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Comparing a Bayesian Approach (BEST) with the Two One-Sided t-Tests (TOSTs) for Bioequivalence Studies.

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  • 1NDA Partners, a ProPharma Group Company, Washington, DC, USA. ccpeck@icloud.com.

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Summary
This summary is machine-generated.

The Bayesian alternative (BEST) more accurately assesses bioequivalence (BE) than the standard two one-sided t-tests (TOST), especially with non-lognormal or extreme data, requiring fewer subjects.

Keywords:
ANDAcredible intervalextreme valuesgeometric mean ratiotwo-way crossover study

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Area of Science:

  • Pharmacokinetics and Drug Development
  • Statistical Methods in Clinical Trials
  • Regulatory Science

Background:

  • The two one-sided t-tests (TOST) is the regulatory standard for evaluating average bioequivalence (BE).
  • TOST's performance may be suboptimal when bioequivalence data deviate from lognormal distributions or include extreme values.
  • A Bayesian approach, BEST, offers an alternative using a posterior distribution potentially more reflective of observed data.

Purpose of the Study:

  • To compare the performance of TOST and the Bayesian BEST procedure for assessing bioequivalence.
  • To evaluate the accuracy and efficiency of both methods under various data conditions, including non-lognormal and extreme values.
  • To determine if BEST offers advantages over TOST in specific bioequivalence assessment scenarios.

Main Methods:

  • Simulated datasets of test/reference ratios (T/R) were generated to represent bioequivalent (BE) and not-BE (NBE) scenarios.
  • Data distributions included normal and lognormal for log(T/R) or T-R, with sample sizes from 10 to 50.
  • Extreme values were randomly included in datasets to mimic real-world variability.
  • The 90% confidence interval (CI) from TOST was compared with the 90% credible interval (CrI) from BEST.

Main Results:

  • Both TOST and BEST agreed on bioequivalence for lognormal T/R data without extreme values.
  • BEST demonstrated higher accuracy in classifying BE/NBE and required fewer subjects when data (log(T/R) or T-R) were normal and contained extreme values.
  • TOST may disadvantage applicants when T/R data are not lognormal or include extreme values, leading to different assessment outcomes compared to BEST.

Conclusions:

  • BEST is a robust alternative to TOST for bioequivalence assessment, particularly when data are not lognormal or contain extreme values.
  • BEST can provide more accurate bioequivalence assessments with potentially fewer subjects in challenging data scenarios.
  • The application of BEST to bioequivalence data warrants consideration for efficient drug formulation development and regulatory evaluation.