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Evaluating manufacturing process profile comparability with multivariate equivalence testing: Case study of cell-culture small scale model transfer

机译:评估制造过程简型与多变量等效测试的可比性:细胞培养小规模模型转移的情况研究

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This article studies the Generalized Mahalanobis Distance (GMD) approach proposed by Hoffelder which measures the dissimilarity of two multivariate Gaussian distributions with arbitrary covariance matrices and unequal sample sizes. This investigation demonstrated that, with appropriate adjustment, the GMD approach can achieve the targeted nominal Type I error and provide sufficient power for testing equivalence between two profile populations. The adjusted GMD approach was applied to examine the equivalence of harvest profiles between a 12L small scale model and 2000L manufacturing scale in a transfer study performed at Sanofi Specialty Care Framingham Biologics. The harvest profiles were evaluated based on three critical parameters (Productivity, Lactate Production, and Total Cell Density) and deemed practically equivalent using a pre-defined equivalence margin per the adjusted GMD approach. (c) 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:187-195, 2018
机译:本文研究了HoffElder提出的广义mahalanobis距离(GMD)方法,该方法采用任意协方差矩阵和不等样本尺寸的两个多变量高斯分布的不同。 本研究表明,通过适当的调整,GMD方法可以实现目标标称I型错误,并为两个概要填充之间的测试等效提供足够的电力。 适用于调整后的GMD方法来检查在Sanofi特种护理弗拉姆生物制剂的转移研究中12L小规模模型和2000L制造规模之间的收获剖面等同物。 基于三个关键参数(生产率,乳酸生产和总细胞密度)评估收获型材,并使用根据调整后的GMD方法使用预定义的等效余量来视为实际等效。 (c)2017美国化学工程师生物科技学院。 Prog。,34:187-195,2018

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