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Regression analysis on serial dilution data from virus validation robustness studies

机译:来自病毒验证稳健性研究的系列稀释数据的回归分析

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摘要

To ensure the safety of plasma-derived medicinal products, the Dutch Blood Supply Foundation (Sanquin) performs virus validation experiments. Data from these experiments are based on serial dilution assays. Regression analysis on assay data faces several problems: only a small number of data points are available, data contain censoring and are subject to sampling error. Furthermore, the process variability inherent to the experiments is not evident. In this paper we address these problems by introducing a regression model for serial dilution data and by analyzing how validation experiments and simulation techniques can help elucidate various sources of variability the experiments are subject to. These are then incorporated into the regression model.
机译:为了确保血浆药物的安全,荷兰血液供应基金会(Sanquin)进行了病毒验证实验。这些实验的数据基于连续稀释测定法。对化验数据的回归分析面临几个问题:只有少量数据点可用,数据包含检查且容易出现抽样误差。此外,实验固有的过程可变性也不明显。在本文中,我们通过引入系列稀释数据的回归模型并分析验证实验和模拟技术如何帮助阐明实验所受的各种变异性来源,来解决这些问题。然后将这些合并到回归模型中。

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