...
首页> 外文期刊>Journal of pharmacokinetics and pharmacodynamics >Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.
【24h】

Reduction and lumping of physiologically based pharmacokinetic models: prediction of the disposition of fentanyl and pethidine in humans by successively simplified models.

机译:减少和集中的基于生理的药代动力学模型:通过连续简化的模型预测芬太尼和哌替啶在人体内的分布。

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Physiologically based pharmacokinetic (PBPK) models can be used to predict drug disposition in humans from animal data and the influence of disease or other changes in physiology on the pharmacokinetics of a drug. The potential usefulness of a PBPK model must however be balanced against the considerable effort needed for its development. Proposed methods to simplify PBPK modeling include predicting the necessary tissue:blood partition coefficients (kp) from physicochemical data on the drug instead of determining them in vivo, formal lumping of model compartments, and replacing the various kp values of the organs and tissues by only two values, for "fat" and "lean" tissues, respectively. The aim of this study was to investigate the effects of simplifying complex PBPK models on their ability to predict drug disposition in humans. Arterial plasma concentration curves of fentanyl and pethidine were simulated by means of a number of successively reduced models. Median absolute prediction errors were used toevaluate the performance of each model, in relation to arterial plasma concentration data from clinical studies, and the Wilcoxon matched pairs test was used for comparison of predictions. An originally diffusion-limited model for fentanyl was simplified to perfusion-limitation, and this model was either lumped, reducing 11 organ/tissue compartments to six, or changed to a model based on only two kp values, those of fat (used for fat and lungs) and muscle (used for all other tissues). None of these simplifications appreciably changed the predictions of arterial drug concentrations in the 10 patients. Perfusion-limited models for pethidine were set up using either experimentally determined [Gabrielsson et al. 1986] or theoretically calculated [Davis and Mapleson 1993] kp values, and predictions using the former were found to be significantly better. Lumping of the models did not appreciably change the predictions; however, going from a full set of kp values to only two ("fat" and "lean") had an adverse effect.Using a kp for lungs determined either in rats or indirectly in humans [Persson et al. 1988], i.e., a total of three kp values, improved these predictions. In conclusion, this study strongly suggested that complex PBPK models for lipophilic basic drugs may be considerably reduced with marginal loss of power to predict standard plasma pharmacokinetics in humans. Determination of only two or three kp values instead of a "full" set can mean an important reduction of experimental work to define a basic model. Organs of particular pharmacological or toxicological interest should of course be investigated separately as needed. This study also suggests and applies a simple method for statistical evaluation of the predictions of PBPK models.
机译:基于生理学的药代动力学(PBPK)模型可用于根据动物数据以及疾病或其他生理学变化对药物药代动力学的影响来预测人类的药物处置。但是,PBPK模型的潜在有用性必须与其开发所需的大量工作相平衡。简化PBPK建模的建议方法包括预测必要的组织:从药物的理化数据中而不是在体内确定它们的血液分配系数(kp),对模型区室进行正式集总,并仅用器官和组织的各种kp值替换两个值,分别代表“胖”和“瘦”组织。这项研究的目的是研究简化复杂的PBPK模型对其预测人类药物处置能力的影响。芬太尼和哌替啶的动脉血药浓度曲线是通过一系列连续减少的模型模拟的。与来自临床研究的动脉血药浓度数据相比,使用中位数绝对预测误差来评估每个模型的性能,并使用Wilcoxon匹配对检验进行预测比较。最初将芬太尼的扩散限制模型简化为灌注限制,并且该模型要么集总,将11个器官/组织隔室减少到六个,要么更改为仅基于两个kp值的模型(用于脂肪(用于脂肪)和肺)和肌肉(用于所有其他组织)。这些简化都没有明显改变10例患者中动脉药物浓度的预测。使用实验确定的方法建立哌替啶的灌注受限模型[Gabrielsson等。 1986年]或理论上计算得出的[Davis and Mapleson 1993年] kp值,发现使用前者的预测要好得多。模型的集总并没有明显改变预测。但是,将整个kp值设置为仅两个值(“胖”和“瘦”)会产生不利影响。将kp用于在大鼠中或间接在人体内确定的肺部[Persson等。 1988],即总共三个kp值,改善了这些预测。总之,这项研究强烈表明,亲脂性碱性药物的复杂PBPK模型可能会大大降低,从而无法预测人的标准血浆药代动力学。仅确定两个或三个kp值而不是“完整”集,就意味着可以大大减少定义基本模型的实验工作。当然,应根据需要单独研究具有特殊药理或毒理学意义的器官。这项研究还建议并应用一种简单的方法对PBPK模型的预测进行统计评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号