Hu Chuanpu, Zhang Ji, Zhou Honghui
Pharmacokinetics, Modeling & Simulation, Centocor R&D, Inc., Malvern, PA 19355, USA.
Pharm Stat. 2011 Jan-Feb;10(1):14-26. doi: 10.1002/pst.403.
Population pharmacokinetics (POPPK) has many important uses at various stages of drug development and approval. At the phase III stage, one of the major uses of POPPK is to identify covariate influences on human pharmacokinetics, which is important for potential dose adjustment and drug labeling. One common analysis approach is nonlinear mixed-effect modeling, which typically involves time-consuming extensive search for best fits among a large number of possible models. We propose that the analysis goal can be better achieved with a more standard confirmatory statistical analysis approach, which uses a prespecified primary analysis and additional sensitivity analyses. We illustrate this approach using a phase III study data set and compare the result with that calculated using the common exploratory approach. We argue that the confirmatory approach not only substantially reduces analysis time but also yields more accurate and interpretable results. Some aspects of this confirmatory approach may also be extended to data analysis in earlier stages of clinical drug development, i.e. phase II and phase I.
群体药代动力学(POPPK)在药物研发和审批的各个阶段都有许多重要用途。在III期阶段,POPPK的主要用途之一是确定协变量对人体药代动力学的影响,这对于潜在的剂量调整和药物标签很重要。一种常见的分析方法是非线性混合效应建模,这通常涉及在大量可能的模型中进行耗时的广泛搜索以找到最佳拟合。我们提出,使用更标准的验证性统计分析方法可以更好地实现分析目标,该方法使用预先指定的主要分析和额外的敏感性分析。我们使用一个III期研究数据集来说明这种方法,并将结果与使用常见探索性方法计算的结果进行比较。我们认为,验证性方法不仅大大减少了分析时间,而且还产生了更准确和可解释的结果。这种验证性方法的某些方面也可能扩展到临床药物研发的早期阶段,即II期和I期的数据分析。