Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA.
Office of New Drug, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
J Clin Pharmacol. 2021 Oct;61(10):1324-1333. doi: 10.1002/jcph.1907. Epub 2021 Jul 28.
This analysis compared the results from noncompartmental analysis and population pharmacokinetic (PopPK) predictions of exposure changes in patients with renal impairment (RI) for 27 new molecular entities (NMEs) approved between 2000 and 2015. Renal function was identified as a covariate in the final PopPK model for 17 NMEs. The final PopPK model was used to simulate (n = 1000 replicates/individual) the results of a dedicated PK study in subjects with renal impairment. For the majority of NMEs, concordance between observed, and predicted area under the curve (AUC) geometric mean ratio (GMR) was observed (ie, in 17, 11, and 11 NMEs for mild, moderate, and severe renal impairment groups, respectively, the observed and predicted AUC GMR were within the same fold of change). Inclusion of colinear covariates in the PopPK model appeared to be the major driver for the NMEs for which there was discordance. PopPK, when done properly, is a valuable tool for supporting labeling recommendations for subjects with renal impairment.
本分析比较了 2000 年至 2015 年间批准的 27 种新分子实体(NME)中肾功能损害(RI)患者暴露变化的非房室分析(noncompartmental analysis)和群体药代动力学(PopPK)预测结果。在 17 种 NME 的最终 PopPK 模型中,肾功能被确定为协变量。最终的 PopPK 模型用于模拟(n = 1000 个个体/重复)在肾功能损害患者中进行的专门 PK 研究的结果。对于大多数 NME,观察到的和预测的曲线下面积(AUC)几何均数比值(GMR)之间存在一致性(即,在轻度、中度和重度肾功能损害组中,分别有 17、11 和 11 种 NME 的观察到的和预测的 AUC GMR 在相同的变化倍数内)。在 PopPK 模型中纳入共线性协变量似乎是导致那些存在差异的 NME 的主要因素。当正确进行时,PopPK 是支持肾功能损害患者标签推荐的有价值工具。