Ghosh, A.; Larrondo-Petrie, M.M.; Pavlovic, M. Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches. Information2023, 14, 665.
Ghosh, A.; Larrondo-Petrie, M.M.; Pavlovic, M. Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches. Information 2023, 14, 665.
Ghosh, A.; Larrondo-Petrie, M.M.; Pavlovic, M. Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches. Information2023, 14, 665.
Ghosh, A.; Larrondo-Petrie, M.M.; Pavlovic, M. Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches. Information 2023, 14, 665.
Abstract
AI-based approaches are increasingly being used to revolutionize vaccine development for COVID-19. Small molecules, peptides, and epitopes are being collected for therapy discovery, which could also direct AI-based models, screening, or generation [1]. AI-based models are being used for drug discovery and vaccine development, and pre-existing data is being leveraged through machine learning approaches for COVID-19 drug discovery and vaccine development [1]. The best candidate targets for future treatment development are being identified and evaluated using AI-based models [1]. AI-based approaches can be used to overcome challenges in manufacturing, storage, logistics, and safety and efficacy issues related to different vaccine candidates for COVID-19 [2]. AI algorithms can help identify the best vaccine candidates for COVID-19 while considering the efficiency of antigenic peptides for immune response generation [2]. The presentation of antigenic peptides by major histocompatibility complex (MHC) class II molecules is the first step after COVID-19 vaccine administration for any vaccine-induced immune response [2]. Thus, AI-based models are being used to identify the best vaccine candidates for COVID-19 and to ensure that the vaccine-induced immune response is efficient and safe. The utilization of AI-based methods to address logistical, manufacturing, storage, safety, and efficacy issues regarding several COVID-19 vaccine candidates will be examined in this study. Additionally, while considering the effectiveness of antigenic peptides for the induction of an immune response, we will determine the best potential targets for the next treatment development and assess how AI-based models can help discover the best vaccine candidates for COVID-19. This research ultimately intends to offer insights into how AI-based techniques can transform COVID-19 vaccine development and how they can be applied to address vaccine development issues. In this paper, we focus on recent advances in using artificial intelligence to develop COVID-19 drugs and vaccines, as well as the potential of intelligent training in discovering COVID-19 therapeutics, highlighting potential challenges and solutions.
Keywords
COVID-19; AI-based approach; vaccine development
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
