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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...
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Related Experiment Video

Updated: May 13, 2026

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Biomarker-driven basket trial designs: origins and new methodological developments.

Yue Tu1, Lindsay A Renfro2

  • 1Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California, USA.

Journal of Biopharmaceutical Statistics
|June 4, 2024
PubMed
Summary

This review explores basket trials for precision medicine, examining traditional designs, challenges, and novel Bayesian and Frequentist adaptations for molecularly-driven cancer therapies.

Keywords:
Basket trialbiomarker trial designclinical trialprecision medicine

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Area of Science:

  • Oncology
  • Biostatistics
  • Clinical Trial Design

Background:

  • Advances in gene sequencing have deepened the molecular understanding of cancer, impacting diagnosis and treatment response assessment.
  • Precision medicine aims to tailor treatments using molecularly-driven interventions and predictive biomarkers.
  • Basket trials are a key design for evaluating targeted therapies across various cancer types irrespective of tumor location.

Purpose of the Study:

  • To provide a comprehensive overview of traditional basket trial designs.
  • To identify and discuss practical challenges associated with existing basket trial methodologies.
  • To review recent innovative adaptations of basket trials from Bayesian and Classical Frequentist viewpoints.

Main Methods:

  • Literature review of traditional and novel basket trial designs.
  • Categorization of new adaptations into Bayesian and Classical Frequentist approaches.
  • Analysis of practical challenges and proposed solutions for basket trial implementation.

Main Results:

  • Traditional basket trial designs and their inherent limitations are presented.
  • Novel adaptations, including Bayesian and Frequentist methods, offer potential solutions to design challenges.
  • The review synthesizes advancements in evaluating biomarker-targeted therapies.

Conclusions:

  • Newer basket trial designs aim to improve the efficiency and effectiveness of precision medicine research.
  • Understanding the advantages and limitations of these novel designs is crucial for future clinical trial development.
  • These adaptations hold promise for advancing the goals of molecularly-targeted cancer therapy.