THE IMPORTANCE OF USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR THE DEVELOPMENT OF THE COVID-19 VACCINE: AN INTEGRATIVE REVIEW
DOI:
https://doi.org/10.66104/ygs1p812Keywords:
Artificial intelligence, Machine learning, Coronavirus vaccineAbstract
The COVID-19 pandemic demanded rapid scientific responses, driving the use of Artificial Intelligence (AI) and Machine Learning (ML) in vaccine development. This study consists of an integrative literature review aimed at analyzing the importance, safety, and role of these technologies in the COVID-19 vaccination process. The search was conducted in the BVS, SciELO, and Google Scholar databases, including articles published between 2020 and 2025. The results show that AI and ML contributed to accelerating research and development stages, optimizing genetic sequences, identifying molecular targets, and adapting to viral variants, in addition to supporting safety and logistics analyses. Despite the advances, ethical, technical, and regulatory challenges persist, especially related to data quality, algorithmic biases, and privacy protection. It is concluded that AI and ML represent strategic tools for innovation in vaccinology and for strengthening the response to future health emergencies.
Downloads
References
ANDRÉ, S.; RIBEIRO, P. E-health: as TIC como mecanismo de evolução em saúde. Gestão e Desenvolvimento, n. 28, p. 95–116, jul. 2020.
AHUJA, A. S. et al. Inteligência artificial e COVID-19: uma abordagem multidisciplinar. Integrative Medicine Research, 2020. DOI: 10.1016/j.imr.2020.100434.l0
ASEDIYA, V. S. et al. Vaccine development using artificial intelligence and machine learning: a review. International Journal of Biological Macromolecules, v. 282, p. 136643, 2024. DOI: https://doi.org/10.1016/j.ijbiomac.2024.136643
BHATTACHARYA, M. et al. Uma nova vacina de próxima geração à prova de mutações para SARS-CoV-2. International Journal of Biological Macromolecules, v. 242, p. 124893, 2023. DOI: 10.1016/j.ijbiomac.2023.124893. DOI: https://doi.org/10.1016/j.ijbiomac.2023.124893
BRAGA, Tiago Moraes et al. O uso de inteligência artificial na interpretação de exames médicos. Brazilian Journal of Health Review, v. 7, n. 3, p. e70932-e70932, 2024. DOI: https://doi.org/10.34119/bjhrv7n3-507
CHAR, D. S. et al. Identifying ethical considerations for machine learning healthcare applications. American Journal of Bioethics, v. 20, n. 11, p. 7-17, 2020. DOI: 10.1080/15265161.2020.1819469. DOI: https://doi.org/10.1080/15265161.2020.1819469
CHEN, B. et al. Previsão da apresentação de antígenos HLA de classe II por aprendizado profundo. Nature Biotechnology, v. 37, p. 1332-1343, 2019. DOI: 10.1038/s41587-019-0280-2. DOI: https://doi.org/10.1038/s41587-019-0280-2
Chen J., Wei GW. Projeto de inteligência artificial matemática de anticorpos monoclonais à prova de mutação contra COVID-19. Commun. Inf. Syst. 2022;22(3):339–361. doi: 10.4310/cis.2022.v22.n3.a3. DOI: https://doi.org/10.4310/CIS.2022.v22.n3.a3
COREY, L. et al. A strategic approach to COVID-19 vaccine R&D. Science, v. 368, n. 6494, p. 948-950, 2020. DOI: https://doi.org/10.1126/science.abc5312
CRUZ, A. A queda da imunização no Brasil. Consensus, v. 25, p. 20-29, 2017.EMA. Inteligência artificial. Disponível em:https://www.ema.europa.eu/en/about-us/how-we-work/big-data/artificial-intelligence. Acesso em: 8 jan. 2026.
El Arab RA, Alkhunaizi M, Alhashem YN, Al Khatib A, Bubsheet M, Hassanein S. Artificial intelligence in vaccine research and development: an umbrella review. Front Immunol. 2025 May 8;16:1567116. doi: 10.3389/fimmu.2025.1567116. DOI: https://doi.org/10.3389/fimmu.2025.1567116
FLORIDI, L. et al. How to design AI for social good: seven essential factors. Science and Engineering Ethics, v. 26, n. 3, p. 1771-1796, 2020. DOI: 10.1007/s11948-020-00213-5. DOI: https://doi.org/10.1007/s11948-020-00213-5
GOECKS, J. et al. How machine learning will transform biomedicine. Cell, v. 181, n. 1, p. 92-101, 2020. DOI: https://doi.org/10.1016/j.cell.2020.03.022
Hasanzadeh A, Hamblin MR, Kiani J, Noori H, Hardie JM, Karimi M, et al. A inteligência artificial poderia revolucionar o desenvolvimento de nanovetores para terapia gênica e vacinas de mRNA? Nano Today. (2022) 47:101665. doi: 10.1016/J.NANTOD.2022.101665. DOI: https://doi.org/10.1016/j.nantod.2022.101665
KAUSHIK, R. et al. Inteligência artificial na aceleração do desenvolvimento de vacinas. Frontiers in Bacteriology, v. 2, p. 1258159, 2023. DOI: 10.3389/fbrio.2023.1258159. DOI: https://doi.org/10.3389/fbrio.2023.1258159
KING, M. H.; MARTODIPOERO, S. Health microplanning in the developing countries: a systems approach to appropriate technology. International Journal of Health Services, v. 8, n. 4, p. 653–664, 1978.
