New approach to assess bioequivalence parameters using generalized gamma mixed-effect model (model-based asymptotic...

Area of Science:

• Pharmacokinetics
• Statistical Modeling
• Bioequivalence Testing

Background:

• Pharmacokinetic (PK) studies are crucial for drug development.
• Traditional bioequivalence tests may lack statistical power or accuracy.
• Mixed-effects models offer advanced analytical capabilities for PK data.

Purpose of the Study:

• To propose a novel mixed-effects model for analyzing drug concentration-time profiles in PK studies.
• To develop a new bioequivalence test based on the proposed model.
• To compare the performance of the proposed test against conventional methods.

Main Methods:

• A mixed-effects model was developed using a multivariate generalized gamma distribution.
• The model incorporates compartmental PK principles with between- and within-subject variability.
• A bioequivalence test was derived from estimated bioavailability parameters.
• Monte Carlo simulations were used for performance evaluation.

Main Results:

• The proposed model-based bioequivalence test demonstrated superior level maintenance and power.
• It outperformed conventional non-compartmental analysis and mixed-effects models with normal error.
• The model effectively describes drug concentration-time profiles with complex variations.

Conclusions:

• The proposed mixed-effects model and associated bioequivalence test offer a more robust approach.
• This method enhances the accuracy and power of bioequivalence assessments in PK studies.
• The approach is validated through simulation and application to real-world PK data.