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Evaluation of program success for programs with multiple trials in binary outcomes.

Meihua Wang1, G Frank Liu1, Jerald Schindler1

  • 1Merck Research Laboratories, North Wales, PA, USA.

Pharmaceutical Statistics
|February 4, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a method to estimate the probability of program success (POPS) for late-stage clinical development programs earlier. This allows for timely decisions, potentially saving resources by abandoning unpromising drug development early.

Keywords:
binary outcomesconfidence measuresprobability of program successprobability of success

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Area of Science:

  • Clinical trial methodology
  • Pharmaceutical development
  • Biostatistics

Background:

  • Late-stage clinical development programs often involve multiple trials.
  • Traditionally, program success is determined only after all trials are completed.
  • Interim analyses are increasingly used for early evaluation of individual studies.

Purpose of the Study:

  • To develop a method for estimating the probability of program success (POPS) in multi-trial clinical development programs.
  • To enable earlier decision-making regarding program continuation or termination.
  • To facilitate resource allocation by identifying unpromising programs early.

Main Methods:

  • Calculating the probability of success (POS) at the individual study level.
  • Estimating the probability of program success (POPS) for programs with multiple trials and binary outcomes.
  • Utilizing conditional power, predictive power, and other indexes for interim analyses.
  • Evaluating methods for calculating variation and confidence measures for POS and POPS.
  • Simulations and retrospective analysis of historical clinical trial data for depression.

Main Results:

  • A novel method for calculating POS and POPS is presented.
  • The proposed methods allow for earlier estimation of overall program success.
  • Simulations demonstrate the utility of the methods for assessing program viability.
  • Retrospective analysis on depression clinical program data illustrates practical application.

Conclusions:

  • Early estimation of POPS can significantly aid decision-making in late-stage clinical development.
  • This approach supports efficient resource management in pharmaceutical R&D.
  • The methods provide valuable tools for evaluating the likelihood of success in multi-trial programs.