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变革实验室实践:全实验室自动化的前沿趋势

Revolutionizing Laboratory Practices: Pioneering Trends in Total Laboratory Automation.

作者信息

Nam Youngwon, Park Hyung-Doo

机构信息

Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Korea.

Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Korea.

出版信息

Ann Lab Med. 2025 Sep 1;45(5):472-483. doi: 10.3343/alm.2024.0581. Epub 2025 Apr 7.

DOI:10.3343/alm.2024.0581
PMID:40190248
Abstract

Total laboratory automation (TLA) is a transformative solution in clinical laboratories that addresses growing demands for operational efficiency, accuracy, and rapid turnaround times in patient care. TLA integrates advanced technologies across pre-analytical, analytical, and post-analytical phases, thereby streamlining workflows, reducing manual intervention, and enhancing QC. TLA adoption is driven by factors such as increasing test volumes, the need for cost reduction and regulatory compliance, and labor shortages. Key benefits of TLA include improved accuracy through error minimization, optimized resource utilization, enhanced staff well-being, and consistent delivery of high-quality results. Leading companies, including Abbott, Roche, Siemens, and Beckman Coulter, dominate the global TLA market with innovative solutions. Recent developments incorporate artificial intelligence (AI), machine learning, robotics, and Internet-of-things technologies, which enable predictive analytics and automated data management. However, challenges remain, including high implementation costs, the need for workforce training, cybersecurity concerns, and system integration complexities. Future trends indicate that TLA will advance through enhanced AI integration, sustainable practices, and big data analytics, fostering continuous improvements in precision diagnostics and clinical outcomes. Moreover, TLA has the potential to revolutionize laboratory operations globally, driving efficiency, accuracy, and sustainability while ultimately improving patient care. Successful adoption of TLA will require strategic planning, interdisciplinary collaboration, and alignment with emerging healthcare needs. In this review, we emphasize that overcoming these challenges through innovation and robust management is essential for ensuring that TLA continues to play a vital role in modern healthcare systems.

摘要

全实验室自动化(TLA)是临床实验室中的一种变革性解决方案,可满足患者护理中对运营效率、准确性和快速周转时间不断增长的需求。TLA整合了分析前、分析中和分析后阶段的先进技术,从而简化工作流程,减少人工干预,并加强质量控制。TLA的采用受到诸如检测量增加、降低成本和合规监管的需求以及劳动力短缺等因素的推动。TLA的主要好处包括通过将误差最小化提高准确性、优化资源利用、提升员工福祉以及持续提供高质量结果。包括雅培、罗氏、西门子和贝克曼库尔特在内的领先公司凭借创新解决方案主导着全球TLA市场。最近的发展纳入了人工智能(AI)、机器学习、机器人技术和物联网技术,这些技术实现了预测分析和自动化数据管理。然而,挑战依然存在,包括高昂的实施成本、对员工培训的需求、网络安全问题以及系统集成复杂性。未来趋势表明,TLA将通过增强AI集成、可持续实践和大数据分析取得进展,促进精准诊断和临床结果的持续改善。此外,TLA有潜力在全球范围内彻底改变实验室运营,提高效率、准确性和可持续性,同时最终改善患者护理。成功采用TLA将需要战略规划、跨学科合作以及与新兴医疗需求保持一致。在本综述中,我们强调通过创新和强有力管理克服这些挑战对于确保TLA在现代医疗系统中继续发挥至关重要的作用至关重要。

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Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.诊断中的人工智能:使用基于手机的读取系统提高尿液检测准确性。
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Advancing Laboratory Medicine Practice With Machine Learning: Swift yet Exact.运用机器学习推动实验室医学实践:快速而精准。
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The Impact of Laboratory Automation on the Time to Urine Microbiological Results: A Five-Year Retrospective Study.实验室自动化对尿液微生物学检测结果报告时间的影响:一项为期五年的回顾性研究
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Quality assurance of add-on testing in plasma samples: stability limit for 29 biochemical analytes.血浆样本中附加测试的质量保证:29 种生化分析物的稳定极限。
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Laboratory Automation in Microbiology: Impact on Turnaround Time of Microbiological Samples in COVID Time.微生物学中的实验室自动化:对新冠疫情期间微生物样本周转时间的影响
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