Meineke I, Gleiter C H
Department of Clinical Pharmacology, University of Göttingen, Germany.
J Clin Pharmacol. 1998 Aug;38(8):680-4. doi: 10.1002/j.1552-4604.1998.tb04806.x.
The evaluation of drug accumulation is approached from a practical point of view. Estimates of accumulation indices as obtained from standard estimators-AUC, peak levels, and trough levels (RAUAUC Rmax and Rmin, respectively)-are compared and differences analyzed. The estimators are based on the concentration-time curve characteristics area under the concentration-time curve (AUC), maximum concentration, and trough level. Simulated data are used for the analysis, both noise-free and with random error added. The data are based on pharmacokinetic parameters derived from a clinical study. The numerical procedures can be reproduced by the interested reader with little effort. It is shown empirically that if Rmin, > RAUC then simple kinetic behavior cannot be safely assumed, but accumulation is a complex function of time. Rmax as obtained from the data and an estimate of this value based on time to peak concentration (tmax) and apparent elimination rate constant (lambda(z)) after a single dose and at steady state can then be compared in an attempt to exclude time-dependent kinetics. This new numerical procedure can provide valuable and even pivotal information regarding the accumulation kinetics of a compound under investigation. Recommendations on how to use the available concentration-time information to the best advantage are presented. It is concluded that the assessment of drug accumulation should not be confined to the calculation of just one estimate, because the three estimators RAUC, Rmax. and Rmin reflect different aspects of accumulation. Moreover, all information about accumulation should be carefully analyzed in the clinical context. This way the relevant accumulation can be identified for safe and efficacious drug treatment.
从实际角度出发对药物蓄积进行评估。比较从标准估算指标——AUC、峰浓度和谷浓度(分别为RAUC、Rmax和Rmin)获得的蓄积指数估算值,并分析差异。这些估算指标基于浓度-时间曲线的特征——浓度-时间曲线下面积(AUC)、最大浓度和谷浓度。分析使用了模拟数据,包括无噪声数据和添加了随机误差的数据。数据基于一项临床研究得出的药代动力学参数。感兴趣的读者可以轻松重现这些数值计算过程。经验表明,如果Rmin > RAUC,则不能安全地假定为简单的动力学行为,而是蓄积是时间的复杂函数。然后可以比较从数据中获得的Rmax以及基于单次给药和稳态时的达峰时间(tmax)和表观消除速率常数(lambda(z))对该值的估算,以试图排除时间依赖性动力学。这种新的数值计算过程可以提供有关所研究化合物蓄积动力学的有价值甚至关键的信息。本文提出了关于如何充分利用可用的浓度-时间信息的建议。得出的结论是,药物蓄积的评估不应局限于仅计算一种估算值,因为RAUC、Rmax和Rmin这三个估算指标反映了蓄积的不同方面。此外,应在临床背景下仔细分析所有关于蓄积的信息。通过这种方式,可以确定相关的蓄积情况,以实现安全有效的药物治疗。