Knowledge of how to do basic tasks using the Phoenix interface, such as creating a project and importing data, is assumed.
Analyzing average bioequivalence of 2x2 crossover study example
Analyzing average bioequivalence of a replicated crossover design example
Evaluating individual and population bioequivalence example
Analyzing average bioequivalence of 2x2 crossover study example
The objective of this study is to compare a newly developed tablet formulation to the capsule formulation that was being used in Phase II studies. Both had a label claim of 25 mg per dosing unit.
A 2x2 crossover design was chosen for this study. Twenty subjects were randomly assigned to one of two sequence groups. Within each sequence group, each subject took both formulations, with a washout period between. Drug concentrations in plasma were measured, and the AUClast (area under a curve computed to the last observation) was calculated.
Data for this example are provided in …\Examples\WinNonlin\Supporting files. The dataset used is Data 2x2.CSV.
The completed project (Bioequivalence_2x2.phxproj) is available for reference in …\Examples\WinNonlin.
Set up the object
Create a new project named Bioequivalence_2x2.
Import the file …\Examples\WinNonlin\Supporting files\Data 2x2.CSV.
Right-click Data 2x2 in the Data folder and then select Send To > Computation Tools > Bioequivalence.
In the Main Mappings panel, map the columns to the contexts as follows:
AUClast to Dependent.
Leave Sequence mapped to Sequence.
Leave Subject mapped to Subject.
Leave Period mapped to Period.
Leave Formulation mapped to Formulation.
In the Model tab below the Setup panel, make sure that:
Crossover is selected for Type of study.
Average is selected for Type of Bioequivalence.
Capsule is selected for Reference Formulation.
Select the Fixed Effects tab and make sure that:
Sequence+Formulation+Period appears in the Model Specification field.
Ln(x) is selected from the Dependent Variables Transformation menu.
Select the Variance Structure tab.
The random effects are already specified in the Variance Structure tab. If they are not, type Subject(Sequence) in the Random Effects Model field.
Execute and view the results
Click 
(Execute icon) to execute the object.
The Average Bioequivalence worksheet indicates that the difference in ln(AUClast) between formulations is 0.046±0.073 (Difference±Diff_SE). The 90% confidence interval for the ratio is 92.216 (CI_90_Lower) to 118.780 (CI_90_Upper).
Since the interval is completely contained between 80 and 125, one can conclude that the formulations are bioequivalent.
Select the Partial Tests worksheet and compare with the Sequential Tests worksheet.
Because the data are balanced, the sequential and partial tests are identical. Note that, in the tests, Sequence is statistically significant but no other factor is.
Select any cell with a numerical value in the Bioequivalence worksheet output and look in the value display bar above to see the full precision of 15 decimal places.
The sequential Tests worksheet for the 2x2 crossover study is shown below.
This concludes the Bioequivalence example of analyzing a 2x2 crossover study.