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Related Concept Videos

Bioequivalence Data: Statistical Interpretation01:16

Bioequivalence Data: Statistical Interpretation

The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...
Bioequivalence of Drugs: Drugs with Multiple Indications01:09

Bioequivalence of Drugs: Drugs with Multiple Indications

The concept of therapeutic equivalence (TE) in drugs with multiple indications is complex. A generic drug may be therapeutically equivalent to a brand-name product for one specific indication, but this doesn't necessarily mean it's equivalent for all other indications. Evidence of TE in one patient group and bioequivalence shown in healthy volunteers can support—but not confirm—TE for other indications. However, definitive proof requires individual clinical studies for each indication due to...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Bioequivalence: Overview01:16

Bioequivalence: Overview

Pharmaceutical equivalents, by definition, are drug products with the same active ingredient in the same quantities, encapsulated in identical dosage forms, and intended for the same administration routes. These pharmaceutical equivalents are deemed bioequivalent if the bioavailability of the active entity in the drug preparations is similar. Moreover, pharmaceutical equivalents demonstrating bioequivalence are also regarded as therapeutically equivalent. This means that when used as directed,...
Bioequivalence studies: Biowaivers01:13

Bioequivalence studies: Biowaivers

In certain scenarios, in vitro dissolution tests can replace in vivo bioequivalence studies. This is particularly true when a drug product, though available in varying strengths, maintains proportional similarity in its active and inactive ingredients. In such cases, the need for in vivo bioequivalence studies for lower strength variants may be waived, provided dissolution tests and in vivo studies on the highest strength yield satisfactory results.Bioequivalence can be indicated through...

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Testing bioequivalence for multiple formulations with power and sample size calculations.

Cheng Zheng1, Jixian Wang, Lihui Zhao

  • 1Novartis Pharmaceuticals Corp., One Health Plaza, East Hanover, NJ, USA. zhengcheng@gmail.com

Pharmaceutical Statistics
|June 14, 2012
PubMed
Summary

Testing multiple drug formulations simultaneously in bioequivalence (BE) trials is efficient. The multiplicity-adjusted two one-sided tests (MATOST) method requires only a small increase in sample size compared to single-formulation trials.

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Area of Science:

  • Pharmacokinetics and Drug Development
  • Biostatistics
  • Regulatory Science

Background:

  • Bioequivalence (BE) trials are crucial for drug development, ensuring therapeutic equivalence between test and reference formulations.
  • The standard statistical analysis involves two one-sided tests (TOST), assessing if the 90% confidence interval for relative bioavailability falls within specified limits.
  • Existing methods for power and sample size calculations are well-established for single test formulations but less so for multiple formulations.

Purpose of the Study:

  • To propose and evaluate a novel statistical method, multiplicity-adjusted TOST (MATOST), for simultaneous BE testing of multiple formulations.
  • To develop and implement simulation-based procedures for power and sample size calculations in MATOST.
  • To assess the efficiency of simultaneous multi-formulation BE trials compared to traditional single-formulation trials.

Main Methods:

  • Development of the MATOST method, integrating multiple comparison adjustment techniques (e.g., Hochberg's, Dunnett's) with TOST.
  • Implementation of simulation-based power and sample size calculation procedures using an R package.
  • Numerical evaluation of MATOST across various scenarios to compare sample sizes and error rates.

Main Results:

  • MATOST effectively controls the overall type I error rate when testing multiple formulations simultaneously.
  • Simulation-based procedures provide reliable power and sample size estimations for MATOST.
  • Simultaneous multi-formulation BE trials require only a modest increase in total sample size compared to single-formulation trials, while maintaining equivalent statistical power and type I error control.

Conclusions:

  • Simultaneous testing of multiple formulations in a single bioequivalence trial is a statistically sound and logistically efficient approach.
  • The MATOST method and its associated R package offer practical tools for designing such trials.
  • This strategy can lead to resource savings and accelerated drug development timelines.