The objective of this study is to compare a newly developed tablet formulation to a capsule formulation that was used in Phase II studies. Both formulations have the same label claim per dosing unit.
A RTRT/TRTR replicated crossover design was chosen for this study. Twenty subjects were randomly assigned to one of two sequence groups. Concentra-tions of the drug were measured in plasma, and the AUClast (area under the time-concentration curve, computed to the last observation) was calculated.
Calculating average bioequivalence
Import the data set:
1. Select File > Import or click the Import button. The Open File(s) dialog is displayed.
2. Navigate to the Phoenix examples directory, which by default is located at C:\Program
Files\Pharsight\Phoenix\applica-tion\Examples.
3. Select Data 2x4.CSV and click Open.
The Worksheet Import Options dialog is displayed. The dialog is used to assign options for how the data are imported and presented.
4. Click Finish. The data set is added to the project’s Data folder.
A data set in CSV (Comma Separated Value) format is added to the Data folder as a worksheet.
5. View the data set by selecting it in the Data folder. The worksheet is dis-played in the Grid tab.
Begin bioequivalence:
1. Select the workflow in the Object Browser and then select Insert > NCA and Toolbox > Bioequivalence.
The Bioequivalence object is added to the workflow in the Object Browser.
Note: When multiple objects of the same type are added to a workflow they are numbered sequentially. For example, the second Bioequivalence object added to this workflow is called Bioequivalence 1.
2. Map the data set Data 2x4 as the input source for the Bioequivalence 1 object:
• Use the pointer to drag the Data 2x4 worksheet from the Data folder to the Main Mappings panel.
OR
• In the Bioequivalence 1 Main Mappings panel click the Select source button to open the Select Object dialog.
• Select the Data 2x4 worksheet and click Select.
3. Use the option buttons in the Main Mappings panel to map the data types to the following contexts:
• Map AUClast to the Dependent context.
The following data types are automatically mapped to contexts when the data set is mapped to the Bioequivalence model. If they are not, use the option buttons in the Main Mappings panel to map the data types to the appropriate contexts.
• Sequence is mapped to the Sequence context.
• Subject is mapped to the Subject context.
• Period is mapped to the Period context.
• Formulation is mapped to the Formulation context.
Set up the model:
Use the Model tab to specify settings for Bioequivalence model options. The Model tab is located underneath the Setup tab.
1. Make sure that Crossover is selected as the Type of study, Average is selected as the Type of Bioequivalence, and Capsule is selected as the Reference Formulation.
2. Select the Fixed Effects tab, which is located underneath the Setup tab.
• Sequence+Formulation+Period is automatically selected as the default Model Specification. Do not change this setting.
Note: Phoenix has automatically selected a model specification and classification variables based on the model for replicated crossovers established in the U.S.
FDA Guidance for Industry - Statistical Approaches to Establishing Bioequiva-lence (January 2001).
• Ln(x) is automatically selected in the Dependent Variables Transforma-tion menu. Do not change this setting.
3. Select the Variance Structure tab, which is located underneath the Setup tab.
The random and repeated effects are already specified in the Variance Structure tab. If they are not, use the following steps to specify the variance structure. Oth-erwise, proceed to step 6.
4. Select the Variance Structure’s Random 1 tab.
• Formulation is automatically selected in the Random Effects field. Do not change this setting.
• Subject is automatically selected in the Variance Blocking Variables (Subject) field. Do not change this setting.
• Banded No-Diagonal Factor Analytic(f) is automatically selected in the Type menu. Do not change this setting.
• 2 is automatically entered in the Number of factors (f) = field. Do not change this setting.
Notice that the default variance structure for a replicated crossover design is sub-stantially different from and more complex than that for the 2x2 crossover design.
As a result, the model fitting is more difficult as well.
5. Select the Variance Structure’s Repeated tab.
• Period is automatically selected in the Repeated Specification field. Do not change this setting.
• Subject is automatically selected in the Variance Blocking Variables (Subject) field. Do not change this setting.
• Formulation is automatically selected in the Group field. Do not change this setting.
• Variance Components is automatically selected in the Type menu. Do not change this setting.
A user can expect that about 50% of data sets analyzed will produce a non-posi-tive definite G matrix. This does not imply that the model-fitting is invalid, but only that a user must be careful not to over-interpret the variance estimates. The con-fidence interval on the formulation difference will still have the expected statistical properties.
6. Click the Execute button. The results are displayed on the Results tab.
Results
The Bioequivalence analysis just failed to show bioequivalence, given that the 90% confidence interval = 91.612 lower and 125.772 upper.
Because the data are balanced, the sequential and partial tests are identical.
Sequential Tests worksheet
Partial Tests worksheet