Impact of Metaverse Technologies Integration on Biotechno-logical Innovation: A Literature Review

  • Amra Abazi Feta International Balkan University, Skopje, R. North Macedonia
  • Hiqmet Kamberaj International Balkan University, Skopje, R. North Macedonia
Keywords: Metaverse, Biotechnological Innovation, Virtual Collaboration, Immersive Environments, Digital Twins, Simulation, Data Security

Abstract

The convergence of metaverse technologies (such as virtual reality, augmented reality, artificial intelli-gence, and digital twins) into biotechnology is ushering in a new age for the creation of pharmaceuticals, medical science research, and teaching. The interactive and immersive environments enable collaboration without geographical limitations through virtual labs, improve the articulation of complex biological processes, and accelerate experiments using enhanced models powered by artificial intelligence. High-visibility use cases comprise virtual clinical trials founded on digital twin models that simulate individual patient profiles. The application of AI in drug discovery medicine, with its expedited time-to-market and 3D learning environments, enhances the knowledge and procedural precision of biotech professionals. This study employs a qualitative methodological approach, comprising an extensive literature review coupled with a case study analysis, to reflect on the participation of metaverse technologies within the biotechnology sector. This systematic review focuses on the transformative role of the metaverse in biotechnolo-gy, analysing its capacity to enable global collaboration, advanced simulations, and immer-sive education. By synthesising peer-reviewed literature (2019-2025), we highlight key ad-vancements, such as AI-driven drug discovery and virtual laboratories, while addressing critical challenges, including data privacy, ethical concerns, and computational require-ments. In this review, we aim to highlight the metaverse’s potential to transform biotechno-logical research and emphasise the need for interdisciplinary solutions to harness its bene-fits. Drawing on an analysis of trends in cloud collaboration, digital simulation, immersive learning, and ethical issues, the research provides a critical analysis of the challenges and problems posed by the digital revolution. Key areas discussed in immense detail include data privacy, algorithm bias, computational infrastructure, and regulatory uncertainty. Our findings emphasise the need for interdisciplinary research and the provision of comprehensive ethi-cal and technical guidelines to enable the secure and equitable use of metaverse technologies in biotech-nology. This study will primarily contribute to the growing corpus of scholarly literature by providing a concise and logical synthesis of existing knowledge, identifying key areas for future research and devel-opment.

Downloads

Download data is not yet available.

