Kişiselleştirilmiş Tıp İçin Dijital İkiz: Sistematik Derleme

Yıl 2024, Cilt: 6 Sayı: 1, 28 - 43, 29.02.2024

Dilek Alay

https://doi.org/10.57224/jhpr.1342561

Öz

Amaç: Kişiselleştirilmiş tıp için dijital ikizlerin uygunluğu, faydaları, zorlukları, sorunları, kişiselleştirilmiş tıptaki uygulama alanlarını görmeye yarayacak bir çerçeve sağlamaktır.
Gereç ve Yöntem: Bu bağlamda sistematik derleme yöntemi kullanılmıştır. Çalışmada Pubmed ve Scopus veri tabanlarından faydalanılmıştır. Çalışmanın tasarımı PRISMA kontrol listesi ve akış diyagramındaki adımlar takip edilerek oluşturulmuştur. Belirli dahil etme ve dışlama kriterleri kullanılarak aramalar yapılmıştır.
Bulgular: Aramalar bittikten sonra elemeler yapılmış ve 14 çalışma tam metin incelemesine dahil edilmiştir.
Sonuç: Çalışma sonucunda kişiselleştirilmiş tıp için dijital ikizlerin birçok tıp alanında uygulanabilir olduğu, maliyetleri düşürmek ve sağlığı iyileştirmek gibi birçok faydalarının olduğu, karmaşık örüntüler, mahremiyet, maliyet, ayrımcılık gibi birçok zorluk ve sorunun olduğu görülmüştür. Daha iyi sonuçlar alabilmek için bu çalışmanın deneysel ortamda uygulanması önerilmektedir.

Anahtar Kelimeler

Dijital ikiz, Kişiselleştirilmiş tıp, Sağlık

Destekleyen Kurum

yok

Teşekkür

Bu çalışmaya yürütmemde katkılarından dolayı değerli Doç. Dr. Nezihe TÜFEKÇİ'ye teşekkürlerimi sunarım.

The Digital Twin for Personalised Medicine: A Systematic Review

Öz

Personalized medicine is a health model that is gaining traction in all areas of medicine. The digital twin is seen as a complementary strategy for this model. The use of a digital twin for personalized medicine involves the patient, the digital copy of the patient and the interaction between the two. With these models, many diseases can be recognized and prevented before they occur. The aim of this study is to provide a framework to see the suitability, benefits, challenges, problems and application areas of digital twins for personalized medicine. In this context, systematic review method was used. Pubmed and Scopus databases were utilized in the study. The design of the study was created by following the steps in the PRISMA checklist and flow diagram. Searches were conducted using specific inclusion and exclusion criteria. After the searches were completed, 14 studies were included in the full text review. As a result of the study, it was seen that digital twins for personalized medicine are applicable in many medical fields, have many benefits such as reducing costs and improving health, but there are many challenges and problems such as complex patterns, privacy, cost, discrimination. It is recommended to apply this study in an experimental setting to get better results

