Suppr超能文献

免疫测定中的批次间差异——原因、后果及解决方案。

Lot-to-Lot Variance in Immunoassays-Causes, Consequences, and Solutions.

作者信息

Luo Yunyun, Pehrsson Martin, Langholm Lasse, Karsdal Morten, Bay-Jensen Anne-Christine, Sun Shu

机构信息

Biomarkers and Research, Nordic Bioscience, 2730 Herlev, Denmark.

出版信息

Diagnostics (Basel). 2023 May 24;13(11):1835. doi: 10.3390/diagnostics13111835.

Abstract

Immunoassays, which have gained popularity in clinical practice and modern biomedical research, play an increasingly important role in quantifying various analytes in biological samples. Despite their high sensitivity and specificity, as well as their ability to analyze multiple samples in a single run, immunoassays are plagued by the problem of lot-to-lot variance (LTLV). LTLV negatively affects assay accuracy, precision, and specificity, leading to considerable uncertainty in reported results. Therefore, maintaining consistency in technical performance over time presents a challenge in reproducing immunoassays. In this article, we share our two-decade-long experience and delve into the reasons for and locations of LTLV, as well as explore methods to mitigate its effects. Our investigation identifies potential contributing factors, including quality fluctuation in critical raw materials and deviations in manufacturing processes. These findings offer valuable insights to developers and researchers working with immunoassays, emphasizing the importance of considering lot-to-lot variance in assay development and application.

摘要

免疫测定法在临床实践和现代生物医学研究中越来越受欢迎,在定量生物样品中的各种分析物方面发挥着越来越重要的作用。尽管免疫测定法具有高灵敏度和特异性,以及能够在一次运行中分析多个样品的能力,但它仍受到批次间差异(LTLV)问题的困扰。LTLV对测定的准确性、精密度和特异性产生负面影响,导致报告结果存在相当大的不确定性。因此,随着时间的推移保持技术性能的一致性是免疫测定法重现性面临的一个挑战。在本文中,我们分享了我们长达二十年的经验,深入探讨了LTLV产生的原因和位置,并探索减轻其影响的方法。我们的调查确定了潜在的促成因素,包括关键原材料的质量波动和制造过程中的偏差。这些发现为从事免疫测定法的开发人员和研究人员提供了有价值的见解,强调了在测定法开发和应用中考虑批次间差异的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/52f8/10252387/c85b0ddeead0/diagnostics-13-01835-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验