EVALUATION OF THE PRE-POSTERIOR DISTRIBUTION OF OPTIMIZED SAMPLING TIMES FOR THE DESIGN OF PHARMACOKINETIC STUDIES
EVALUATION OF THE PRE-POSTERIOR DISTRIBUTION OF OPTIMIZED SAMPLING TIMES FOR THE DESIGN OF PHARMACOKINETIC STUDIES
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DOI：
10.1080/10543406.2010.500065
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发表时间：
2012-01-01
影响因子：
1.1
通讯作者：
Eccleston, John
中科院分区：
文献类型：
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作者：
Duffull, Stephen B.;Graham, Gordon;Eccleston, John
信息论方法经常用于设计旨在了解药代动力学和药代动力学-药效学系统相关联的研究。这些设计技术，如d -最优性，提供了最佳的实验条件。最佳设计的性能将取决于研究者遵守所提出的研究条件的能力。然而，在临床环境中，不可能完全符合最佳设计，因此由于研究执行中的错误，会出现某种程度的非计划次优性。此外，由于这些模型的参数与数据的非线性关系，设计也局部依赖于一组标称参数值的任意选择。对研究条件和标称参数值集的不确定性都具有鲁棒性的设计可能在临床上使用。我们提出了一种自适应设计策略来考虑执行误差和参数值的不确定性。在这项研究中，我们研究了一个单室一级药代动力学模型的设计。我们在贝叶斯框架中使用马尔可夫链蒙特卡罗（MCMC）方法来实现这一点。我们考虑了参数上的对数正态先验分布，并研究了采样时间上的几种先验分布。采用自适应设计，以所有先前样本的实际时间为条件，找到当前采样时间的采样窗口。
Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.