Ebru Uğraş 0000-0002-5618-5265

Erken Görünüm Tarihi 28 Temmuz 2025
Yayımlanma Tarihi
Gönderilme Tarihi 19 Mart 2025
Kabul Tarihi 21 Temmuz 2025
Yayımlandığı Sayı Yıl 2025 EARLY ONLINE

Kaynak Göster

AMA Uğraş E. Digital twins in personalized medicine: Insights from a systematic review. Eur Res J. Published online 01 Temmuz 2025:1-8. doi:10.18621/eurj.1661091

e-ISSN: 2149-3189 


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