Sophie I E Knahl1, Benjamin Lang1, Frank Fleischer1, Meinhard Kieser2. 1. Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Straße 65, 88397, Biberach, Germany. 2. Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany. meinhard.kieser@imbi.uni-heidelberg.de.
Abstract
PURPOSE: A drug is defined as highly variable if its intra-individual coefficient of variation (CV) is greater than or equal to 30%. In such a case, bioequivalence may be assessed by means of methods that take the (high) variability into account. The Scaled Average Bioequivalence (SABE) approach is such a procedure and represents the recommendations of FDA. The aim of this investigation is to compare the performance characteristics of classical group sequential designs (GSD) and fixed design settings for three-period crossover bioequivalence studies with highly variable drugs, where the SABE procedure is utilized. METHODS: Monte Carlo simulations were performed to assess type I error rate, power, and average sample size for GSDs with Pocock's and O'Brien-Fleming's stopping rules and various timings of the interim analysis and for fixed design settings. RESULTS: Based on our investigated scenarios, the GSDs show comparable properties with regard to power and type I error rate as compared to the corresponding fixed designs. However, due to an advantage in average sample size, the most appealing design is Pocock's approach with interim analysis after 50% information fraction. CONCLUSIONS: Due to their favorable performance characteristics, two-stage GSDs are an appealing alternative to fixed sample designs when assessing bioequivalence in highly variable drugs.
PURPOSE: A drug is defined as highly variable if its intra-individual coefficient of variation (CV) is greater than or equal to 30%. In such a case, bioequivalence may be assessed by means of methods that take the (high) variability into account. The Scaled Average Bioequivalence (SABE) approach is such a procedure and represents the recommendations of FDA. The aim of this investigation is to compare the performance characteristics of classical group sequential designs (GSD) and fixed design settings for three-period crossover bioequivalence studies with highly variable drugs, where the SABE procedure is utilized. METHODS: Monte Carlo simulations were performed to assess type I error rate, power, and average sample size for GSDs with Pocock's and O'Brien-Fleming's stopping rules and various timings of the interim analysis and for fixed design settings. RESULTS: Based on our investigated scenarios, the GSDs show comparable properties with regard to power and type I error rate as compared to the corresponding fixed designs. However, due to an advantage in average sample size, the most appealing design is Pocock's approach with interim analysis after 50% information fraction. CONCLUSIONS: Due to their favorable performance characteristics, two-stage GSDs are an appealing alternative to fixed sample designs when assessing bioequivalence in highly variable drugs.
Entities:
Keywords:
Bioequivalence; Group sequential designs; Highly variable drugs; Two-stage designs
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