KONG, W. H. et al. SARS-CoV-2 detection in patients with influenza-like illness. Nature Microbiology, v. 5, n. 5, p. 675-678, 2020. DOI: 10.1038/s41564-020-0713-1. DOI: https://doi.org/10.1038/s41564-020-0713-1
KRAMMER, F. SARS-CoV-2 vaccines in development. Nature, v. 586, p. 516-527, 2020. DOI: https://doi.org/10.1038/s41586-020-2798-3
LESLIE, D. et al. IA na luta contra a COVID-19: avanços e desafios. Nature Machine Intelligence, 2021.
MINSSEN, T. et al. Regulatory responses to medical machine learning. Journal of Law and the Biosciences, v. 7, n. 1, lsaa002, 2020. DOI: 10.1093/jlb/lsaa002. DOI: https://doi.org/10.1093/jlb/lsaa002
OLAWADE, D. B. et al. Leveraging artificial intelligence in vaccine development. Journal of Microbiological Methods, v. 224, p. 106998, 2024. DOI: https://doi.org/10.1016/j.mimet.2024.106998
ORGANIZAÇÃO MUNDIAL DA SAÚDE. Estudo global sobre as origens do SARS-CoV-2. Genebra: OMS, 2021.
PATEL, S. J. et al. Artificial intelligence enabled rapid development of COVID-19 vaccines. Expert Opinion on Drug Discovery, 2021. DOI: 10.1080/17460441.2021.1882788.
POLACK, F. P. et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine. New England Journal of Medicine, v. 383, p. 2603-2615, 2020.
PORTNOY, A.; JIT, M.; HELLERINGER, S.; VERGUET, S. Impact of measles supplementary immunization activities on reaching children missed by routine programs. Vaccine, v. 36, n. 1, p. 170–178, 2018.
RAMOS, Maíra Catharina et al. Big Data e Inteligência Artificial para pesquisa translacional na Covid-19: revisão rápida. Saúde em Debate,v.46,p.1202-1214,2023. https://doi.org/10.1590/0103-1104202213518 DOI: https://doi.org/10.1590/0103-1104202213518
SATO, A. P. S. Pandemic and vaccine coverage: challenges of returning to schools. Revista de Saúde Pública, v. 54, p. 115, 2020. DOI: https://doi.org/10.11606/s1518-8787.2020054003142
SCANNELL, J. W. et al. Diagnosing the decline in pharmaceutical R&D efficiency. Nature Reviews Drug Discovery, v. 11, n. 3, p. 191-200, 2012. DOI: 10.1038/nrd3681. DOI: https://doi.org/10.1038/nrd3681
SCHWAB, K. A quarta revolução industrial. São Paulo: Edipro, 2016.
THAKKAR, S. et al. Inteligência artificial e dados reais para segurança de medicamentos. Regulatory Toxicology and Pharmacology, v. 140, p. 105388, 2023.
TIAN, Yuan et al. Imunologia de célula única da infecção por SARS-CoV-2. Nature biotechnology , v. 40, n. 1, p. 30-41, 2022.
TOPOL, E. J. High-performance medicine. Nature Medicine, v. 25, p. 44-56, 2019. DOI: https://doi.org/10.1038/s41591-018-0300-7
Zhang WY, Zheng XL, Coghi PS, Chen JH, Dong BJ, Fan XX. Revolucionando o desenvolvimento de adjuvantes: aproveitando a IA para vacinas contra o câncer de próxima geração. Front Immunol. (2024) 15:1438030/BIBTEX. doi: 10.3389/FIMMU.2024.1438030/BIBTEX.
ZHAVORONKOV, A. Artificial intelligence for drug discovery. Molecular Pharmaceutics, v. 15, n. 10, p. 4311-4317, 2018. DOI: 10.1021/acs.molpharmaceut.8b00930. DOI: https://doi.org/10.1021/acs.molpharmaceut.8b00930
ZHOU, P. et al. A pneumonia outbreak associated with new coronavirus of bat origin. Nature, v. 579, n. 7798, p. 270-273, 2020. DOI: 10.1038/s41586-020-2012-7. DOI: https://doi.org/10.1038/s41586-020-2012-7
FDA. Utilizando inteligência artificial e aprendizado de máquina no desenvolvimento de medicamentos. 2023. Disponível em: https://www.fda.gov/media/167973/download.
