Designing trials to test the bioequivalence of diets for animal performance

ABSTRACT It is usually the desire of the researcher to demonstrate a difference in the comparisons made. This is certainly the case when an improved product is desired. However, in establishing the bioequivalence of a test product to a standard, the objective is usually to conclude, with reasonable justification, that no difference has been detected. In making such determinations, the probabilities of accepting false hypotheses or those of rejecting correct hypotheses of difference must be taken into account. Before beginning the trial, the researcher should have a good estimate of the power that will be associated with the detection of a given minimum acceptable difference. The required sample size for achieving the desired power for these tests depends on the coefficient of variation in the data collected and the minimum detectable difference between two groups that the study is meant to detect. It is important to determine the relative magnitudes of the sampling and the experimental errors in order to decide, for a given number of animals available for the study, how they might be best subdivided into groups within treatment. This paper addresses these points and others in an attempt to summarize some of the key items that researchers should consider when planning trials for the bioequivalence testing of new products.

Key Words: Experimental Design, Hypothesis Testing, Power, Sensitivity

© 2004, by the American Society of Animal Science. All rights reserved.

J. Anim. Sci. 2004. 82(E. Suppl.):E223-E228

Implications

When performing trials that compare the production potential of a new product with what is presently available in an existing product, it is imperative to specify the minimum difference between the two that will be used as a criterion for bioequivalence. This difference should have biological significance. It is also essential that the appropriate design be chosen to control bias and make possible a representative sample of the effects the products deliver in the experimental units that they are applied to. Using an incorrect error term for making the required comparisons is an often overlooked item that can result in misleading results. It is important that the researcher be quite clear on how broadly applied the results of the trial are intended to be. When there is concern about the validity of the statistical model or the way the analysis is to be performed, a statistician should be consulted. It is wise to involve a statistician in the planning stage of the trial.