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使用β清除率校正和末端约束非参数回归通过直接反卷积法测定时变处置中的药物吸收速率

Determination of drug absorption rate in time-variant disposition by direct deconvolution using beta clearance correction and end-constrained non-parametric regression.

作者信息

Neelakantan S, Veng-Pedersen P

机构信息

College of Pharmacy, The University of Iowa, Iowa City, IA 52242, USA.

出版信息

Biopharm Drug Dispos. 2005 Nov;26(8):353-70. doi: 10.1002/bdd.468.

Abstract

A novel numerical deconvolution method is presented that enables the estimation of drug absorption rates under time-variant disposition conditions. The method involves two components. (1) A disposition decomposition-recomposition (DDR) enabling exact changes in the unit impulse response (UIR) to be constructed based on centrally based clearance changes iteratively determined. (2) A non-parametric, end-constrained cubic spline (ECS) input response function estimated by cross-validation. The proposed DDR-ECS method compensates for disposition changes between the test and the reference administrations by using a "beta" clearance correction based on DDR analysis. The representation of the input response by the ECS method takes into consideration the complex absorption process and also ensures physiologically realistic approximations of the response. The stability of the new method to noisy data was evaluated by comprehensive simulations that considered different UIRs, various input functions, clearance changes and a novel scaling of the input function that includes the "flip-flop" absorption phenomena. The simulated input response was also analysed by two other methods and all three methods were compared for their relative performances. The DDR-ECS method provides better estimation of the input profile under significant clearance changes but tends to overestimate the input when there were only small changes in the clearance.

摘要

提出了一种新型数值反卷积方法,该方法能够在时变处置条件下估计药物吸收率。该方法包括两个部分。(1)处置分解-重构(DDR),能够基于迭代确定的基于中心的清除率变化构建单位脉冲响应(UIR)的精确变化。(2)通过交叉验证估计的非参数、末端约束三次样条(ECS)输入响应函数。所提出的DDR-ECS方法通过基于DDR分析的“β”清除率校正来补偿测试给药和参考给药之间的处置变化。ECS方法对输入响应的表示考虑了复杂的吸收过程,并且还确保了响应的生理现实近似。通过综合模拟评估了新方法对噪声数据的稳定性,该模拟考虑了不同的UIR、各种输入函数、清除率变化以及包括“翻转”吸收现象的输入函数的新型缩放。还通过其他两种方法分析了模拟的输入响应,并比较了所有三种方法的相对性能。DDR-ECS方法在清除率显著变化时能更好地估计输入曲线,但在清除率仅有微小变化时往往会高估输入。

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