International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 11, Issue 6 (June 2024), Pages: 215-228

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 Review Paper

COVID-19 mRNA vaccine degradation rate prediction using artificial intelligence techniques: A narrative review

 Author(s): 

 Hwai Ing Soon 1, 2, Azian Azamimi Abdullah 1, 3, *, Hiromitsu Nishizaki 2, Mohd Yusoff Mashor 1, Latifah Munirah Kamarudin 1, 4, Zeti-Azura Mohamed-Hussein 5, 6, Zeehaida Mohamed 7, Wei Chern Ang 8, 9

 Affiliation(s):

 1Faculty of Electronic Engineering and Technology, Universiti Malaysia Perlis, Arau, Malaysia
 2Integrated Graduate School of Medicine, Engineering, and Agricultural Science, University of Yamanashi, Kofu, Japan
 3Medical Devices and Life Sciences Cluster, Sport Engineering Research Centre, Centre of Excellence, Universiti Malaysia Perlis, Arau, Malaysia
 4Advanced Sensor Technology, Centre of Excellence, Universiti Malaysia Perlis, Arau, Malaysia
 5Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia
 6UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
 7Department of Medical Microbiology Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kelantan, Malaysia
 8Clinical Research Centre, Hospital Tuanku Fauziah, Ministry of Health Malaysia, Perlis, Malaysia
 9Department of Pharmacy, Hospital Tuanku Fauziah, Ministry of Health Malaysia, Perlis, Malaysia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-5851-7705

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.06.023

 Abstract

As diseases become more common, the use of mRNA (messenger ribonucleic acid) vaccines is becoming more important. These vaccines can be developed quickly and have a low risk of side effects. However, they are sensitive to environmental conditions, which means they need careful storage and transport, creating challenges in distributing them. Testing the stability of an mRNA vaccine requires a lot of work and time, as it needs many lab tests. Artificial Intelligence (AI) offers a new solution by using the genetic information in RNA sequences to predict how quickly these vaccines might break down. This approach helps address potential shortages of vaccines by avoiding some of the challenges with vaccine distribution. The COVID-19 pandemic has greatly sped up the use of AI in this area. This change is significant because using AI to predict and improve the stability of mRNA vaccines was not well explored before the pandemic. This paper reviews recent studies that use AI to study mRNA vaccines during the COVID-19 pandemic. It points out that the main issue with these vaccines is how long they can be stored before they are no longer effective due to their sensitivity to environmental conditions. By looking at these studies, the paper not only shows how AI and vaccine research are coming together but also points out opportunities for more research. The goal of this review is to outline effective methods to improve the use of mRNA vaccines and encourage more scientific research and development in this field. This is an important step in improving how we deal with pandemics.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Artificial intelligence, Degradation rate, mRNA vaccines, Environmental sensitivity, COVID-19 pandemic

 Article history

 Received 21 February 2024, Received in revised form 10 June 2024, Accepted 11 June 2024

 Acknowledgment 

The authors gratefully acknowledge funding from the Fundamental Research Grant Scheme (FRGS) funded by the Ministry of Higher Education (MOHE), Malaysia. FRGS/1/2021/TKO/UNIMAP/02/65.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Soon HI, Abdullah AA, Nishizaki H, Mashor MY, Kamarudin LM, Mohamed-Hussein ZA, Mohamed Z, and Ang WC (2024). COVID-19 mRNA vaccine degradation rate prediction using artificial intelligence techniques: A narrative review. International Journal of Advanced and Applied Sciences, 11(6): 215-228

 Permanent Link to this page

 Figures

 Fig. 1 

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5

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