References

1. Mystakidis, S. (2022). Metaverse. Encyclopedia, 2(1), 486-497. https://doi.org/10.3390/encyclopedia2010031
2. Lee, L. H., Braud, T., Zhou, P., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C., & Hui, P. (2021). All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda. arXiv preprint arXiv:2110.05352. URL: https://arxiv.org/abs/2110.05352
3. Shen, S., Qi, W., Liu, X. et al. From virtual to reality: innovative practices of digital twins in tumor therapy. J Transl Med 23, 348 (2025). https://doi.org/10.1186/s12967-025-06371-z
4. Uddin, Mueen & Obaidat, Muath & Manickam, Selvakumar & Laghari, Shams Ul Arfeen & Dandoush, Abdulhalim & Ullah, Hidayat & Ullah, Syed Sajid. (2024). Exploring the convergence of Metaverse, Blockchain, and AI: A comprehensive survey of enabling technologies, applications, challenges, and future directions. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 14. 10.1002/widm.1556.
5. Bordukova, M., Makarov, N., Rodriguez-Esteban, R., Schmich, F., & Menden, M. P. (2023). Generative artificial intelligence empowers digital twins in drug discovery and clinical trials. Expert Opinion on Drug Discovery, 19(1), 33–42. https://doi.org/10.1080/17460441.2023.2273839
6. Mercado, Justine & Picardal, Jay. (2023). Virtual Laboratory Simulations in Biotechnology: A Systematic Review. Science Education International. 34. 52-57. 10.33828/sei.v34.i1.6.
7. Maedeh Mosharraf, Data governance in metaverse: Addressing security threats and countermeasures across the data lifecycle, Technology in Society, Volume 82, 2025, 102910, ISSN 0160-791X, https://doi.org/10.1016/j.techsoc.2025.102910.
8. Kaddoura S, Al Husseiny F. The rising trend of Metaverse in education: challenges, opportunities, and ethical considerations. PeerJ Comput Sci. 2023 Feb 13;9:e1252. doi: 10.7717/peerj-cs.1252. PMID: 37346578; PMCID: PMC10280453.
9. Venkatesh, K.P., Raza, M.M. & Kvedar, J.C. Health digital twins as tools for precision medicine: Considerations for computation, implementation, and regulation. npj Digit. Med. 5, 150 (2022). https://doi.org/10.1038/s41746-022-00694-7
10. Petrigna, L., & Musumeci, G. (2022). The Metaverse: A New Challenge for the Healthcare System: A Scoping Review. Journal of Functional Morphology and Kinesiology, 7(3), 63, 10.3390/jfmk7030063
11. K. -B. Ooi et al., "The Metaverse in Engineering Management: Overview, Opportunities, Challenges, and Future Research Agenda" in IEEE Transactions on Engineering Management, vol. 71, pp. 13882-13889, 2024, doi: 10.1109/TEM.2023.3307562.
12. Taylor, S., & Soneji, S. (2022). Bioinformatics and the Metaverse: Are We Ready? Frontiers in Bioinformatics, 2, 863676. DOI: 10.3389/fbinf.2022.863676
13. Deeks, H. M., Walters, R. K., Hare, S. R., O'Connor, M. B., Mulholland, A. J., & Glowacki, D. R. (2020). Interactive Molecular Dynamics in Virtual Reality for Accurate Flexible Protein-Ligand Docking. PLOS ONE, 15(3), e0228461. DOI: 10.1371/journal.pone.0228461
14. T. Gutmann, I. B. Schaefer, C. S. Poojai, I. Vattulainen, M. Strauss, U. Coskun, Cryo-EM structure of the complete and ligand-saturated insulin receptor ectodomain
15. J. Cell Biol., 219, 1540-8140, 2020 in an intercellular virtual environment created using the ProteinVR software.
16. Williams, A., Lee, J., Kadakia, K., et al. (Eds.). (2023, February 10). Emerging stronger from COVID-19: Priorities for health system transformation. The Learning Health System Series. National Academy of Medicine. National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK589824/
17. Chengoden, R., Victor, N., Huynh-The, T., Yenduri, G., Jhaveri, R. H., Alazab, M., & Gadekallu, T. R. (2023). Metaverse for healthcare: a survey on potential applications, challenges and future directions. IEEE Access, 11, 12765-12795.
18. Patel, S. K. (2022). R&D Using the Metaverse and Digital Twins. Applied Clinical Trials, 31(7/8). URL: https://www.appliedclinicaltrialsonline.com/view/r-d-using-the-metaverse-and-digital-twins
