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An Example of How to Write the Statistical Section of a Bioequivalence Study Protocol for FDA Review

This paper provides a detailed example of how one should write the statistical section of a bioequivalence study protocol for FDA review. Three forms of bioequivalence are covered: average bioequivalence (ABE), population bioequivalence (PBE) and individual bioequivalence (IBE). The method of analysis is based on Jones and Kenward (2003) and a modification of their SAS Macro is provided. Statistical Approach to Establishing Bioequivalence If one assumes an orally administered drug is being considered, pharmacokinetics (PK) is concerned with obtaining information on the absorption, distribution, metabolism and elimination of the drug under consideration. PK is the study of what the body does to the drug. An important outcome of a PK study is the assessment of how much of the active constituents of the drug reaches its site of action. Since this type of assessment cannot be easily made, the concentration of the drug under consideration that reaches the circulating bloodstream is taken as a surrogate. This concentration of the drug in the blood is referred to as its bioavailability. Two drugs that have the same bioavailability are termed bioequivalent. Following FDA Guidelines, the statistical analysis should be based on the non-compartmental PK parameters AUC0-t (Area Under the Curve from time 0 to last measurable time point), AUC0 to inf (Area Under the Curve from time 0 to infinity) and Cmax (maximum concentration) derived from the drug concentration-time curve. Three Forms of Bioequivalence In the following narrative, we refer to the original or innovator version of the drug under consideration as the “Reference” or R. The new or alternative version of the drug we will refer to as the “Test” or T. 1. Average Bioequivalence (ABE): To show that T and R are average bioequivalent it is only necessary to show that the mean ln(AUC) and the mean ln(Cmax) for T is not significantly different from the mean ln(AUC) and the mean ln(Cmax) for R. In other words we need to show that, “on average”, in the population of intended patients, the two drugs are bioequivalent. This measure does not take into account the variability of T and R. It is possible for one drug to be much more variable than the other, yet similar in terms of mean ln(AUC) and the mean ln(Cmax). It is for this reason that Population Bioequivalence (PBE) was introduced. 2. Population Bioequivalence (PBE): The measure of PBE is a mixture of the mean and variance of the ln(AUC) and the ln(Cmax). PBE can be considered as a measure that permits patients who have not yet been treated with T or R to be safely prescribed either. 3. Individual Bioequivalence (IBE): Two drugs could be similar in mean and variance over the population of potential patients, but be such that they produce different effects when a patient is switched from formulation T to formulation R or vice-versa. In other words, there is a significant subject-by-formulation interaction. To show that this is not the case T and R have to be shown to be Individual Bioequivalence (IBE). 1 Hosted by The Berkeley Electronic Press The measure of IBE is an aggregate measure involving the means and variances of T and R and the subject-by-formulation interaction. IBE can be considered as a measure that permits a patient who is currently being treated with R to be safely switched to T. NOTE: If T is IBE to R it does not imply that R is IBE to T. Study Design A replicated crossover design (four-period, two-sequence, two-formulation) will be used that will allow for the assessment of ABE, PBE and IBE.