论文标题
有效的基于模型的生物等效性测试
Efficient model-based Bioequivalence Testing
论文作者
论文摘要
旨在比较两种不同配方的生物等效性研究中分析药代动力学（PK）数据的经典方法是进行非各个分析分析（NCA），然后进行两项单方面测试（TOST）。 In this regard the PK parameters $AUC$ and $C_{max}$ are obtained for both treatment groups and their geometric mean ratios are considered.根据美国食品和药物管理局和欧洲药品局的当前指南，如果这些比率的$ 90 \％$ - 置信区间宣布配方相似。由于NCA不是稀疏设计的可靠方法，因此已经提出了一种基于模型的替代方案，用于使用非线性混合效果模型估算$ AUC $和$ c_ {max} $。在这里，我们提出了另一个比TOST更强大的测试，并通过用于NCA和基于模型的方法的仿真研究来证明其优越性。对于PK参数差异很高的产品，此方法似乎具有更接近的I型错误，而常规接受的显着性水平为$ 0.05 $，这表明其在不适用常规生物等效性分析的情况下的潜在用途。
The classical approach to analyze pharmacokinetic (PK) data in bioequivalence studies aiming to compare two different formulations is to perform noncompartmental analysis (NCA) followed by two one-sided tests (TOST). In this regard the PK parameters $AUC$ and $C_{max}$ are obtained for both treatment groups and their geometric mean ratios are considered. According to current guidelines by the U.S. Food and Drug Administration and the European Medicines Agency the formulations are declared to be sufficiently similar if the $90\%$- confidence interval for these ratios falls between $0.8$ and $1.25$. As NCA is not a reliable approach in case of sparse designs, a model-based alternative has already been proposed for the estimation of $AUC$ and $C_{max}$ using non-linear mixed effects models. Here we propose another, more powerful test than the TOST and demonstrate its superiority through a simulation study both for NCA and model-based approaches. For products with high variability on PK parameters, this method appears to have closer type I errors to the conventionally accepted significance level of $0.05$, suggesting its potential use in situations where conventional bioequivalence analysis is not applicable.
