PHARMACOKINETIC & PHARMACODYNAMIC SYSTEMS ANALYSIS

药代动力学

• 批准号: 6339176
• 负责人: DAVID Z D'ARGENIO
• 金额: $ 14.32万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2001-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6339176
• 关键词: bioengineering /biomedical engineering; biomedical resource; cardiovascular system; drug /agent; health care; statistics /biometry; technology /technique

During this past grant year we have implemented and investigated a Markov Chain Monte Carlo method, for use in individual Bayesian estimation of pharmacokinetic/pharmacodynamic models. The Independence Metropolis-Hastings (IMH) algorithm has been implemented for the general class a pk/pd models. In this implementation the prior density can be specified as a mixture of multivariate Normal or Lognormal densities. This has allowed us to investigate the case when the prior density is multimodal, which may occur, for example, when a minor subpopulation of subjects has pk/pd parameters distinct from the major population density. Our implementation of the IMH method is currently being used for individual Bayesian estimation as part of a clinical protocol of the drug Busulfan at the Saint Jude Research Hospital. We have also begun to investigate, using ideas from renewal processes, a regenerative MCMC method. The motivation is to provide an error analysis as part of a sample-based estimation scheme. Our first effort produces a regenerative Markov Chain by imbedding a IMH sampling within a non-Markov rejection sampling method. The combined method is referred to as a reject IMH sampler (RIMH). While this represents the simplest of nonlinear Bayesian estimation examples, it does illustrate the methods feasibility and will provide a useful initial example to further explore the performance of the RIMH algorithm.

在过去的赠款年中，我们已经实施并调查了 马尔可夫链蒙特卡洛法，用于单个贝叶斯 药代动力学/药效学模型的估计。 这 独立大都市杂货（IMH）算法已实施 对于通用类A PK/PD模型。 在此实施中 先前的密度可以指定为多元正常或 对数正态密度。 这使我们能够调查案件 先前的密度是多模态，例如，当a时可能发生 受试者的次要亚群的PK/PD参数不同于 主要人口密度。 我们对IMH方法的实施是 目前被用于单个贝叶斯估计作为一个 圣裘德研究中的毒品布鲁芬的临床方案 医院。 我们还开始使用Renewal的想法进行调查 过程，一种再生MCMC方法。 动机是提供 错误分析作为基于样本的估计方案的一部分。 我们的 首先努力通过嵌入IMH来产生一个再生马尔可夫链 在非马尔科夫排斥采样方法中采样。 组合 方法称为拒绝IMH采样器（RIMH）。 同时 代表最简单的非线性贝叶斯估计示例， 确实说明了方法可行性，并将提供有用的 最初的示例以进一步探索RIMH的性能 算法。