Anahtar Kelimeler

Digital twin, Personalised medicine, Health

Kaynakça

• Barbiero P, Viñas Torné R, Lió P. Graph Representation Forecasting of Patient’s Medical Conditions: Toward a Digital Twin. Front Genet. 2021;12.
• 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;15:927–42.
• Mishra V, Chanda P, Tambuwala MM, Suttee A. Personalized medicine: An overview. International Journal of Pharmaceutical Quality Assurance. 2019;10(2):290–4.
• Tekpınar L, Erdem R. Kişiselleştirilmiş tıp ve genom araştırmalarının sağlık çıktıları bağlamında değerlendirilmesi [Internet]. Vol. 22, Hacettepe Sağlık İdaresi Dergisi. 2019. Available from: https://orcid.org/0000-0003-2267-771X
• Pritchard DE, Moeckel F, Villa MS, Housman LT, McCarty CA, McLeod HL. Strategies for integrating personalized medicine into healthcare practice. Vol. 14, Personalized Medicine. 2017.
• Ginsburg GS, Willard HF. Genomic and personalized medicine: foundations and applications. Translational Research. 2009;154(6):277–87.
• 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).
• Misra SC, Bisui S, Singh A. A study on the role of trust factor in adopting personalised medicine. Behaviour and Information Technology. 2020;39(7):771–87.
• Grieves M. Digital Twin : Manufacturing Excellence through Virtual Factory Replication. White Paper. 2014;(March).
• 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.
• Liu Y, Zhang L, Yang Y, Zhou L, Ren L, Wang F, et al. A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin. IEEE Access. 2019;7:49088–101.
• Currie GM, Rohren EM. Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks. Semin Nucl Med. 2023;53(3):457–66.
• Bruynseels K, de Sio FS, van den Hoven J. Digital Twins in health care: Ethical implications of an emerging engineering paradigm. Front Genet. 2018;9(FEB).
• Alber M, Buganza Tepole A, Cannon WR, De S, Dura-Bernal S, Garikipati K, et al. Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. Vol. 2, npj Digital Medicine. 2019.
• Aynacı İ. Dijital ikiz ve sağlık uygulamaları. İzmir Katip Çelebi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2020;3(1):70–82.
• Karakaş Ü. Dijital sağlık ve Hassas Tıp. In: Erdoğan Tarakçı İ, Göktaş B, editors. Dijital Gelecek Dijital Dönüşüm-2 [Internet]. EfeAkademi Yayınları.; 2021. p. 29–44. Available from: https://www.researchgate.net/publication/354464455
• Corral-Acero J, Margara F, Marciniak M, Rodero C, Loncaric F, Feng Y, et al. The “Digital Twin” to enable the vision of precision cardiology. Eur Heart J. 2020;41(48):4556-4564B.
• Iqbal JD, Krauthammer M, Biller-Andorno N. The Use and Ethics of Digital Twins in Medicine. The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics. 2022;50(3):583–96.
• Eddy DM, Schlessinger L. Archimedes: A trial-validated model of diabetes. Diabetes Care. 2003;26(11).
• Fagherazzi G. Deep digital phenotyping in type 1 diabetes: The reinvention of epidemiological research | Phénotypage numérique profond dans le diabète de type 1: le renouveau de la recherche en épidémiologie. Medecine des Maladies Metaboliques. 2021;15(4):375–9.
• Grande Gutierrez N, Mathew M, McCrindle BW, Tran JS, Kahn AM, Burns JC, et al. Hemodynamic variables in aneurysms are associated with thrombotic risk in children with Kawasaki disease. Int J Cardiol. 2019;281.
• Shang JK, Esmaily M, Verma A, Reinhartz O, Figliola RS, Hsia TY, et al. Patient-Specific Multiscale Modeling of the Assisted Bidirectional Glenn. Annals of Thoracic Surgery. 2019;107(4):1232–9.
• Kovatchev B. A Century of Diabetes Technology: Signals, Models, and Artificial Pancreas Control. Trends in Endocrinology and Metabolism. 2019;30(7):432–44.
• Brown SA, Kovatchev BP, Raghinaru D, Lum JW, Buckingham BA, Kudva YC, et al. Six-month randomized, multicenter trial of closed-loop control in type 1 diabetes. New England Journal of Medicine. 2019;381(18):1707–17.
• Elayan H, Aloqaily M, Guizani M. Digital Twin for Intelligent Context-Aware IoT Healthcare Systems. IEEE Internet Things J. 2021;8(23):16749–57.
• Gillette K, Gsell MAF, Bouyssier J, Prassl AJ, Neic A, Vigmond EJ, 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):3143–53.
• 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).
• Laubenbacher R, Sluka JP, Glazier JA. Using digital twins in viral infection. Science (1979). 2021;371(6534):1105–6.
• Pesapane F, Rotili A, Penco S, Nicosia L, Cassano E. Digital Twins in Radiology. J Clin Med. 2022;11(21).
