Trial Probability of Success for Testing 3-Way PK/PD Similarity With Multiple Endpoints.

Area of Science:

• Pharmacometrics
• Biostatistics
• Drug Development

Background:

• Pharmacokinetics and pharmacodynamics (PK/PD) similarity trials are crucial for biosimilar drug development.
• These trials often involve complex designs with multiple coprimary endpoints and 3-way treatment comparisons.
• Current sample size calculations may not adequately address uncertainty in treatment differences and variability, potentially impacting study power.

Purpose of the Study:

• To introduce and evaluate the assurance method for sample size determination in PK/PD similarity studies.
• To address the uncertainty associated with treatment differences and variability in multiple coprimary endpoints.
• To provide a practical tool for enhancing the reliability of study power estimations.

Main Methods:

• Development of an assurance method to handle multiple comparisons in PK/PD similarity trials.
• Proposal of a strategy for eliciting joint prior distributions using historical data.
• Implementation of methods in an R shiny application utilizing Monte Carlo simulations.

Main Results:

• The assurance method provides a more reliable estimation of study power by accounting for parameter uncertainty.
• The proposed methods enhance the understanding of power in complex PK/PD similarity study designs.
• A real data example demonstrates the practical utility and application of the assurance method.

Conclusions:

• The assurance method offers a valuable complement to conditional power in sample size considerations for PK/PD similarity studies.
• Incorporating assurance methods can lead to more robust and reliable study designs.
• This approach improves the accuracy of power calculations, crucial for regulatory submissions.