el-Tahtawy A A, Tozer T N, Harrison F, Lesko L, Williams R
Food and Drug Administration, Center for Drug Evaluation and Research, Rockville, Maryland 20857, USA.
Pharm Res. 1998 Jan;15(1):98-104. doi: 10.1023/a:1011961006297.
Evaluating of the effects of high intrasubject variability in clearance (CL) and volume of distribution (V), on 90% confidence intervals (CIs) for AUC (Area Under the concentration Curve) in single and multiple-dose bioequivalence studies. The main methodology was Monte Carlo simulation, and we also used deterministic simulation, and examination of clinical trials. The results are compared with those previously observed for Cmax (maximum concentration.)
The time course of drug concentration in plasma was simulated using a one-compartment model with log-normal statistical distributions of intersubject and intrasubject variabilities in the pharmacokinetic parameters. Both immediate-release and prolonged-release products were simulated using several levels of intrasubject variability in single-dose and multiple-dose studies. Simulations of 2000 clinical bioequivalence trials per condition (138 conditions) with 30 subjects in each crossover trial were carried out. Simulated data were compared with data from actual bioequivalence trials.
The current simulations for AUC show similar probabilities of failure for single-dose and multiple-dose bioequivalence studies, even with differences in the rate of absorption or fraction absorbed. AUC values from prolonged-release scenario studies are more sensitive to changes in the first order absorption rate constant ka, and to variability in CL and V than AUC from studies of immediate-release studies.
We showed that multiple-dose designs for highly variable drugs do not always reduce intrasubject variability in either AUC or Cmax, although the behavior of AUC differs from Cmax. Single dose AUC to the last quantifiable concentration was more reliable than either single dose AUC extrapolated to infinity, or multiple dose AUC during a steady-state interval. Multiple-dose designs may not be the best solution for assessing bioequivalence of highly variable drugs.
评估清除率（CL）和分布容积（V）的高个体内变异性对单剂量和多剂量生物等效性研究中AUC（浓度曲线下面积）的90%置信区间（CI）的影响。主要方法是蒙特卡洛模拟，我们还使用了确定性模拟和临床试验检查。将结果与先前观察到的Cmax（最大浓度）结果进行比较。
使用单室模型模拟血浆中药物浓度的时间过程，药代动力学参数的个体间和个体内变异性采用对数正态统计分布。在单剂量和多剂量研究中，使用几种个体内变异性水平模拟速释和缓释产品。对每种情况（138种情况）进行2000次临床生物等效性试验模拟，每个交叉试验有30名受试者。将模拟数据与实际生物等效性试验数据进行比较。
目前对AUC的模拟显示，单剂量和多剂量生物等效性研究的失败概率相似，即使吸收速率或吸收分数存在差异。与速释研究相比，缓释方案研究的AUC值对一级吸收速率常数ka的变化以及CL和V的变异性更敏感。
我们表明，对于高变异性药物，多剂量设计并不总是能降低AUC或Cmax的个体内变异性，尽管AUC的行为与Cmax不同。单剂量至最后可量化浓度的AUC比外推至无穷大的单剂量AUC或稳态间隔期间的多剂量AUC更可靠。多剂量设计可能不是评估高变异性药物生物等效性的最佳解决方案。
