Statistical comparison of dissolution profiles to predict the bioequivalence of extended release formulations

通过溶出曲线的统计比较来预测缓释制剂的生物等效性

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Abstract

Appropriate setting of dissolution specification of extended release (ER) formulations should include precise definition of a multidimensional space of complex definition and interpretation, including limits in dissolution parameters, lag time (t-lag), variability, and goodness of fit. This study aimed to set dissolution specifications of ER by developing drug-specific dissolution profile comparison tests (DPC tests) that are able to detect differences in release profiles between ER formulations that represent a lack of bioequivalence (BE). Dissolution profiles of test formulations were simulated using the Weibull and Hill models. Differential equations based in vivo-in vitro correlation (IVIVC) models were used to simulate plasma concentrations. BE trial simulations were employed to find the formulations likely to be declared bioequivalent and nonbioequivalent (BE space). Customization of DPC tests was made by adjusting the delta of a recently described tolerated difference test (TDT) or the limits of rejection of f2. Drug ka (especially if ka is small), formulation lag time (t-lag), the number of subjects included in the BE studies, and the number of sampled time points in the DPC test were the factors that affected the most these setups of dissolution specifications. Another recently described DPC test, permutation test (PT), showed excellent statistical power. All the formulations declared as similar with PT were also bioequivalent. Similar case-specific studies may support the biowaiving of ER drug formulations based on customized DPC tests.

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