GOODSWEN, S. J. et al. Um guia para vacinologia reversa na descoberta de vacinas in silico. FEMS Microbiology Reviews, v. 47, n. 2, 2023. DOI: 10.1093/femsre/fuad004. DOI: https://doi.org/10.1093/femsre/fuad004
GUIMARÃES, L. E. et al. Vacinas, adjuvantes e autoimunidade. Pharmacological Research, v. 100, p. 190-209, 2015. DOI: 10.1016/j.phrs.2015.08.003. DOI: https://doi.org/10.1016/j.phrs.2015.08.003
KING, M. H.; MARTODIPOERO, S. Health microplanning in the developing countries. International Journal of Health Services, v. 8, n. 4, p. 653-664, 1978. DOI: https://doi.org/10.2190/ATDG-DLRW-UCKU-1RLF
MAZZOCCO, G. et al. Projeto auxiliado por IA de vacina baseada em epítopos para SARS-CoV-2. Frontiers in Genetics, v. 12, 2021. DOI: 10.3389/fgene.2021.602196. DOI: https://doi.org/10.3389/fgene.2021.602196
MARENGO, L. L. et al. Tecnologias móveis em saúde: reflexões sobre desenvolvimento, aplicações, legislação e ética. Revista Panamericana de Salud Pública, v. 46, 2022. DOI: https://doi.org/10.26633/RPSP.2022.37
Mohammad, S., & Maryam, M. (2023). The Role of Artificial Intelligence in the Development of COVID-19 Vaccine. International journal of preventive medicine, 14, 97. https://doi.org/10.4103/ijpvm.ijpvm_333_21. DOI: https://doi.org/10.4103/ijpvm.ijpvm_333_21
NICHIATA, L. Y. I.; PASSARO, T. E-health e saúde pública: a presença digital do Sistema Único de Saúde do Brasil por meio de aplicativos de dispositivos móveis. Revista Eletrônica de Comunicação, Informação & Inovação em Saúde, [S. l.], v. 17, n. 3, 2023. DOI: https://doi.org/10.29397/reciis.v17i3.3663
ONG, E.; HE, Y. Desenvolvimento de vacinas por vacinologia reversa e machine learning. Methods in Molecular Biology, v. 2414, p. 1-16, 2022.
PORTNOY, A. et al. Impact of measles supplementary immunization activities. Vaccine, v. 36, n. 1, p. 170-178, 2018. DOI: https://doi.org/10.1016/j.vaccine.2017.10.080
WALTZ, Emily. AI takes its best shot: what AI can—and can't—do in the race for a coronavirus vaccine-[vaccine]. IEEE Spectrum, v. 57, n. 10, p. 24-67, 2020. DOI: 10.1109/MSPEC.2020.9205545. DOI: https://doi.org/10.1109/MSPEC.2020.9205545
Wang R., et al. Variantes emergentes do SARS-CoV-2 que superam a resistência à vacina. ACS Infect Dis. 2022;8(3):546–556. doi: 10.1021/acsinfecdis.1c00557 DOI: https://doi.org/10.1021/acsinfecdis.1c00557
LIBIDIBIA FERREA: UMA REVISÃO ABRANGENTE E POTENCIAIS APLICAÇÕES DE DIFERENTES EXTRATOS DE JUCÁ. (2026). Revista Multidisciplinar Do Nordeste Mineiro, 1(03), 1-38. https://doi.org/10.61164/xq4dqy35 DOI: https://doi.org/10.61164/xq4dqy35
A PROPOSAL FOR TEACHING METRIC RELATIONS IN RIGHT TRIANGLES. (2026). Revista Multidisciplinar Do Nordeste Mineiro, 2(01), 1-17. https://doi.org/10.61164/trsscq72 DOI: https://doi.org/10.61164/trsscq72
O AMBIENTE E OS INSTRUMENTOS DE MEDIDAS PARA AVALIAR O DESENVOLVIMENTO MOTOR DE CRIANÇAS E ADOLESCENTES: UM ESTUDO DE REVISÃO. (2026). Revista Multidisciplinar Do Nordeste Mineiro, 2(01), 1-12. https://doi.org/10.61164/cbk44936 DOI: https://doi.org/10.61164/cbk44936
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Agnaldo da Silva Carneiro, Noemi Isabelle Alves Monteiro, Vanessa Regina Silva Mota, Lucas Piani Corrêa , Cibelhe Mayara Silva, Alessandro Quaresma Durães de Sousa

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish in this journal agree to the following terms:
Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under the Creative Commons Attribution License, which permits the sharing of the work with proper acknowledgment of authorship and initial publication in this journal;
Authors are authorized to enter into separate, additional agreements for the non-exclusive distribution of the version of the work published in this journal (e.g., posting in an institutional repository or publishing it as a book chapter), provided that authorship and initial publication in this journal are properly acknowledged, and that the work is adapted to the template of the respective repository;
Authors are permitted and encouraged to post and distribute their work online (e.g., in institutional repositories or on their personal websites) at any point before or during the editorial process, as this may lead to productive exchanges and increase the impact and citation of the published work (see The Effect of Open Access);
Authors are responsible for correctly providing their personal information, including name, keywords, abstracts, and other relevant data, thereby defining how they wish to be cited. The journal’s editorial board is not responsible for any errors or inconsistencies in these records.
PRIVACY POLICY
The names and email addresses provided to this journal will be used exclusively for the purposes of this publication and will not be made available for any other purpose or to third parties.
Note: All content of the work is the sole responsibility of the author and the advisor.
