Abstract：
Recently, we have proposed simple methodology to derive clearance and rate constant equations, independent of differential equations, based on Kirchhoff\'s Laws, a common methodology from physics used to describe rate-defining processes either in series or parallel. Our approach has been challenged in three recent publications, two published in this journal, but notably what is lacking is that none evaluate experimental pharmacokinetic data. As reviewed here, manuscripts from our laboratory have evaluated published experimental data, demonstrating that the Kirchhoff\'s Laws approach explains (1) why all of the experimental perfused liver clearance data appear to fit the equation that was previously believed to be the well-stirred model, (2) why linear pharmacokinetic systemic bioavailability determinations can be greater than 1, (3) why renal clearance can be a function of drug input processes, and (4) why statistically different bioavailability measures may be found for urinary excretion versus systemic concentration measurements. Our most recent paper demonstrates (5) how the universally accepted steady-state clearance approach used by the field for the past 50 years leads to unrealistic outcomes concerning the relationship between liver-to-blood Kpuu and hepatic availability FH , highlighting the potential for errors in pharmacokinetic evaluations based on differential equations. The Kirchhoff\'s Laws approach is applicable to all pharmacokinetic analyses of quality experimental data, those that were previously adequately explained with present pharmacokinetic theory, and those that were not. The publications that have attempted to rebut our position do not address unexplained experimental data, and we show here why their analyses are not valid. SIGNIFICANCE STATEMENT: The Kirchhoff\'s Laws approach to deriving clearance equations for linear systems in parallel or in series, independent of differential equations, successfully describes published pharmacokinetic data that has previously been unexplained. Three recent publications claim to refute our proposed methodology; these publications only make theoretical arguments, do not evaluate experimental data, and never demonstrate that the Kirchhoff methodology provides incorrect interpretations of experimental pharmacokinetic data, including statistically significant data not explained by present pharmacokinetic theory. We demonstrate why these analyses are invalid.
摘要：
最近,我们提出了简单的方法来推导清除率和速率常数方程，独立于微分方程，根据基尔霍夫定律,物理学中的一种常用方法，用于描述串行或并行的速率定义过程。我们的方法在最近的三份出版物中受到了挑战，两篇发表在这本杂志上，但值得注意的是缺乏的是没有人评估实验药代动力学数据。正如这里所回顾的，我们实验室的手稿评估了已发表的实验数据，证明基尔霍夫定律方法解释了（1）为什么所有的实验灌注肝脏清除率数据似乎符合以前被认为是良好搅拌模型的方程，（2）为什么线性药代动力学全身生物利用度测定可以大于1，（3）为什么肾脏清除率可以是药物输入过程的函数，和（4）为什么统计上不同的生物利用度测量可以发现尿排泄与全身浓度测量。我们最近的论文证明（5）在过去的50年中，该领域采用的普遍接受的稳态清除方法如何导致有关肝脏-血液Kpuu和肝脏可用性FH之间关系的不切实际的结果，强调在基于微分方程的药代动力学评估中可能出现错误。基尔霍夫定律方法适用于所有药代动力学分析的高质量实验数据，那些以前用目前的药代动力学理论充分解释的，和那些不是。试图反驳我们立场的出版物没有解决无法解释的实验数据，我们在这里展示了为什么他们的分析无效。意义陈述基尔霍夫定律方法推导并行或串行线性系统的间隙方程，独立于微分方程，成功描述了以前无法解释的已发表的药代动力学数据.最近的三篇出版物声称驳斥了我们提出的方法；这些出版物只提出了理论上的论点，不评估实验数据；从不证明基尔霍夫方法对实验药代动力学数据的解释不正确，包括目前药代动力学理论无法解释的统计学显著数据。我们证明了为什么这些分析是无效的。
