Disposition of minaprine in animals and in human extensive and limited debrisoquine hydroxylators

A global examination of allometric scaling for predicting human drug clearance and the prediction of large vertical allometry**This work was presented at the American Association of Pharmaceutical Scientists Annual meeting, Salt Lake City, USA, Oct. 26, 2003

Allometrically scaled data sets (138 compounds) used for predicting human clearance were obtained from the literature. Our analyses of these data have led to four observations. (1) The current data do not provide strong evidence that systemic clearance (CL(s); n = 102) is more predictable than apparent oral clearance (CL(po); n = 24), but caution needs to be applied because of potential CL(po) prediction error caused by differences in bioavailability across species. (2) CL(s) of proteins (n = 10) can be more accurately predicted than that of non-protein chemicals (n = 102). (3) CL(s) is more predictable for compounds eliminated by renal or biliary excretion (n = 33) than by metabolism (n = 57). (4) CL(s) predictability for hepatically eliminated compounds followed the order: high CL (n = 11) > intermediate CL (n = 17) > low CL (n = 29). All examples of large vertical allometry (% error of prediction greater than 1000%) occurred only when predicting human CL(s) of drugs having very low CL(s). A qualitative analysis revealed the application of two potential rules for predicting the occurrence of large vertical allometry: (1) ratio of unbound fraction of drug in plasma (f(u)) between rats and humans greater than 5; (2) C logP greater than 2. Metabolic elimination could also serve as an additional indicator for expecting large vertical allometry.

Interspecies scaling: predicting oral clearance in humans

The objective of this study was to test the interspecies scaling approach for a wide variety of drugs to predict oral clearance in humans from animal data. This study is an attempt to evaluate whether the rule of exponents of Mahmood and Balian for the prediction of systemic clearance can also be applied for the prediction of oral clearance in humans. Three different methods were used to generate log-log plots to scale up the clearance values: (1) clearance versus body weight (simple allometric equation), (2) the product of clearance and maximum life-span potential (MLP) versus body weight, and (3) the product of clearance and brain weight versus body weight. Data from 32 drugs were analyzed, and it was concluded that the oral clearance of drugs could be best predicted using one of the allometric equations.

Interspecies scaling: is a priori knowledge of cytochrome p450 isozymes involved in drug metabolism helpful in prediction of clearance in humans from animal data?

The objective of this study was to evaluate whether a priori knowledge of cytochrome P450 isozymes involved in drug metabolism coupled with Mahmood' and Balian's 'rule of exponents' can be helpful for the prediction of clearance in humans using animal data. The clearance of 27 randomly selected drugs metabolized by different isozymes were scaled up from the animal data (at least three animal species) obtained from the literature. Three methods were utilized to generate allometric equations to scale up the clearance values: (i) clearance vs body weight (simple allometry); (ii) product of the clearance and maximum life-span potential (MLP) vs body weight; and (iii) the product of clearance and brain weight vs body weight. The choice of one of the methods was based on the 'rule of exponents' as described by Mahmood and Balian. The results of this study indicate that the knowledge of a particular isozyme does not provide a guide for the failure or success of allometry for the prediction of clearance. There is no trend which indicates that the chances of accurate prediction of clearance for a given drug are comparatively higher or lower when they are metabolized by a particular isozyme.

Metabolic polymorphisms

Polymorphisms have been detected in a variety of xenobiotic-metabolizing enzymes at both the phenotypic and genotypic level. In the case of four enzymes, the cytochrome P450 CYP2D6, glutathione S-transferase mu, N-acetyltransferase 2 and serum cholinesterase, the majority of mutations which give rise to a defective phenotype have now been identified. Another group of enzymes show definite polymorphism at the phenotypic level but the exact genetic mechanisms responsible are not yet clear. These enzymes include the cytochromes P450 CYP1A1, CYP1A2 and a CYP2C form which metabolizes mephenytoin, a flavin-linked monooxygenase (fish-odour syndrome), paraoxonase, UDP-glucuronosyltransferase (Gilbert's syndrome) and thiopurine S-methyltransferase. In the case of a further group of enzymes, there is some evidence for polymorphism at either the phenotypic or genotypic level but this has not been unambiguously demonstrated. Examples of this class include the cytochrome P450 enzymes CYP2A6, CYP2E1, CYP2C9 and CYP3A4, xanthine oxidase, an S-oxidase which metabolizes carbocysteine, epoxide hydrolase, two forms of sulphotransferase and several methyltransferases. The nature of all these polymorphisms and possible polymorphisms is discussed in detail, with particular reference to the effects of this variation on drug metabolism and susceptibility to chemically-induced diseases.