A global examination of allometric scaling for predicting human drug clearance and the prediction of large vertical allometry

• Published in: Journal of pharmaceutical sciences Vol. 95; no. 8; pp. 1783 - 1799
• Main Authors: Tang, Huadong, Mayersohn, Michael
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.08.2006; Wiley; American Pharmaceutical Association
• Subjects: allometric scaling; Biological and medical sciences; Biological Availability; C logP; clearance; Databases, Factual; General pharmacology; Humans; Medical sciences; Metabolic Clearance Rate - drug effects; Metabolic Clearance Rate - physiology; Pharmaceutical Preparations - administration & dosage; Pharmaceutical Preparations - metabolism; Pharmaceutical technology. Pharmaceutical industry; Pharmacology. Drug treatments; Predictive Value of Tests; protein binding; Technology, Pharmaceutical - methods; vertical allometry; Human; Drug; allometric scaling; Binding protein; Pharmaceutical technology; C logP; Prediction; Clearance; Pharmacokinetics; protein binding; vertical allometry
• ISSN: 0022-3549; 1520-6017
• DOI: 10.1002/jps.20481

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 (CLs; n = 102) is more predictable than apparent oral clearance (CLpo; n = 24), but caution needs to be applied because of potential CLpo prediction error caused by differences in bioavailability across species. (2) CLs of proteins (n = 10) can be more accurately predicted than that of non‐protein chemicals (n = 102). (3) CLs is more predictable for compounds eliminated by renal or biliary excretion (n = 33) than by metabolism (n = 57). (4) CLs 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 CLs of drugs having very low CLs. 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 (fu) 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. © 2006 Wiley‐Liss, Inc. and the American Pharmacists Association J Pharm Sci 95: 1783–1799, 2006