Drug Metabolism and Pharmacokinetics, Merck Research Laboratory, 2015 Galloping Hill Road, Kenilworth, NJ 07033, USA.
Curr Top Med Chem. 2011;11(4):340-50. doi: 10.2174/156802611794480945.
This review focuses on a discussion of the controversies in allometric scaling (AS) for predicting human clearance from a mathematical and statistical perspective. First, a history of allometric scaling in comparative biology and its use in pharmacokinetics are reviewed. It is shown that the application of AS in predicting human clearance values based on a limited number of animal species (typically, 3 or 4) contains fundamental statistical errors when AS was first introduced from comparative biology. Second, the mathematical nature of various allometrically-based methods is revealed and the soundness of these methods is assessed. It is demonstrated that any of these methods, which incorporate a correction factor in a traditional allometric approach (varying-exponent allometry), not only reduces the statistical power of the allometric analysis, but are also incorrect with regard to aspects of biology. Finally, it is concluded that allometry remains a valuable tool for predicting human clearance, and should be applied in the context of a fixed exponent. However, fixed-exponent allometry does not provide satisfactory accuracy in predicting human clearance, since it is not able to capture the biological differences among species. Therefore, it is recommended that the overall effort in predicting human pharmacokinetics should be directed to the collection and generation of reliable data (both in vitro and in vivo) along with a better understanding of the DMPK properties of the chemical entity.
这篇综述从数学和统计学的角度讨论了用于预测人体清除率的种属间差异归一化(AS)的争议。首先,回顾了比较生物学中 AS 的历史及其在药代动力学中的应用。结果表明,当 AS 首次从比较生物学引入用于根据少数几种动物物种(通常为 3 或 4 种)预测人体清除率值时,AS 的应用存在基本的统计错误。其次,揭示了各种基于 AS 的方法的数学性质,并评估了这些方法的合理性。结果表明,这些方法中的任何一种,在传统的 AS 方法中加入校正因子(变指数 AS),不仅降低了 AS 分析的统计功效,而且在生物学方面也是不正确的。最后,结论是 AS 仍然是预测人体清除率的一种有价值的工具,应该在固定指数的背景下应用。然而,固定指数 AS 并不能提供令人满意的预测人体清除率的准确性,因为它无法捕捉物种之间的生物学差异。因此,建议在预测人体药代动力学时,应致力于收集和生成可靠的数据(包括体外和体内数据),并更好地了解化学实体的 DMPK 特性。