VACCINE TARGET OPTIMISATION AND DEVELOPMENT: THE ROLE OF MACHINE LEARNING
ALGORITHMS AND EMERGING AI TECHNOLOGIES
CHUKWUEMEKA SYLVESTER NWORU1,3,*, RUPHIN KUSINZA BYAMUNGU2 , THIERRY
MUGENZI4
- Department of Pharmacology & Toxicology, Faculty of Pharmaceutical Sciences, University of Nigeria,
Nsukka, Nigeria
- Department of Cybersecurity, Faculty of Computing & Sciences, Olivia University, Bujumbura, Burundi
- Faculty of Pharmaceutical Sciences, Olivia University, Bujumbura, Burundi
- Department of Artificial Intelligence, Faculty of Computing & Sciences, Olivia University, Bujumbura, Burundi
Afr. J Pharm Res Dev; Volume 15(1): 32-48; 2023
ABSTRACT
Vaccines are significant advancements in modern medicine, preventing numerous life-threatening diseases. Their development is a complex, multidisciplinary process involving antigen identification, production, preclinical testing, human clinical trials, regulatory approval, large-scale manufacturing, and distribution to target populations. However, vaccine development is expensive and has a high failure rate. This situation is further complicated by pathogen mutations, which can reduce vaccine effectiveness. This review examines the application of machine learning algorithms (MLA) and artificial intelligence (AI) in vaccine development, with a focus on identifying optimal vaccine targets and the significance of employing advanced technologies for the rapid production of effective vaccines against existing and emerging infectious diseases. The review process involved searching various academic databases such as PubMed, ScienceDirect, and Google Scholar, using a combination of keywords and Boolean operators to find relevant articles related to vaccine target optimization and development that utilized machine learning algorithms and emerging AI technologies and appraising relevant studies to provide a comprehensive summary of the available evidence. It was discovered that incorporating machine learning algorithms and artificial intelligence has the potential to expedite and enhance vaccine development and rollout. AI facilitates the proficient analysis of extensive data sets, identifying patterns that might be missed by conventional methods. By scrutinizing the genomic data of pathogens, AI assists in pinpointing potential antigen targets for vaccine development. This results in creating more effective vaccines against specific strains or variants, accelerating the process. Targeted and efficient vaccine development is crucial during pandemics or when new infectious diseases emerge. Moreover, AI technologies can predict the potential effectiveness of vaccine candidates, detect side effects and adverse events, guarantee safety, and optimize dosage regimens. The application of AI in vaccine design and development offers several benefits but also presents several ethical considerations and challenges. In summary, MLA and other AI technologies can substantially improve vaccine target optimization, expedite development, and enhance the accuracy and speed of target selection, antigen design, and clinical trial optimization.
Email of correspondence: chukwuemeka.nworu@oliviauniversity.com
KEYWORDS: Antigen selection, Artificial intelligence, Epitope optimization, Machine learning algorithms,
Vaccines development