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Biobanks, repositories of biological samples and associated data, are crucial for advancing our understanding of disease biology. They facilitate long-term sample storage while enabling efficient retrieval for research. However, traditional biobanking practices often struggle to maintain sample quality and uniformity due to repetitive handling and temperature fluctuations during storage and retrieval. The advent of high-throughput “-omics” technologies has further amplified the operational demands on biobanks, necessitating increased scale and agility. Automation offers a solution to these challenges, enabling biobanks to meet the demands of modern research while preserving sample integrity. This review explores the key considerations for establishing an automated biobank, including design principles, essential components, and integration strategies. We discuss various automated storage and retrieval systems, liquid handling platforms, and environmental monitoring tools. Furthermore, we examine the impact of automation on sample quality, data management, and overall biobank efficiency. This review aims to provide a comprehensive overview of automated biobanking, highlighting its potential to revolutionize research and personalized medicine.
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