19. Wang, X., Zhang, Y., & Zhang, Y. (2023). AI-Driven Virtual Environments for Predictive Medicine. arXiv preprint arXiv:2301.00001. URL: https://arxiv.org/abs/2301.00001
20. Gani, Abrara; Pickering, Oliver; Ellis, Caroline; Sabri, Omar; Pucher, Philip. Impact of haptic feedback on surgical training outcomes: A Randomised Controlled Trial of haptic versus non-haptic immersive virtual reality training. Annals of Medicine & Surgery 83(), November 2022. | DOI: 10.1016/j.amsu.2022.104734
21. Kostick-Quenet, K., Rahimzadeh, V. Ethical hazards of health data governance in the metaverse. Nat Mach Intell 5, 480–482 (2023). https://doi.org/10.1038/s42256-023-00658-w
22. Tsai, M. C., Liang, J. C., & Tsai, C. C. (2022). Virtual Reality Enhancing Medical Education and Practice: Brief Communication. Journal of Medical Education, 26(4), 599–601. DOI: 10.3946/kjme.2022.234
23. Wiederhold, B. K. (2022). The Metaverse in Healthcare: Accelerating Research and Innovation. Cyberpsychology, Behavior, and Social Networking, 25(6), 345–346. DOI: 10.1089/cyber.2022.29210.editorial
24. Wiederhold BK. Metaverse Games: Game Changer for Healthcare? Cyberpsychol Behav Soc Netw. 2022 May; 25(5):267-269. doi: 10.1089/cyber.2022.29246.editorial. PMID: 35549346.
25. Minji Kim, Seungzoon Lee, Jeongil Choi. (2023). A Study on Factors Affecting Intention to Continuous Use Metaverse Platform Service. Journal of Korean Society for Quality Management, 51(1), 97–117. https://doi.org/10.7469/JKSQM.2023.51.1.97
26. Shah, C., Pathak, J., & Kumar, S. (2024). Utilizing Blockchain Technology for Healthcare and Biomedical Research: A Review. Cureus, 16(10), e72040. DOI: 10.7759/cureus.72040
27. Rahimzadeh, V., Kostick-Quenet, K., Blumenthal Barby, J., & McGuire, A. L. (2023). Ethics Education for Healthcare Professionals in the Era of ChatGPT and Other Large Language Models: Do We Still Need It? The American Journal of Bioethics, 23(10), 17–27. https://doi.org/10.1080/15265161.2023.2233358
28. PubMed. (n.d.). https://pubmed.ncbi.nlm.nih.gov/
29. IEEE Xplore Digital Library*. (n.d.). Retrieved from [https://ieeexplore.ieee.org/Xplore/home.jsp]
30. SpringerLink. (n.d.). Retrieved from https://link.springer.com/
31. ScienceDirect. (n.d.). Retrieved from https://www.sciencedirect.com/
32. Google Scholar. (n.d.). Retrieved from https://scholar.google.com/
33. Sakala IG, Eichinger KM, Petrovsky N. Neonatal vaccine effectiveness and the role of adjuvants. Expert Rev Clin Immunol. 2019 Aug;15(8):869-878. doi: 10.1080/1744666X.2019.1642748. Epub 2019 Jul 25. PMID: 31293189; PMCID: PMC6678067.
34. Yunxiao Ren, Andrew A. Pieper, Feixiong Cheng,Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease,Neurotherapeutics,Volume 22, Issue 3,2025,e00553,ISSN 1878-7479,https://doi.org/10.1016/j.neurot.2025.e00553.
35. O. Goldstein. Cogent Education 3, 1200833 (2016).
36. W. Muliawan, W. S. Nahar, C. E. Sebastian, E. Yuliza, and Khairurri-jal. Journal of Physics: Conference Series 739, 012139 (2016).
37. S. T. Kanyesigye, J. Uwamahoro, and I. Kemeza. Physical Review Physics Education Research 18, 010140 (2022).
38. R. Cross. Eur. J. Phys. 45, 035003 (2024).
39. A. Vidak et al. Eur. J. Phys. 45, 023002 (2024).
40. P. Wul↵. Eur. J. Phys. 45, 023001 (2024).
41. L. Moran and H. Vaughan. New Directions in the Teaching of the Physical Sciences 8, 17–21 (2016).
42. V. K. LaBoskey, J. Loughran, and M. L. Hamilton. International Handbook of Self-study of Teaching and Teacher Education Practices 2, 817–869 (2004).
43. L. S. Vygotsky. Mind in Society: The Development of Higher Psychological Processes. Cambridge, MA, Harvard, (1978).
Published
2025-07-10
How to Cite
Feta, A. A., & Kamberaj, H. (2025). Impact of Metaverse Technologies Integration on Biotechno-logical Innovation: A Literature Review. European Scientific Journal, ESJ, 43, 15. Retrieved from https://eujournal.org/index.php/esj/article/view/19744
Section
ESI Preprints