Centre for Human Drug Research, Leiden, The Netherlands.
Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
J Pharmacokinet Pharmacodyn. 2021 Jun;48(3):439-444. doi: 10.1007/s10928-021-09743-2. Epub 2021 Mar 3.
The quantitative description of individual observations in non-linear mixed effects models over time is complicated when the studied biomarker has a pulsatile release (e.g. insulin, growth hormone, luteinizing hormone). Unfortunately, standard non-linear mixed effects population pharmacodynamic models such as turnover and precursor response models (with or without a cosinor component) are unable to quantify these complex secretion profiles over time. In this study, the statistical power of standard statistical methodology such as 6 post-dose measurements or the area under the curve from 0 to 12 h post-dose on simulated dense concentration-time profiles of growth hormone was compared to a deconvolution-analysis-informed modelling approach in different simulated scenarios. The statistical power of the deconvolution-analysis-informed approach was determined with a Monte-Carlo Mapped Power analysis. Due to the high level of intra- and inter-individual variability in growth hormone concentrations over time, regardless of the simulated effect size, only the deconvolution-analysis informed approach reached a statistical power of more than 80% with a sample size of less than 200 subjects per cohort. Furthermore, the use of this deconvolution-analysis-informed modelling approach improved the description of the observations on an individual level and enabled the quantification of a drug effect to be used for subsequent clinical trial simulations.
当研究的生物标志物具有脉冲释放时（例如胰岛素、生长激素、促黄体激素），非线性混合效应模型中随时间变化的个体观测的定量描述变得复杂。遗憾的是，标准的非线性混合效应群体药效动力学模型（如转化和前体反应模型，无论是否包含余弦成分）无法随时间定量描述这些复杂的分泌曲线。在这项研究中，比较了标准统计方法（如 6 次给药后测量或给药后 0 至 12 小时的曲线下面积）的统计效能与去卷积分析信息建模方法在不同模拟场景中的表现。去卷积分析信息建模方法的统计效能通过蒙特卡罗映射功率分析来确定。由于生长激素浓度随时间的个体内和个体间变异性很高，无论模拟的效应大小如何，只有去卷积分析信息建模方法在每个队列不到 200 名受试者的样本量下，才达到了超过 80%的统计效能。此外，使用这种去卷积分析信息建模方法可以改善个体水平上的观测描述，并能够量化药物效应，用于后续的临床试验模拟。
