Pharmacokinetic and Pharmacodynamic Modeling of a Monoclonal Antibody Antagonist of Glucagon Receptor in Male ob/ob Mice
Journal Title: The AAPS Journal - Year 2009, Vol 11, Issue 4
Abstract
Elevated basal concentrations of glucagon and reduced postprandial glucagon suppression are partly responsible for the increased hepatic glucose production seen in type 2 diabetic patients. Recently, it was demonstrated that an antagonistic human monoclonal antibody (mAb) blocking glucagon receptor (GCGR) has profound glucose-lowering effects in various animal models. To further understand the effects on glucose homeostasis mediated by such an antibody, a pharmacokinetic-pharmacodynamic (PK-PD) study was conducted in a diabetic ob/ob mouse model. Four groups of ob/ob mice were randomized to receive single intraperitoneal administration of placebo, 0.6, 1, or 3 mg/kg of mAb GCGR, a fully human mAb against GCGR. The concentration-time data were used for noncompartmental and compartmental analysis. A semi-mechanistic PK-PD model incorporating the glucose-glucagon inter-regulation and the hypothesized inhibitory effect of mAb GCGR on GCGR signaling pathway via competitive inhibition was included to describe the disposition of glucose and glucagon over time. The pharmacokinetics of mAb GCGR was well characterized by a two-compartment model with parallel linear and nonlinear saturable eliminations. Single injection of mAb GCGR caused a rapid glucose-lowering effect with blood glucose concentrations returning to baseline by 4 to 18 days with increasing dose from 0.6 to 3 mg/kg. Elevation of glucagon concentrations was also observed in a dose-dependent manner. The results illustrated that the feedback relationship between glucose and glucagon in the presence of mAb GCGR could be quantitatively described by the developed model. The model may provide additional understanding in the underlying mechanism of GCGR antagonism by mAb.
Authors and Affiliations
Yvonne Y. Lau, Peiming Ma, Leonid Gibiansky, Renee Komorowski, Jin Wang, George Wang, Hai Yan, Murielle M. Véniant, Tarundeep Kakkar
Keywords
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