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The Use and Importance of Artificial Intelligence in Vaccine Research, Development and Production | ||
| Archives of Razi Institute | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 30 فروردین 1404 اصل مقاله (440.85 K) | ||
| نوع مقاله: Review Article | ||
| شناسه دیجیتال (DOI): 10.22092/ari.2025.367895.3442 | ||
| نویسندگان | ||
| Zeliha Selamoglu* 1؛ Muhammad Yasir Naeem2؛ Batuhan Selamoglu3؛ Koshanova Gulnazira Danebekovna4؛ Mesut Selamoglu5 | ||
| 1Nigde Omer Halisdemir University | ||
| 2Department of Agronomy, Animals, Food, Natural Resources and the Environment (DAFNAE), University of Padova, Italy | ||
| 3Mersin University, Institute of Science, Electrical and Electronic Engineering, Mersin, Turkey | ||
| 4Khoja Akhmet Yassawi International Kazakh-Turkish University, Faculty of Sciences, Department of Mathematics, Central Campus, Turkestan, Kazakhstan | ||
| 5Osmaniye Korkut Ata University, Bahce Vocational School, Management and Organization, Osmaniye, Turkey | ||
| چکیده | ||
| Artificial intelligence (AI) refers to a variety of computing approaches, including machine learning, deep learning, natural language processing, and computer vision. AI has transformed healthcare, with applications ranging from diagnostics to personalised medicine, drug development, and clinical trial optimisation. 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 machine learning, deep learning, and natural language processing—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 optimised 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, minimising delays and saving waste, by analysing 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 | ||
| Computational biology؛ machine learning؛ immune-informatics؛ biopharmaceuticals؛ predictive analytics | ||
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آمار تعداد مشاهده مقاله: 192 تعداد دریافت فایل اصل مقاله: 207 |
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