A single-species approach considering additional physiological information for prediction of hepatic clearance of glycoprotein derivate therapeutics

Abstract

Background and objectives: Existing methods for the prediction of human clearance of therapeutic proteins involve the use of allometry approaches. In general, these approaches have concentrated on the role of body weight, with only occasional attention given to more specific physiological parameters. The objective of this study was to develop a mechanism-based model of hepatic clearance (CL(H)), which combines a single-species scaling approach with liver physiology, for predicting CL(H) of selected glycoprotein derivate therapeutics, and to compare the outcome of this novel method with those of two empirical methods obtained from the literature - namely, the single-exponent theory and multiple-species allometry. Thus, this study was designed as an explanatory study to verify if the addition of physiological information is of benefit for extrapolating clearance of selected therapeutic proteins from one species to another.

Methods: Five glycoprotein derivate therapeutics that are known to be principally eliminated by asialoglycoprotein receptors (ASGPRs) under in vivo conditions were selected. It was assumed that the interspecies differences in CL(H) reported for these compounds are reflected by the interspecies differences in the abundance of these receptors. Therefore, key scaling factors related to these differences were integrated into one model. Fourteen extrapolation (prediction) scenarios across species were used in this study while comparing the single-species model, based on physiology, with the single-exponent theory. In addition, the physiological model was compared with multiple-species allometry for three proteins.

Results: In general, the novel physiological model is superior to the derived allometric methods. Overall, the physiological model produced a predicted CL(H) value with levels of accuracy of 100% within 3-fold, 100% within 2-fold and about 82% within 1.5-fold, compared with the observed values, whereas the levels of accuracy decreased to 93%, 77% and 53%, respectively, for allometry. The proposed physiological model is also superior to allometry on the basis of the root mean square error and absolute average fold error values.

Conclusions: It has been demonstrated that interspecies differences in the abundance of ASGPRs principally govern interspecies variations in CL(H) of compounds that are principally eliminated by ASGPRs. Overall, the proposed physiological model is an additional tool, which should facilitate investigation and prediction of human CL(H) of specific glycoproteins solely on the basis of clearance data determined in a single preclinical species.