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最优抽样理论与种群建模:在确定微重力环境对药物分布和消除影响方面的应用

Optimal sampling theory and population modelling: application to determination of the influence of the microgravity environment on drug distribution and elimination.

作者信息

Drusano G L

机构信息

Division of Infectious Diseases, University of Maryland School of Medicine, Baltimore 21201.

出版信息

J Clin Pharmacol. 1991 Oct;31(10):962-7. doi: 10.1002/j.1552-4604.1991.tb03657.x.

Abstract

Newer mathematical techniques such as optimal sampling theory and NON-linear Mixed Effects Modelling (NONMEM) allow the determination of pharmacokinetics and pharmacodynamics in populations of individuals previously believed to be "too ill" or "too difficult to study." Optimal sampling determines the most information-rich times to sample the system, allowing robust parameter estimates to be determined from the minimal number of samples. NONMEM, by taking the population as the unit of analysis, allows even fragmentary patient data sets to contribute to population parameter estimates. Obviously, the microgravity environment presents extreme logistical difficulties to the performance of traditional pharmacokinetic and pharmacodynamic studies. Examples of the validation of these techniques are presented, which indicates their likely utility in the important task of determining the influence of the microgravity environment on drug distribution and elimination, even accounting for the limitations of support which will be faced in this circumstance.

摘要

更新的数学技术,如最优抽样理论和非线性混合效应建模(NONMEM),使得在以前被认为“病情太重”或“太难研究”的个体群体中确定药代动力学和药效学成为可能。最优抽样确定对系统进行采样的信息最丰富的时间,从而能够从最少数量的样本中确定可靠的参数估计值。NONMEM以群体作为分析单位,甚至允许零碎的患者数据集对群体参数估计有所贡献。显然,微重力环境给传统药代动力学和药效学研究的开展带来了极大的后勤困难。文中给出了这些技术的验证示例,这表明它们在确定微重力环境对药物分布和消除的影响这一重要任务中可能具有实用价值,甚至考虑到在这种情况下将会面临的支持方面的限制。

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