Grasela T H, Fiedler-Kelly J B, Salvadori C, Marey C, Jochemsen R, Loo H
Center for Pharmacoepidemiology Research, University at Buffalo, New York.
Eur J Clin Pharmacol. 1993;45(2):123-8. doi: 10.1007/BF00315492.
The predictive ability of population pharmacokinetic parameters of tianeptine, obtained from a mixed effect analysis of pre-marketing pharmacokinetic studies, was evaluated using tianeptine plasma concentrations obtained during a large multi-center post-marketing surveillance study. The mean prediction error was 7.8 ng.ml-1 and the root mean square prediction error was 52.1 ng/ml when initial estimates of population pharmacokinetic parameters were used to predict drug concentrations in one half of the post-marketing data. When the population parameters were revised to reflect the data collected in the first half of the post-marketing study, the mean prediction error was reduced to -3.2 ng.ml-1 and the root mean square prediction error was reduced to 29.5 ng.ml-1. These results suggest that population pharmacokinetic parameters obtained from pre-marketing data may not accurately predict drug concentrations in patients receiving the drug in the post-marketing setting. Once the population parameters are updated to reflect data from the post-marketing period, the predictive ability of the data-base increases, but substantial variability in the prediction error remains.
使用从大型多中心上市后监测研究中获得的噻奈普汀血浆浓度，对通过上市前药代动力学研究的混合效应分析得出的噻奈普汀群体药代动力学参数的预测能力进行了评估。当使用群体药代动力学参数的初始估计值来预测上市后数据一半中的药物浓度时，平均预测误差为7.8 ng/ml，均方根预测误差为52.1 ng/ml。当群体参数经过修订以反映上市后研究前半段收集的数据时，平均预测误差降至-3.2 ng/ml，均方根预测误差降至29.5 ng/ml。这些结果表明，从上市前数据获得的群体药代动力学参数可能无法准确预测在上市后环境中接受该药物治疗的患者体内的药物浓度。一旦群体参数更新以反映来自上市后时期的数据，数据库的预测能力就会提高，但预测误差中仍存在很大的变异性。
