Purpose

The purpose of this paper is to unveil two novel statistical strategies to decide on the acceptability of an analytical and bioanalytical method transfer. These new approaches, namely the uncertainty assessment approach and the risk-based approach, are based on the measurement uncertainty as a decision-making tool.

Methods

At first, we illustrate step by step all the calculations required to construct the maximum tolerated interval and the limits of uncertainty in the transfer phase from a Monte Carlo simulation. Then, we exemplify an original equation to assess the expected risk or probability that a receiving laboratory measurement will fall outside the maximum tolerated interval according to the estimated trueness, fidelity, and uncertainty parameters.

Results

We elucidate the applicability and flexibility of uncertainty approach as well as risk procedure to consider the fitness for purpose of analytical and bioanalytical methods in the transfer phase. We also demonstrate here that our approaches provide guarantees that each future measurement made by the receiving laboratory will be inside the specified acceptance limits.

Conclusion

We show that there is no difference statistically between the decisions taken throughout the analytical transfer by our methodologies and those arising from the accuracy strategies.

中文翻译：

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使用蒙特卡洛模拟和不确定性评估评估分析和生物分析方法转移的新方法

目的

本文的目的是揭示两种新颖的统计策略，以决定分析和生物分析方法转移的可接受性。这些新方法，即不确定性评估方法和基于风险的方法，都基于测量不确定性作为决策工具。

方法

首先，我们一步一步地说明从蒙特卡洛模拟中构造最大容许间隔和转移阶段不确定性极限所需的所有计算。然后，我们举例说明一个原始方程式，以根据估计的真实性，保真度和不确定性参数来评估接收实验室测量值将落在最大容许间隔之外的预期风险或概率。

结果

我们阐明了不确定性方法的适用性和灵活性以及风险程序，以考虑在转移阶段是否适合分析和生物分析方法的目的。在这里，我们还证明了我们的方法可确保接收实验室将来进行的每次测量都将在指定的接受范围内。

结论

我们表明，在整个分析过程中，我们的方法所做出的决策与准确性策略所产生的决策在统计上没有区别。