Incorporating Multiple Imputation Into Tanezumab Dose-Response Modeling of WOMAC Pain CFB Across Six Randomized...

Area of Science:

• Clinical Trials
• Pharmacometrics
• Statistical Modeling

Background:

• Multiple imputation is a common technique for addressing missing data in clinical trials.
• Its application is well-established for pre-defined statistical models.
• Implementation for pharmacometric model development remains less clear.

Purpose of the Study:

• To describe the implementation of multiple imputation for pharmacometric model development during a regulatory submission.
• To consider alternative approaches for future applications.

Main Methods:

• Case study detailing the application of multiple imputation in a regulatory submission context.
• Exploration of challenges and solutions for model development.

Main Results:

• Successfully addressed the challenges of applying multiple imputation in pharmacometric model development for a regulatory submission.
• Identified practical considerations and potential alternative strategies.

Conclusions:

• Multiple imputation can be practically implemented for pharmacometric model development, even in regulatory settings.
• Further exploration of alternative methods is warranted for future clinical trial data analysis.