Regulatory assessment of drug dissolution profiles comparability via maximum deviation

Area of Science:

• Pharmaceutical Sciences
• Biopharmaceutics
• Statistical Analysis in Drug Development

Background:

• The similarity factor f2 is commonly used to assess drug dissolution profile comparability between formulations.
• The f2 factor has specific validity conditions that, if not met, render it unsuitable for comparability assessment.
• Existing methods may not adequately account for measurement variability over time.

Purpose of the Study:

• To propose and evaluate a novel inferential framework for testing drug dissolution profile comparability.
• To develop a method that is applicable irrespective of the f2 similarity factor's validity criteria.
• To introduce an approach that incorporates measurement variability, not just average differences.

Main Methods:

• An inferential framework based on the maximum deviation between dissolution profile curves was developed.
• Simulations were conducted using real case studies from the European Medicines Agency.
• The new method's performance was evaluated against the f2 factor, considering type I error rate and statistical power.

Main Results:

• The proposed maximum deviation method effectively controlled its type I error rate when deviations exceeded the 10% similarity limit.
• Statistical power exceeded 80% for small deviations, demonstrating sensitivity in detecting differences.
• The method showed robustness to sampling variations and performed conservatively for intermediate deviations.

Conclusions:

• The maximum deviation-based method is a valid and reliable alternative for assessing drug dissolution profile comparability.
• This approach is particularly valuable when the standard f2 similarity factor's validity criteria are not satisfied.
• The method's ability to integrate measurement variability enhances the assessment of formulation comparability.