COVID-19 mRNA vaccine degradation rate prediction using artificial intelligence techniques: A narrative review
Authors:   Faculty of Electronic Engineering and Technology, Universiti Malaysia Perlis, Arau, Malaysia, Soon Hwai Ing ,   Integrated Graduate School of Medicine, Engineering, and Agricultural Science, University of Yamanashi, Kofu, Japan, Abdullah Azian Azamimi ,   Faculty of Electronic Engineering and Technology, Universiti Malaysia Perlis, Arau, Malaysia,   Medical Devices and Life Sciences Cluster, Sport Engineering Research Centre, Centre of Excellence, Universiti Malaysia Perlis, Arau, Malaysia, Nishizaki Hiromitsu ,   Integrated Graduate School of Medicine, Engineering, and Agricultural Science, University of Yamanashi, Kofu, Japan, Mashor Mohd Yusoff ,   Faculty of Electronic Engineering and Technology, Universiti Malaysia Perlis, Arau, Malaysia, Kamarudin Latifah Munirah ,   Faculty of Electronic Engineering and Technology, Universiti Malaysia Perlis, Arau, Malaysia,   Advanced Sensor Technology, Centre of Excellence, Universiti Malaysia Perlis, Arau, Malaysia, Mohamed-Hussein Zeti-Azura ,   Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia,   UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia, Mohamed Zeehaida ,   Department of Medical Microbiology Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kelantan, Malaysia, Ang Wei Chern ,   Clinical Research Centre, Hospital Tuanku Fauziah, Ministry of Health Malaysia, Perlis, Malaysia,   Department of Pharmacy, Hospital Tuanku Fauziah, Ministry of Health Malaysia, Perlis, Malaysia
Published: July 2024

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.