The Role of Cloud Computing in Personalized Medicine: A Systematic Review

Temiwande Esho *

Lincoln University of Pennsylvania, United States of America.

Oluwafunto Ayeni

Indianapolis University Purdue University Indianapolis (IUPUI), United States of America.

Oluwafunsho Lasisi

South Western Oklahoma State University, United States of America.

Olorunmaiye Peter

University of Ilorin, Kwara State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

This review critically examines the role of cloud computing in personalized medicine, employing a systematic literature analysis methodology. The study involved a comprehensive search and evaluation of scholarly articles from academic databases and journals, focusing on publications within the last decade. Key terms such as "cloud computing", "personalized medicine", "genomic data management", and "patient-centric healthcare technology" guided the literature search. The study illuminates the significant role of cloud computing in revolutionizing personalized medicine. It highlights the importance of cloud computing for managing large-scale genetic data and individualized patient care, as well as its role in enhancing patient-centric care through innovations like cloud-fog diagnostics. Challenges in data security, privacy, and ethical considerations are acknowledged, emphasizing the need for robust governance and compliance. The future of cloud computing in personalized medicine is poised for growth, with immense opportunities for innovation, yet accompanied by challenges in data management and healthcare equity. The ongoing evolution of cloud computing in healthcare promises substantial advancements, albeit with a need for careful consideration of its complexities to fully realize its potential.

Keywords: Cloud computing, personalized medicine, internet of medical things (IoMT)


How to Cite

Esho, Temiwande, Oluwafunto Ayeni, Oluwafunsho Lasisi, and Olorunmaiye Peter. 2024. “The Role of Cloud Computing in Personalized Medicine: A Systematic Review”. Current Journal of Applied Science and Technology 43 (3):1-8. https://doi.org/10.9734/cjast/2024/v43i34355.

Downloads

Download data is not yet available.

References

Mathur S, Sutton J. Personalized medicine could transform healthcare. Biomed. Reports. 2017; 7(1):3–5.

Meiliana A, Dewi NM, Wijaya AY. Personalized Medicine: The Future of Health Care. Indones. Biomed. J. 2016;8:127[Online]. Available:https://api.semanticscholar.org/CorpusID:78335287

Žitnik IP et al. Personalized laboratory medicine: a patient-centered future approach. Clin. Chem. Lab. Med. 2018;56:1981–1991. Available:https://api.semanticscholar.org/CorpusID:51612272

Joseph R, Brown P. The cloud gets personal: perspectives on cloud computing for person alized medicine.2020;1364–1377. DOI: 10.4018/978-1-7998-1204-3.ch068.

Mathew G, Obradovic Z. Improving computational efficiency for personalized medical applications in mobile cloud computing environment. IEEE Int. Conf. Healthc. Informatics. 2013;535–540. Available:https://api.semanticscholar.org/CorpusID:16139808

Marcu R, Popescu D, Danila I. Healthcare integration based on cloud computing. UPB Sci. Bull. 2015;77(2):31–42,.

Zafar Z, Islam S, Aslam MS, Sohaib M. Cloud computing services for the healthcare industry. Int J Multidiscip Sci Eng. 2014;5:25–29.

Bahga A, Madisetti VK. Healthcare data integration and informatics in the cloud. Computer (Long. Beach. Calif). 2015;48:50–57. Available:https://api.semanticscholar.org/CorpusID:6407253

Molo MJ et al. A Review of Evolutionary Trends in Cloud Computing and Applications to the Healthcare Ecosystem. Appl. Comput. Intell. Soft Comput. 2021;1843671:1-1843671:16. Available:https://api.semanticscholar.org/CorpusID:239204973

Hannock CM. Healthcare Usage of Cloud Computing and Resources. J. Inf. Technol. & Softw. Eng. 2021;1–3. Available:https://api.semanticscholar.org/CorpusID:237311098

Devadass L, Sekaran SS, Thinakaran R. Cloud computing in Healthcare. Int. J. Students’ Res. Technol. & Manag. 2017;5:25–31. Available:https://api.semanticscholar.org/CorpusID:67810382

Agapito G, Cannataro M. An overview on the challenges and limitations using cloud computing in healthcare corporations. Big Data Cogn. Comput. 2023;7:68. DOI: 10.3390/bdcc7020068.

Calabrese B, Cannataro M. Cloud computing in healthcare and biomedicine. Scalable Comput. Pract. Exp. 2015;16. DOI: 10.12694/scpe.v16i1.1057.

April A. Cloud-computing and precision medicine: Big data offers big opportunities. Eur. J. Public Health. 2019;29. DOI: 10.1093/eurpub/ckz185.258.

Ali O, Shrestha A, Soar J, Fosso Wamba S. Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review. Int. J. Inf. Manage. 2018;43:146–158. DOI: 10.1016/j.ijinfomgt.2018.07.009.

Rai V et al. Cloud computing in healthcare industries: Opportunities and challenges. Recent Innov. Comput. Proc. ICRIC 2021. 2022;2:695–707.

Tver R, Federation, Moscow. The evolution of personalized medicine: Literature review. Res. Pract. Med. J; 2022.

