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The Use and Importance of Artificial Intelligence in Vaccine Research, Development, and Production | ||
| Archives of Razi Institute | ||
| مقاله 3، دوره 80، شماره 5، آذر و دی 2025، صفحه 1103-1112 اصل مقاله (871.27 K) | ||
| نوع مقاله: Review Article | ||
| شناسه دیجیتال (DOI): 10.66224/ARI.80.5.3442 | ||
| نویسندگان | ||
| Muhammad Yasir Naeem1؛ Batuhan Selamoglu2؛ Koshanova Gulnazira Danebekovna3؛ Mesut Selamoglu4؛ Zeliha Selamoglu* 5 | ||
| 1Department of Agronomy, Animals, Food, Natural Resources and the Environment (DAFNAE), University of Padova, Padova, Italy. | ||
| 2Institute of Science, Electrical and Electronic Engineering, Mersin University, Mersin, Turkey. | ||
| 3Department of Mathematics, Faculty of Sciences, Central Campus, Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkestan, Kazakhstan. | ||
| 4Bahce Vocational School, Osmaniye Korkut Ata University, Management and Organization, Osmaniye, Turkey. | ||
| 5Department of Medical Biology, Faculty of Medicine, Nigde Omer Halisdemir University, Nigde, Turkey. | ||
| چکیده | ||
| Artificial intelligence (AI) refers to a variety of computing approaches, including machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision. AI has transformed healthcare, with applications ranging from diagnostics to personalized medicine, drug development, and clinical trial optimization. The advancement of vaccine creation, research, and manufacturing is being significantly impacted by AI. The integration of AI into vaccine research, development, and production has the potential to revolutionize traditional methodologies, significantly accelerating the process of bringing vaccines to market. This review aims to evaluate the role of AI technologies—such as ML, DL, and NLP—in identifying vaccine targets, optimizing formulations, and streamlining manufacturing processes. AI facilitates the analysis of extensive datasets, enabling predictive analytics that enhance the selection of promising vaccine candidates and improve trial outcomes. Furthermore, AI-driven optimization of supply chains enhances vaccine distribution, particularly in low-resource settings, addressing global disparities in access to immunizations. Despite these advancements, challenges remain, including ethical concerns related to data privacy, algorithmic bias, and the integration of AI into existing frameworks. Future directions point toward advancements in AI technologies, including quantum computing, which could further enhance vaccine development efficiency. Collaboration between AI experts and vaccine researchers is crucial for maximizing the potential of AI and ensuring equitable access to vaccines globally. The vaccination distribution may be optimized by AI-powered logistics systems, guaranteeing that doses are given to the appropriate places at the appropriate times. AI can identify the most effective ways to deliver vaccines, minimizing delays and reducing waste, by analyzing data on transportation routes, storage capacity, and cold chain needs. This review highlights the transformative impact of AI on the vaccine development landscape and underscores its importance in responding to emerging infectious diseases and public health crises. | ||
| کلیدواژهها | ||
| Biopharmaceuticals؛ Computational biology؛ Immune-informatics؛ Machine learning (ML)؛ Predictive analytics | ||
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