传输稳定性分析-提议的通用协议

Lars Willems, M. Paal, M. Vogeser
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摘要

摘要目的诊断样品在运输到实验室期间暴露于一系列变量;因此,评估相当全面的稳定性概况措施是必要的。虽然已经为药品和试剂建立了适当的检测标准,但诊断样品的情况并非如此。我们工作的目的是制定和评估适用于诊断样本的方案。方法建立温度和暴露时间在二维矩阵中表示的等时方法。根据所应用的分析测量程序的测量不确定度,评估与暴露有关的测量结果与基线的偏差。实验变量记录在标准化矩阵中。作为概念验证,我们在初级血清样管中分析了在四个温度水平下长达72小时的许多测量的稳定性模式。结果该方案被证明是可行的,并允许基于从每个志愿者收集并根据该方案暴露的21个小体积初级样品的相当数量的化合物的综合稳定性概况的描述。结论一种简单可行的同步方案可用于详细研究不同预处理条件对初级样品在运往诊断实验室过程中测量稳定性的影响。随着分析服务的集中化,分析前物流变得越来越重要,这一点具有重要意义。
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Transport stability profiling – a proposed generic protocol
Abstract Objectives Diagnostic samples are exposed to a spectrum of variables during transport to laboratories; therefore, the evaluation of a rather comprehensive stability profile of measurands is warranted. While appropriate testing standards have been established for pharmaceuticals and reagents, this is not the case for diagnostic samples. The aim of our work was to develop and evaluate a protocol applicable to diagnostic samples. Methods An isochronous approach with representation of temperature and exposure duration in a two-dimensional matrix was established. The deviations of the measurement results from the baseline associated with the exposure are evaluated with respect to the measurement uncertainty of the analytical measurement procedure applied. Variables of the experiment are documented in a standardized matrix. As a proof-of-concept, we profiled the stability patterns of a number of measurands at four temperature levels over up to 72 h in primary serum sample tubes. Results The protocol proved to be workable and allowed the description of a comprehensive stability profile of a considerable number of compounds based on 21 small-volume primary samples collected from each volunteer and exposed according to this protocol. Conclusions A straightforward and feasible isochronous protocol can be used to investigate in detail the effects of different pre-processing conditions on the stability of measurands in primary samples during transport to diagnostic laboratories. This is of significance as pre-analytical logistics become increasingly important with the centralization of analytical services.
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