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A seamless Phase I/II platform design with a time-to-event efficacy endpoint for potential COVID-19 therapies

Thomas Jaki1,2, Helen Barnett3, Andrew Titman3

  • 1Faculty for Informatics and Data Science, University Regensburg, Germany.

Statistical Methods in Medical Research
|October 14, 2024
PubMed

Insights

The AGILE platform efficiently identifies safe and effective COVID-19 treatments using adaptive trials. This novel approach accelerates the discovery of promising therapies with minimal sample sizes.

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Infectious Diseases

Background:

  • COVID-19 treatment development initially focused on repurposed drugs.
  • There is a need for novel therapeutics specifically designed for COVID-19.
  • Adaptive trial designs are crucial for efficient drug development.

Purpose of the Study:

  • To describe and evaluate the statistical design of the AGILE platform.
  • To establish a safe dosage range for potential COVID-19 treatments.
  • To investigate the efficacy of novel single-agent and combination therapies.

Main Methods:

  • Utilized an adaptive randomized seamless Phase I/II trial platform.
  • Employed a Bayesian statistical design with randomization during dose-finding.
  • Incorporated shared control arm information and a time-to-event endpoint for efficacy evaluation.

Main Results:

  • The AGILE platform design reliably identifies safe and efficacious treatments.
  • The design is effective with small to moderate sample sizes.
  • Successfully considered both single-agent and combination treatment strategies.

Conclusions:

  • The AGILE platform offers a robust and efficient method for COVID-19 drug discovery.
  • Adaptive trial designs are vital for accelerating the development of new infectious disease treatments.
  • The platform's statistical design ensures reliable identification of effective therapies.
Keywords:
Adaptive platform trialCOVID-19dose-escalationrandomizedseamlesstime-to-improvement

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