Fullerton T, Forrest A, Levy G
Department of Pharmacy, School of Pharmacy, State University of New York at Buffalo, Amherst 14260, USA.
J Pharm Sci. 1996 Jun;85(6):600-7. doi: 10.1021/js9504705.
The purpose of this investigation was to explore, by computer simulation, the utility of two different clinical trial designs with sparse sampling (three concentration--effect measurements per subject) for population pharmacodynamic studies when the targeted drug concentration or effect measurements are determined by application of optimal sampling theory based on the results of a preceding, data-intensive pilot study. The two design paradigms were concentration-controlled and pharmacologic effect-controlled randomized clinical trials, respectively. The drug concentration--pharmacologic effect relationship was assumed to be describable by the Hill (sigmoid Emax) equation without hysteresis. Intersubject variability was represented by coefficients of variation of 30, 40, and 30% for Emax, EC50, and gamma, respectively. Random controller imprecision and measurement errors were included. Concentration and effect data for 100 subjects were generated by Monte Carlo simulation (ADAPT II), and pharmacodynamic parameter values were obtained by iterative two-stage analysis. These were then used to predict effect intensities over a range of drug concentrations, and the results were compared with those obtained by use of the true parameter values. Concentration- and effect-controlled trial designs were simulated in two forms: unconstrained and constrained with respect to the highest allowed targeted drug concentration or effect intensity. It was found that both types of unconstrained trials yielded good and comparable parameter estimates whereas the constrained trials (which are clinically more realistic) yielded more biased and imprecise estimates of individual pharmacodynamic parameters. Nevertheless, use of the latter to determine the effect intensities produced by different drug concentrations yielded good estimates but only in the range covered by the targeted concentration or effect measurements. For concentration-controlled trials it appears essential that the individuals in the pilot group and the clinical study group be drawn from the same population. Effect-controlled trials gave good results even when the pilot group was not representative of the population (e.g., for an aberrant subpopulation).
本研究的目的是通过计算机模拟,探讨在基于前期数据密集型预试验结果应用最优抽样理论确定目标药物浓度或效应测量值时,两种不同的稀疏抽样临床试验设计(每位受试者进行三次浓度-效应测量)在群体药效学研究中的效用。这两种设计范式分别是浓度控制和药理效应控制的随机临床试验。假设药物浓度-药理效应关系可用无滞后的希尔(S形Emax)方程描述。个体间变异性分别用Emax、EC50和γ的变异系数30%、40%和30%表示。纳入了随机控制器不精确性和测量误差。通过蒙特卡罗模拟(ADAPT II)生成100名受试者的浓度和效应数据,并通过迭代两阶段分析获得药效学参数值。然后将这些参数值用于预测一系列药物浓度下的效应强度,并将结果与使用真实参数值获得的结果进行比较。浓度控制和效应控制的试验设计以两种形式进行模拟:无约束和在最高允许目标药物浓度或效应强度方面有约束。结果发现,两种无约束试验都产生了良好且可比的参数估计值,而有约束试验(在临床上更现实)对个体药效学参数的估计更有偏差且不精确。然而,使用后者来确定不同药物浓度产生的效应强度能得到良好的估计值,但仅在目标浓度或效应测量所涵盖的范围内。对于浓度控制试验,似乎至关重要的是,预试验组和临床研究组的个体应来自同一人群。即使预试验组不代表总体人群(例如,对于异常亚群),效应控制试验也能给出良好结果。