A Novel Model for Prediction of Human Drug Clearance by Allometric Scaling

Abstract

Allometric scaling is widely used in predicting human clearance (CL) based on animal data. Since prediction errors are commonly observed in the practical application of this approach, various modifications to allometric scaling have been proposed. These modifications include in vitro metabolic data (Lave et al., 1997), correction by either maximum life-span potential (MLP) or brain weight (BrW) (Mahmood and Balian, 1996b), the "rule of exponents" (ROE) (Mahmood and Balian, 1996a), and scaling unbound CL (Feng et al., 2000). Correction by in vitro metabolic data was successful in predicting human CL of 10 extensively metabolized drugs (Lave et al., 1997). Based on a data analysis of 16 drugs, however, Mahmood (2002) concluded that the use of in vitro data obtained from liver microsomes to predict hepatic CL in humans did not provide reliable predictions. In addition, in vitro metabolic corrections cannot be applied to compounds eliminated by excretion. Scaling unbound CL across animal species improved the prediction for certain compounds (Feng et al., 2000); however, it failed to predict well for a few compounds with large vertical allometry such as diazepam and valproate. Recently, Mahmood (2000) suggested that unbound CL cannot be predicted any better than total clearance. Corrections either with MLP or BrW have been shown to be inappropriate if they are used indiscriminately, which led to the idea of ROE. This rule provides selection criteria for use of MLP or BrW, based on the values of the exponents obtained from simple allometry (Mahmood and Balian, 1996a). Although ROE has been shown to improve the prediction significantly compared with simple allometry, this method is still not satisfactory in predicting large vertical allometry. More recent studies (Nagilla and Ward, 2004) found that the corrections using MLP or BrW or the rule of exponents in allometric scaling did not result in significant improvements in predictions of human CL. Furthermore, they proposed that the monkey liver blood flow approach was superior to the rule of exponents. This controversy is currently not resolved (Mahmood, 2005;Nagilla and Ward, 2005).The coefficients (a) of the power function have been considered important in determining the magnitude of CL, because the exponents (b) have been shown to be relatively constant, with a typical value close to 0.75 (Boxenbaum, 1982). Based upon analysis of more than 60 drugs, we have observed that the water-octanol partition coefficient (log P) and the ratio of unbound fraction (f u ) in plasma between rats and humans (Rf u ) may provide simple rules for anticipating the occurrence of large vertical allometry. Based upon these findings, therefore, we attempted to develop a new model for predicting human CL. Materials and MethodsA literature search was performed to obtain animal data for allometric scaling of systemic CL (CL used in this article refers to systemic CL) and f u ratio in rats and humans. Only data sets including at least three animal species were used for scaling. Coefficien...

Drug metabolism and pharmacokinetics, the blood-brain barrier, and central nervous system drug discovery

“…There is a clear need to predict drug clearance in humans on the basis of experimental data. 11 As well as affecting the absorption and metabolism of a drug, lipophilicity also influences its binding and distribution. Generally, the higher the lipophilicity of a drug, the stronger its binding to protein and the greater its distribution.…”

Interspecies Prediction of Human Drug Clearance Based on Scaling Data from One or Two Animal Species

“…Because of its empirical nature and the numerous observed failures in predicting human CL, various modified allometrically based scaling methods have been proposed with the intent of improving predictability in humans. These methods primarily include corrections for maximum life-span potential (MLP) (Boxenbaum, 1982), corrections for brain weight (BrW) (Mahmood and Balian, 1996b), corrections for unbound fraction of drug in plasma (f u ) (Feng et al, 2000), the "rule of exponents" (ROE) (Mahmood and Balian, 1996a), liver blood flow (LBF) methods (Nagilla and Ward, 2004), corrections for in vitro metabolic CL (Lave et al, 1996), and empirical models correcting for plasma binding differences between animals and humans (Tang and Mayersohn, 2005c). The ROE technique has gained considerable support because of the soundness and practicality of the approach in correcting for MLP or BrW in each animal species; these correction procedures lower the prediction of human CL when a relatively high exponent is obtained from simple allometry (SA).…”

Derivation of a Unique Body Surface Area (Bsa) Formula for Calculation of Relatively Safe Doses of Dog and Human Anticancer Drugs

“…Although anticancer overdosing may be easily recognized, underdosing may occur in 30% of cancer patients [32]. This is because the predicted values for humans are heavily depended on certain species for example, dog [24], which has similar stomach morphology and emptying characteristics with human [33]. Higher BMI>25 kg/m 2 recorded for Irish Wolf Hound, Chinese Imperial Ch'ln (giant), Chinese Imperial Ch'ln (classic), Chinese Imperial Ch'ln (miniature), Chinese Imperial Ch'ln (Sleeve), Poodle (standard), Great Spitz, French Bulldog, Poodle (miniature) and Chinese Temple dog (miniature) may portend higher tendency for obesity, hypertension, coronary artery disease, diabetes and cancer in these breeds.…”

“…Hence modifications have been proposed to the various scalings [24]. The fact that all the human BSA formulas applied in this study yield BSA of larger dogs less than that of Cowgill and Drabkin's formula, indicates that human BSA formulas may be used in cancer chemotherapy of dogs.…”