A Unified Approach for Design and Analysis of Transfer Studies for Analytical Methods
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A Unified Approach for Design and Analysis of Transfer Studies for Analytical Methods Robert Kringle, Richard Khan-Malek, Fred Snikeris, Peter Munden, Christophe Agut and Michel Bauer Drug Information Journal 2001 35: 1271 DOI: 10.1177/009286150103500424 The online version of this article can be found at: http://dij.sagepub.com/content/35/4/1271
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Drug InJormurion J o u m l , Vol. 35, pp. 1271-1288. 2001 Printed in the USA. All rights reserved.
Oo92-8615ROOl Copyright 0 2001 Drug Information Association Inc.
A UNIFIED APPROACH FOR DESIGN AND ANALYSIS OF TRANSFER STUDIES FOR ANALYTICAL METHODS ROBERTKRINGLE,MS, RICHARDKHAN-MALEK, MS, AND FREDSNIKERIS, PHD Biostatistics, Sanofi-Synthelabo Research, Malvern, Pennsylvania
PETER MUNDEN,PHD Analytical Sciences, Sanofi-Synthelabo Research, Malvern, Pennsylvania
CHRISTOPHE AGUT, MS Biostatistics, Sanofi-Synthelabo Recherche, Toulouse, France
MICHELBAUER,PHD Analytical Sciences, Sanofi-Synthelabo Recherche, Toulouse, France
Various approaches are compared for the design and analysis of studies to assess the transfer of an analytical method from a research and development site to one or more other sites: comparison of observed bias and precision to acceptance limits, statistical quality control-type analysis, statistical difference tests, and statistical equivalence tests. These approaches are evaluated in terms of the extent to which the risks of incorrect decisions (consumer risk of failing to detect that a site is unacceptable, and producer risk of rejecting an acceptable site) are known and/or controlled. Comparison of observed accuracy and precision to acceptance limits is a flawed approach because both the consumer and producer risks are unknown and uncontrolled. For technology transfec where the objective is to demonstrate sufSicient acceptability or similarity, the statistical quality control and difference tests are well known to suffer from illogical characteristics (decreasing true acceptance probabilities as the sample size increases). The equivalence test is the preferred approach because it alone controls the more important consumer risk and performs in a scientifically logical manne,: Acceptance limits for accuracy and precision in the equivalence test should be based on need for intended use (ie, ensuring thar good batches will pass, and bad batches will fail, during future release testing and stability testing), and a rigorous method for selection of well-conceived limits is pres
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