Available:https://api.semanticscholar.org/CorpusID:252228364

Gajare SR, Deshmukh AS, Shinde CK. Personalized medicine: A review. Int. J. Pharm. Sci. Rev. Res; 2021. Available:https://api.semanticscholar.org/CorpusID:239703695

Redekop WK, Mladsi D. the faces of personalized medicine: A framework for understanding its meaning and scope. Value Heal. 2013;16(6):S4–S9. DOI:https://doi.org/10.1016/j.jval.2013.06.005

Pokorska-Bocci A, Stewart A, Sagoo GS, Hall A, Kroese M, Burton H. Personalized medicine: What’s in a name?. Per. Med. 2014;11(2):197–210.

Sun L, Jiang X, Ren H, Guo Y. Edge-Cloud Computing and Artificial Intelligence in Internet of Medical Things: Architecture, Technology and Application. IEEE Access. 2020;1. DOI: 10.1109/ACCESS.2020.2997831.

Gifari MW, Samodro P, Kurniawan DW. Artificial intelligence toward personalized medicine. Pharm. Sci. Res; 2021. Available:https://api.semanticscholar.org/CorpusID:243304623

Chakraborty C, Kishor A. Real-time cloud-based patient-centric monitoring using computational health systems. IEEE Trans. Comput. Soc. Syst. 2022;9(6):1613–1623. DOI: 10.1109/TCSS.2022.3170375.

Gohar AN, Abdelmawgoud SA, Farhan MS. A patient-centric healthcare framework reference architecture for better semantic interoperability based on blockchain, cloud, and IoT. IEEE Access. 2022;10:92137–92157 DOI: 10.1109/ACCESS.2022.3202902.

Chen D, Chen L, Fan X, He L, Pan S, Hu R. Securing patient-centric personal health records sharing system in cloud computing. China Commun. 2014;11: 13:121–127. DOI: 10.1109/CC.2014.7022535.

Agarwal A, Henehan N, Somashekarappa V, Pandya AS, Kalva H, Furht B. A Cloud Computing Based patient centric medical information system BT - Handbook of Cloud Computing. B. Furht and A. Escalante, Eds., Boston, MA: Springer US. 2010;553–573. DOI: 10.1007/978-1-4419-6524-0_24.

Santos NL, Younis W, Ghita BV, Masala GB. Enhancing medical data security on public cloud. 2021 IEEE Int. Conf. Cyber Secur. Resil. 2021;103–108. Available:https://api.semanticscholar.org/CorpusID:237445631

Blobel B, Lopez DM, Gonzalez C. Patient privacy and security concerns on big data for personalized medicine. Health Technol. (Berl). 2016;6(1):75–81. DOI: 10.1007/s12553-016-0127-5.

Wang B, Song W, Lou W, Hou YT. Privacy-preserving pattern matching over encrypted genetic data in cloud computing. in IEEE INFOCOM 2017- IEEE Conference on Computer Communications. 2017;1–9. DOI: 10.1109/INFOCOM.2017.8057178

Chow-White PA, MacAulay M, Charters A, Chow P. From the bench to the bedside in the big data age: Ethics and practices of consent and privacy for clinical genomics and personalized medicine. Ethics Inf. Technol. 2015;17:189–200.

Mendelson D, Legal protections for personal health information in the age of big data—A proposal for regulatory framework; 2017.

Santaló J, Berdasco M. Ethical implications of epigenetics in the era of personalized medicine. Clin. Epigenetics. 2022;14(1):44. DOI: 10.1186/s13148-022-01263-1

Sethu SG, Nair RS, Sadath L. Big data in precision medicine and its legal implications. In 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS). 2020;350–356. DOI: 10.1109/ICIIS51140.2020.9342723.

Cohen V, Gerke S, Kramer. DB. Ethical and legal implications of remote monitoring of medical devices. Milbank Q. 2020;98(4):1257–1289. DOI: https://doi.org/10.1111/1468-0009.12481.

Silva I, Soto M. Privacy-preserving data sharing in healthcare: An in-depth analysis of big data solutions and regulatory compliance. Int. J. Appl. Heal. Care Anal. 2022;7(1) SE-Articles: 14–23. Available:https://norislab.com/index.php/IJAHA/article/view/39

Cirillo D, Valencia A. Big data analytics for personalized medicine. Curr. Opin. Biotechnol. 2019;58:161–167. DOI:https://doi.org/10.1016/j.copbio.2019.03.004.

Viceconti M, Hunter P, Hose D. Big data, big knowledge: Big data for personalized healthcare. IEEE J. Biomed. Heal. Informatics. 2015;19(1). DOI: 10.1109/JBHI.2015.2406883.

Ahmed MN, Toor AS, O’Neil K, Friedland D. Cognitive computing and the future of health care cognitive computing and the future of healthcare: The cognitive power of IBM watson has the potential to transform global personalized medicine. IEEE Pulse. 2017;8(3):4–9. DOI: 10.1109/MPUL.2017.2678098.

Lightbody G et al. Review of applications of high-throughput sequencing in personalized medicine: Barriers and facilitators of future progress in research and clinical application. Brief. Bioinform. 2019;20(5):1795–1811. DOI: 10.1093/bib/bby051.

Kuo AMH. Opportunities and challenges of cloud computing to improve health care services. J Med Internet Res. 2011; 13(3):e67 DOI: 10.2196/jmir.1867.

Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med. Genomics. 2015;8(1):33. DOI: 10.1186/s12920-015-0108-y.