Agonistic TAM-163 antibody targeting tyrosine kinase receptor-B

Abstract

TAM-163, an agonist monoclonal antibody targeting tyrosine receptor kinase-B (TrkB), is currently being investigated as a potential body weight modulatory agent in humans. To support the selection of the dose range for the first-in-human (FIH) trial of TAM-163, we conducted a mechanistic analysis of the pharmacokinetic (PK) and pharmacodynamic (PD) data (e.g., body weight gain) obtained in lean cynomolgus and obese rhesus monkeys following single doses ranging from 0.3 to 60 mg/kg. A target-mediated drug disposition (TMDD) model was used to describe the observed nonlinear PK and Emax approach was used to describe the observed dose-dependent PD effect. The TMDD model development was supported by the experimental determination of the binding affinity constant (9.4 nM) and internalization rate of the drug-target complex (2.08 h⁻¹). These mechanistic analyses enabled linking of exposure, target (TrkB) coverage, and pharmacological activity (e.g., PD) in monkeys, and indicated that ≥ 38% target coverage (time-average) was required to achieve significant body weight gain in monkeys. Based on the scaling of the TMDD model from monkeys to humans and assuming similar relationship between the target coverage and pharmacological activity between monkey and humans, subcutaneous (SC) doses of 1 and 15 mg/kg in humans were projected to be the minimally and the fully pharmacologically active doses, respectively. Based on the minimal anticipated biological effect level (MABEL) approach for starting dose selection, the dose of 0.05 mg/kg (3 mg for a 60 kg human) SC was recommended as the starting dose for FIH trials, because at this dose level < 10% target coverage was projected at Cmax (and all other time points). This study illustrates a rational mechanistic approach for the selection of FIH dose range for a therapeutic protein with a complex model of action.

Keywords: :

• TAM-163
• Cachexia
• TrkB
• antibody
• TMDD
• body weight
• modeling
• pharmacokinetics
• pharmacodynamics
• PK/PD modeling

Disclosure of Potential Conflicts of Interest

All authors were employees of Pfizer, Inc. at the time of study completion.

Acknowledgments

Authors thank Chandrasekhar Udata, Pam Szklut, Lei Sun, Beth Leary, Chris Shea, Bonnie Rup, Janet Paulsen, Ying Sun, Kim Marquette, Guo Feng, Karissa Adkins, William McWilliams and Xin Xu for their valuable contributions to data generation and interpretation.