Combinability of Animal Data in Relative Potency Estimations

In this article, we propose a strategy to show the combinability of multiple animal datasets in a parallel-line assay to estimate the relative potency. The following three assumptions are made in the linear fixed-effect modeling, and we examine if any of them result in nonconformance: For inferences about relative potency, a) is essential, and we derived a new metrics, intrasubject parallelism criterion (ISP), via the translation of aggregated individual bioequivalence criterion stated in the regulatory guidance (Food and Drug Administration, 2001). For b) and c), we used the 95% confidence interval of the I 2 criterion, which is commonly used to evaluate the interstudy homogeneity in a meta-analysis (Higgins and Thompson, 2002). For choosing the thresholds, we applied the conven-tions used in the guideline. The proposed procedure is demonstrated in an example analysis, and its properties are evaluated through a Monte Carlo simulation. The power of our proposed intrasubject parallelism criterion was shown to be high for designs of moderate size, but the demonstration of homogeneity via I 2 was rather conservative.