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首页> 外文期刊>Brazilian Journal of Medical and Biological Research >Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone
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Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

机译:估计4-甲基氨基安替比林(一种双嘧啶的活性代谢物)的药代动力学参数的有限采样策略模型

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Bioanalytical data from a bioequivalence study were used to develop limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) and the peak plasma concentration (Cmax) of 4-methylaminoantipyrine (MAA), an active metabolite of dipyrone. Twelve healthy adult male volunteers received single 600 mg oral doses of dipyrone in two formulations at a 7-day interval in a randomized, crossover protocol. Plasma concentrations of MAA (N = 336), measured by HPLC, were used to develop LSS models. Linear regression analysis and a "jack-knife" validation procedure revealed that the AUC0- and the Cmax of MAA can be accurately predicted (R2>0.95, bias <1.5%, precision between 3.1 and 8.3%) by LSS models based on two sampling times. Validation tests indicate that the most informative 2-point LSS models developed for one formulation provide good estimates (R2>0.85) of the AUC0- or Cmax for the other formulation. LSS models based on three sampling points (1.5, 4 and 24 h), but using different coefficients for AUC0- and Cmax, predicted the individual values of both parameters for the enrolled volunteers (R2>0.88, bias = -0.65 and -0.37%, precision = 4.3 and 7.4%) as well as for plasma concentration data sets generated by simulation (R2>0.88, bias = -1.9 and 8.5%, precision = 5.2 and 8.7%). Bioequivalence assessment of the dipyrone formulations based on the 90% confidence interval of log-transformed AUC0- and Cmax provided similar results when either the best-estimated or the LSS-derived metrics were used.
机译:来自生物等效性研究的生物分析数据用于开发有限采样策略(LSS)模型,以估算血浆中的浓度与时间的曲线下面积(AUC)和4-甲基氨基安替比林(MAA)的峰值血浆浓度(Cmax)双嘧啶的代谢产物。十二位健康的成年男性志愿者在随机交叉方案中以7天间隔接受了两种制剂的600 mg口服双嘧酮的口服剂量。通过HPLC测量的MAA的血浆浓度(N = 336)用于建立LSS模型。线性回归分析和“千刀”验证程序表明,可以准确地预测AUC0- 和MAA的Cmax(R2> 0.95,偏差<1.5%,精度在3.1之间)和8.3%)的LSS模型基于两次采样时间。验证测试表明,为一种配方开发的最有用的2点LSS模型可以为另一种配方提供AUC0- 或Cmax的良好估计(R2> 0.85)。基于三个采样点(1.5、4和24小时)的LSS模型,但是使用不同的AUC0- 和Cmax系数,预测了参选志愿者的两个参数的个体值(R2 > 0.88,偏差= -0.65和-0.37%,精度= 4.3和7.4%)以及通过模拟生成的血浆浓度数据集(R2> 0.88,偏差= -1.9和8.5%,精度= 5.2和8.7%) 。当使用最佳估计值或LSS衍生指标时,基于对数转化的AUC0- 和Cmax的90%置信区间,对双嘧啶制剂的生物等效性评估提供了相似的结果。

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