药代动力学
叠加原理
可预测性
加药
医学
药理学
线性模型
药品
数学
药品管理局
前提
计量经济学
统计
语言学
数学分析
哲学
作者
Alexander Bauer,Matts Kågedal,Martin J. Wolfsegger
摘要
Abstract The prediction of drug concentration time courses after different dosing scenarios is greatly facilitated if the pharmacokinetics (PK) can be assumed linear. The assumption of linear PK thus needs careful evaluation for any new drug in development. Under linear PK, exposure is proportional to dose (linear PK across doses) and exposure at steady state can be predicted from a single dose based on the superposition principle (linear PK over time). While investigation of dose‐proportionality is common practice, evaluation of time dependent PK has received less attention in the literature. In particular, the superposition principle can be used to assess whether the observed extent of accumulation after repeated administration is expected under the premise of linear PK. This work emphasizes the importance of the time related aspect of linear PK by introducing the predictability ratio (PR). Linear PK over time can be concluded if PR = 1. Accumulation is higher than expected if PR >1, and lower if PR <1. If PK data from multiple dose cohorts are available, the PR is assessed for each dose cohort and a supportive hypothesis test can be applied to test for potential differences between doses in PR.
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