On sample size calculation in drug interaction trials

Area of Science:

• Pharmacokinetics and Drug Development
• Clinical Trial Design
• Statistical Methodology in Pharmacology

Background:

• Drug-drug interaction (DDI) trials are crucial for assessing concomitant medication risks and benefits.
• Traditional sample size calculations for DDIs rely on difficult-to-define no-effect boundaries, often leading to overly conservative estimates and large sample sizes.
• Existing methods are insufficient when prior evidence suggests a mild or moderate interaction may exist, necessitating effect boundaries.

Purpose of the Study:

• To introduce a novel precision-based sample size calculation method for DDI trials.
• To provide a more efficient and adaptable approach compared to traditional no-effect boundary methods.
• To account for pharmacokinetic variability and anticipated interaction boundaries.

Main Methods:

• Developed a precision-based sample size calculation framework.
• Incorporated stochastic pharmacokinetic parameters into the calculation.
• Considered the width of potential no-effect or effect boundaries.

Main Results:

• The proposed precision-based method requires a considerably smaller sample size.
• The methodology demonstrates favorable operating characteristics.
• A case study involving statins illustrated the practical application and benefits.

Conclusions:

• Precision-based sample size calculation offers a more efficient and practical approach for DDI trials.
• This method is advantageous when dealing with pharmacokinetic variability and known or anticipated interactions.
• The approach can streamline drug development by optimizing sample size requirements.