• Lloyd DG, Saxby DJ, Pizzolato C, Worsey M, Diamond LE, Palipana D, et al. Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision. J Sci Med Sport. 2023;26:S30–9.
• Kamel Boulos MN, Zhang P. Digital twins: From personalised medicine to precision public health. J Pers Med. 2021;11(8).
• 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).
• Maes M. Precision Nomothetic Medicine in Depression Research: A New Depression Model, and New Endophenotype Classes and Pathway Phenotypes, and A Digital Self. J Pers Med. 2022;12(3).
• https://www.usa.philips.com/healthcare/resources/feature-detail/ultrasound-heartmodel. https://www.usa.philips.com/healthcare/resources/feature-detail/ultrasound-heartmodel. 2023 [cited 2023 Aug 13]. Ultrasound Heartmodel. Available from: https://www.usa.philips.com/healthcare/resources/feature-detail/ultrasound-heartmodel
• URL. https://liu.se/forskning/medigit. 2023. Medicinsk digital tvilling (MeDigiT).
• 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. 2022;22(15).
• Gkouskou K, Vlastos I, Karkalousos P, Chaniotis D, Sanoudou D, Eliopoulos AG. The “virtual Digital Twins” Concept in Precision Nutrition. Advances in Nutrition. 2020;11(6):1405–13.
• Björnsson B, Borrebaeck C, Elander N, Gasslander T, Gawel DR, Gustafsson M, et al. Digital twins to personalize medicine. Genome Med. 2020;12(1).
• Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Version 5.1.0. [Internet]. 2011 [cited 2023 Aug 13]. Available from: http://www.mrc-bsu.cam.ac.uk/ cochrane/ handbook/
• URL. https://pubmed.ncbi.nlm.nih.gov/about/. 2023. About.
• URL. https://www.elsevier.com/solutions/scopus/how-scopus-works/content?dgcid=RN_AGCM_Sourced_300005030. 2023. Scopus.
• Thamotharan P, Srinivasan S, Kesavadev J, Krishnan G, Mohan V, Seshadhri S, et al. Human Digital Twin for Personalized Elderly Type 2 Diabetes Management. J Clin Med. 2023;12(6).
• 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).
• Azzolin L, Eichenlaub M, Nagel C, Nairn D, Sanchez J, Unger L, et al. Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence. Europace. 2023;25(1):211–22.
• Rahmim A, Brosch-Lenz J, Fele-Paranj A, Yousefirizi F, Soltani M, Uribe C, et al. Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology. Front Oncol. 2022;12.
• Wickramasinghe N, Ulapane N, Andargoli A, Ossai C, Shuakat N, Nguyen T, et al. Digital twins to enable better precision and personalized dementia care. JAMIA Open. 2022;5(3).
• Pinton P. Computational models in inflammatory bowel disease. Clin Transl Sci. 2022;15(4):824–30.
• 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. 2022;10(5).
• Barbiero P, Viñas Torné R, Lió P. Graph Representation Forecasting of Patient’s Medical Conditions: Toward a Digital Twin. Front Genet. 2021;12.
• Voigt I, Inojosa H, Dillenseger A, Haase R, Akgün K, Ziemssen T. Digital Twins for Multiple Sclerosis. Front Immunol. 2021;12.
• Geissler F, Heiβ R, Kopp M, Wiesmüller M, Saake M, Wuest W, et al. Personalized computed tomography - Automated estimation of height and weight of a simulated digital twin using a 3D camera and artificial intelligence. RoFo Fortschritte auf dem Gebiet der Rontgenstrahlen und der Bildgebenden Verfahren. 2021;193(4):437–45.
• T.C. Sağlık Bakanlığı Sağlık Bilgi Sistemleri Genel Müdürlüğü. Sağlık İstatistikleri Yıllığı 2021. 2021.
• URL. https://data.tuik.gov.tr/Bulten/Index?p=Istatistiklerle-Yaslilar-2022-49667. 2023. İstatistiklerle Yaşlılar.
• Shamanna P, Dharmalingam M, Sahay R, Mohammed J, Mohamed M, Poon T, 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).
• de Sio FS, Faber NS, Savulescu J, Vincent NA. Why less praise for enhanced performance? Moving beyond responsibility-shifting, authenticity, and cheating toward a nature-of-activities approach. In: Cognitive enhancement: Ethical and policy implications in international perspectives. 2016.
• Fukuyama Francis. Our posthuman future: Consequences of the biotechnology revolution. Frofile Books; 2003. 272 p.
• URL. https://www.sdtc.se. 2023. Swedish Digital Twin Consortium.
• Hernandez-Boussard T, Macklin P, Greenspan EJ, Gryshuk AL, Stahlberg E, Syeda-Mahmood T, et al. Digital twins for predictive oncology will be a paradigm shift for precision cancer care. Nat Med. 2021;27(12):2065–6.
• Spitzer M, Dattner I, Zilcha-Mano S. Digital twins and the future of precision mental health. Front Psychiatry. 2023;14.