UMR738 INSERM and University Paris Diderot, Paris, France.
Stat Med. 2012 May 20;31(11-12):1043-58. doi: 10.1002/sim.4390. Epub 2011 Oct 3.
Bioequivalence or interaction trials are commonly studied in crossover design and can be analysed by nonlinear mixed effects models as an alternative to noncompartmental approach. We propose an extension of the population Fisher information matrix in nonlinear mixed effects models to design crossover pharmacokinetic trials, using a linearisation of the model around the random effect expectation, including within-subject variability and discrete covariates fixed or changing between periods. We use the expected standard errors of treatment effect to compute the power for the Wald test of comparison or equivalence and the number of subjects needed for a given power. We perform various simulations mimicking crossover two-period trials to show the relevance of these developments. We then apply these developments to design a crossover pharmacokinetic study of amoxicillin in piglets and implement them in the new version 3.2 of the r function PFIM.
生物等效性或相互作用试验通常在交叉设计中进行研究，并可通过非线性混合效应模型进行分析，作为非房室方法的替代方法。我们提出了一种扩展非线性混合效应模型中的群体 Fisher 信息矩阵的方法，用于设计交叉药代动力学试验，该方法在随机效应期望处对模型进行线性化，包括个体内变异性和固定或随时间变化的离散协变量。我们使用治疗效果的预期标准误差来计算 Wald 检验的功效比较或等效性以及为给定功效所需的受试者数量。我们进行了各种模拟交叉两期试验的仿真，以展示这些发展的相关性。然后，我们将这些发展应用于设计一种关于小猪阿莫西林的交叉药代动力学研究，并在 r 函数 PFIM 的新版本 3.2 中实现它们。
