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提高平均药代动力学参数的估计值,以提高给药准确性并降低患者风险。

Improved estimates of mean pharmacokinetic parameters for increased accuracy in dosing and reduced risk to patients.

机构信息

School of Pharmacy and Biomolecular Sciences, University of Brighton, Brighton, UK.

Centre for Computational Systems Biology, ISTBI, Fudan University, Shanghai, PRC, China.

出版信息

Br J Clin Pharmacol. 2021 Sep;87(9):3518-3530. doi: 10.1111/bcp.14766. Epub 2021 Mar 1.

Abstract

AIMS

Pharmacokinetic equations, which relate different parameters of a single individual, are often applied to reported mean parameter-values, with the aim of estimating the mean value of an unreported parameter. Due to population heterogeneity this approach generally leads to errors in their estimation. We provide details of this source of error. Our aim is to take into account the effects of population heterogeneity in commonly used pharmacokinetic models. This provides improved estimates and knowledge of the concentration of a drug in the plasma over time.

METHODS

Inequalities and approximations for corrected mean estimates are derived. These results are then applied to published clinical-trial data to illustrate their accuracy in practical situations.

RESULTS

By using mean values within the pharmacokinetic equations for a single individual, we show that estimates of mean parameter values, for a variety of dosing regimens, generally have errors. Using published clinical trial data, we show that such estimates can systematically deviate from the exact mean value by up to 19%. We provide analytical results, which amount to inequalities when there are systematic deviations from exact results, along with approximate results that improve the accuracy of estimates.

CONCLUSIONS

Medical, pharmacy and nursing students should be educated about errors and inequalities that can arise when transforming reported mean values of pharmacokinetic parameters into the mean values of parameters that are required, but not reported. Using approximate results, that correct estimates of mean parameter values so that they more accurately reflect actual average values, may provide a practical solution.

摘要

目的

药代动力学方程将个体的不同参数联系起来,通常用于报告平均参数值,目的是估计未报告参数的平均值。由于人群异质性,这种方法通常会导致其估计值出现误差。我们详细说明了这种误差的来源。我们的目的是在常用的药代动力学模型中考虑到人群异质性的影响。这可以提供随时间变化的血浆中药物浓度的改善估计值和知识。

方法

推导出了校正平均值估计值的不等式和逼近值。然后将这些结果应用于已发表的临床试验数据,以说明它们在实际情况下的准确性。

结果

通过在单个个体的药代动力学方程中使用平均值,我们表明,对于各种给药方案,平均参数值的估计值通常存在误差。使用已发表的临床试验数据,我们表明,这些估计值可能会系统地偏离真实平均值高达 19%。我们提供了分析结果,当从精确结果存在系统偏差时,这些结果表现为不等式,同时还提供了可以提高估计值准确性的近似结果。

结论

医学生、药学学生和护理学生应该了解在将报告的药代动力学参数的平均值转换为所需但未报告的参数的平均值时可能出现的误差和不等式。使用近似结果校正平均参数值的估计值,使它们更准确地反映实际平均值,可能是一种实用的解决方案。

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