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药物研发中药代动力学参数的异速生长标度:能否根据大鼠体内数据预测人体的清除率(CL)、稳态分布容积(Vss)和半衰期(t1/2)?

Allometric scaling of pharmacokinetic parameters in drug discovery: can human CL, Vss and t1/2 be predicted from in-vivo rat data?

作者信息

Caldwell Gary W, Masucci John A, Yan Zhengyin, Hageman William

机构信息

Johnson & Johnson Pharmaceutical Research and Development, L.L.C. Drug Discovery, Spring House, PA 19477, USA.

出版信息

Eur J Drug Metab Pharmacokinet. 2004 Apr-Jun;29(2):133-43. doi: 10.1007/BF03190588.

Abstract

In a drug discovery environment, reasonable go/no-go human in-vivo pharmacokinetic (PK) decisions must be made in a timely manner with a minimum amount of animal in-vivo or in-vitro data. We have investigated the accuracy of the in-vivo correlation between rat and human for the prediction of the total systemic clearance (CL), the volume of distribution at steady state (Vss), and the half-life (t1/2) using simple allometric scaling techniques. We have shown, using a large diverse set of drugs, that a fixed exponent allometric scaling approach can be used to predict human in-vivo PK parameters CL, Vss and t(1/2) solely from rat in-vivo PK data with acceptable accuracy for making go/no-go decisions in drug discovery. Human in-vivo PK predictions can be obtained using the simple allometric scaling relationships CL(Human) approximately = 40 CL(Rat) (L/hr), Vss(Human) approximately = 200 Vss(Rat) (L), and t1/2(Human) approximately = 4 t1/2(Rat) (hr). The average fold error for human CL predictions for N = 176 drugs was 2.25 with 79% of the drugs having a fold error less than 3. The average fold error for human Vss predictions for N = 144 drugs was 1.85 with 84% of the drugs having a fold error less than 3. The average fold error for human t1/2 predictions for N = 145 drugs was 2.05 with 76% of the drugs having a fold error less than 3. Using these simple allometric relationships, the sorting of drug candidates into a low/medium/high/very high human classification scheme was also possible from rat data. Since these simple allometric relationships between rat and human CL, Vss, and t1/2 are reasonably accurate, easy to remember and simple to calculate, these equations should be useful for making early go/no-go in-vivo human PK decisions for drug discovery candidates.

摘要

在药物研发环境中,必须利用最少的动物体内或体外数据及时做出合理的人体体内药代动力学(PK)放行/终止决策。我们使用简单的异速生长缩放技术,研究了大鼠与人类之间体内相关性在预测总全身清除率(CL)、稳态分布容积(Vss)和半衰期(t1/2)方面的准确性。我们使用大量不同的药物表明,固定指数的异速生长缩放方法可用于仅根据大鼠体内PK数据预测人体体内PK参数CL、Vss和t(1/2),其准确性足以在药物研发中做出放行/终止决策。可以使用简单的异速生长缩放关系CL(人类) ≈ 40 CL(大鼠)(L/小时)、Vss(人类) ≈ 200 Vss(大鼠)(L)和t1/2(人类) ≈ 4 t1/2(大鼠)(小时)来获得人体体内PK预测值。对于N = 176种药物的人体CL预测的平均倍数误差为2.25,79%的药物倍数误差小于3。对于N = 144种药物的人体Vss预测的平均倍数误差为1.85,84%的药物倍数误差小于3。对于N = 145种药物的人体t1/2预测的平均倍数误差为2.05,76%的药物倍数误差小于3。利用这些简单的异速生长关系,也可以根据大鼠数据将候选药物分类为低/中/高/非常高人体分类方案。由于大鼠与人类CL、Vss和t1/2之间的这些简单异速生长关系相当准确、易于记忆且计算简单,这些方程应有助于对药物研发候选物做出早期人体体内PK放行/终止决策。

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