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Selection of Quantitative Decision-Making Criteria Using Weighted Decision Error Rates.

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This study introduces a weighted decision error rate (WDER) to optimize drug development decisions, minimizing incorrect go/no-go errors. It guides phase 2 sample size and threshold selection for more efficient and robust drug advancement.

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Area of Science:

  • Drug Development
  • Decision Analysis
  • Biostatistics

Background:

  • Drug development involves critical go/no-go decisions.
  • Errors include proceeding with a failing drug (incorrect go) or halting a successful one (incorrect no-go).

Purpose of the Study:

  • To minimize combined risks of incorrect go and no-go decisions in phase 2/3 drug development.
  • To introduce a weighted decision error rate (WDER) for optimizing go thresholds when error types have different costs.
  • To explore the impact of prior beliefs and weighting on decision rules and phase 2 sample size.

Main Methods:

  • Developing a quantitative decision-making framework.
  • Defining and applying a weighted decision error rate (WDER).
  • Analyzing the influence of prior beliefs and weighting on optimal decision rules.

Main Results:

  • Optimal go thresholds can minimize combined decision error risks.
  • WDER guides phase 2 sample size determination, often increasing size and stringency.
  • Prior beliefs significantly influence optimal decision rules.

Conclusions:

  • A new definition of phase 2 probability of success should focus on correct decision-making, not just advancement.
  • The WDER framework enhances robustness and tailoring in drug development decision-making.
  • This approach improves risk-benefit assessment for phase transitions.