Wright J G, Boddy A V
Cancer Research Unit, University of Newcastle, Medical School, Newcastle upon Tyne, England.
Clin Pharmacokinet. 2001;40(4):237-44. doi: 10.2165/00003088-200140040-00001.
The half-life of a drug, which expresses a change in concentration in units of time, is perhaps the most easily understood pharmacokinetic parameter and provides a succinct description of many concentration-time profiles. The calculation of a half-life implies a linear, first-order, time-invariant process. No drug perfectly obeys such assumptions, although in practise this is often a valid approximation and provides invaluable quantitative information. Nevertheless, the physiological processes underlying half-life should not be forgotten. The concept of clearance facilitates the interpretation of factors affecting drug elimination, such as enzyme inhibition or renal impairment. Relating clearance to the observed concentration-time profile is not as naturally intuitive as is the case with half-life. As such, these 2 approaches to parameterising a linear pharmacokinetic model should be viewed as complementary rather than alternatives. The interpretation of pharmacokinetic parameters when there are multiple disposition phases is more challenging. Indeed, in any pharmacokinetic model, the half-lives are only one component of the parameters required to specify the concentration-time profile. Furthermore, pharmacokinetic parameters are of little use without a dose history. Other factors influencing the relevance of each disposition phase to clinical end-points must also be considered. In summarising the pharmacokinetics of a drug, statistical aspects of the estimation of a half-life are often overlooked. Half-lives are rarely reported with confidence intervals or measures of variability in the population, and some approaches to this problem are suggested. Half-life is an important summary statistic in pharmacokinetics, but care must be taken to employ it appropriately in the context of dose history and clinically relevant pharmacodynamic end-points.
药物的半衰期以时间单位表示浓度变化,可能是最容易理解的药代动力学参数,它简洁地描述了许多浓度-时间曲线。半衰期的计算意味着一个线性、一级、时不变过程。没有药物能完全符合这些假设,尽管在实际应用中这通常是一个有效的近似值,并能提供宝贵的定量信息。然而,不应忘记半衰期背后的生理过程。清除率的概念有助于解释影响药物消除的因素,如酶抑制或肾功能损害。将清除率与观察到的浓度-时间曲线联系起来,不像半衰期那样直观。因此,这两种参数化线性药代动力学模型的方法应被视为互补而非替代。当存在多个处置相时,药代动力学参数的解释更具挑战性。实际上,在任何药代动力学模型中,半衰期只是指定浓度-时间曲线所需参数的一个组成部分。此外,没有剂量史,药代动力学参数几乎没有用处。还必须考虑影响每个处置相对临床终点相关性的其他因素。在总结药物的药代动力学时,半衰期估计的统计学方面常常被忽视。半衰期很少报告置信区间或人群变异性的测量值,并提出了一些解决这个问题的方法。半衰期是药代动力学中一个重要的汇总统计量,但在剂量史和临床相关药效学终点的背景下,必须谨慎恰当地使用它。