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Reference datasets for bioequivalence trials in a two-group parallel design.

Anders Fuglsang1, Helmut Schütz, Detlew Labes

  • 1Fuglsang Pharma, Hiort Lorenzens Vej 6c st. tv., 6100, Haderslev, Denmark, anfu@fuglsangpharma.com.

The AAPS Journal
|December 10, 2014
PubMed
Summary
This summary is machine-generated.

This study provides 11 public datasets for validating bioequivalence trial software. These datasets offer consensus results from six software packages to ensure reliable bioequivalence assessments.

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Area of Science:

  • Pharmacokinetics and Pharmacodynamics
  • Biostatistics
  • Pharmaceutical Software Validation

Background:

  • Software validation is critical for bioequivalence (BE) trials.
  • Standardized datasets are needed to qualify and validate BE software.
  • Existing software may have limitations in handling different statistical assumptions or dataset sizes.

Purpose of the Study:

  • To define datasets with known results for software validation in bioequivalence trials.
  • To provide public domain datasets and consensus results for evaluating bioequivalence software.
  • To establish validation targets for software used in two parallel treatment group BE studies.

Main Methods:

  • Compilation of 11 datasets for bioequivalence trials.
  • Evaluation of datasets using six different software packages: R, SAS, WinNonlin, OpenOffice Calc, Kinetica, and EquivTest.
  • Analysis performed with and without the assumption of equal variances for 90% confidence interval construction.

Main Results:

  • Public release of 11 datasets with proposed consensus results.
  • Identified software limitations regarding unequal variance assumptions and large dataset handling.
  • Observed questionable results from one software package (Kinetica) with unequal group sizes.

Conclusions:

  • The study provides essential resources for bioequivalence software validation.
  • Highlights the need for robust software capable of handling diverse statistical assumptions and data sizes.
  • Proposes specific validation targets to ensure reliable bioequivalence trial evaluations.