PURPOSE: 4-[(1S,2S)-2-(4-cyclobutylpiperazine-1-carbonyl)cyclopropyl]benzamide (“AZ1”) is a histamine 3 (H3) autoreceptor in vivo antagonist. Sleep disturbance is a well-known class-effect for H3 antagonists and associated with high H3 receptor occupancy (RO) at night. The objective of the present work was to investigate if it was possible to obtain large diurnal fluctuations in RO for AZ1 and to suggest suitable doses for a Phase IIa study. METHODS: Four Phase I studies were pooled and used to build a population pharmacokinetic model in NONMEM. Based on simulations of the PK model and the reported Ki-value for H3 RO from a human PET-study, RO vs. time profiles were simulated. RESULTS: The model well described the AZ1 pharmacokinetics. Simulations predicting plasma concentration and RO vs. time profiles for several doses were explored and doses with a wide range of fluctuation in RO over the dosing interval could be identified. CONCLUSIONS: By using population modeling and simulations of PK data and the Ki-value from a human PET study, predictions of RO vs. time for unstudied doses of AZ1 was made. Using this methodology it was possible to suggest doses with expected large diurnal fluctuations in RO.
PURPOSE: 4-[(1S,2S)-2-(4-cyclobutylpiperazine-1-carbonyl)cyclopropyl]benzamide (“AZ1”) is a histamine 3 (H3) autoreceptor in vivo antagonist. Sleep disturbance is a well-known class-effect for H3 antagonists and associated with high H3 receptor occupancy (RO) at night. The objective of the present work was to investigate if it was possible to obtain large diurnal fluctuations in RO for AZ1 and to suggest suitable doses for a Phase IIa study. METHODS: Four Phase I studies were pooled and used to build a population pharmacokinetic model in NONMEM. Based on simulations of the PK model and the reported Ki-value for H3 RO from a human PET-study, RO vs. time profiles were simulated. RESULTS: The model well described the AZ1 pharmacokinetics. Simulations predicting plasma concentration and RO vs. time profiles for several doses were explored and doses with a wide range of fluctuation in RO over the dosing interval could be identified. CONCLUSIONS: By using population modeling and simulations of PK data and the Ki-value from a human PET study, predictions of RO vs. time for unstudied doses of AZ1 was made. Using this methodology it was possible to suggest doses with expected large diurnal fluctuations in RO.
Authors: Jorge D Brioni; Tim A Esbenshade; Tiffany Runyan Garrison; Scott R Bitner; Marlon D Cowart Journal: J Pharmacol Exp Ther Date: 2010-09-23 Impact factor: 4.030
Authors: P Bonaventure; M Letavic; C Dugovic; S Wilson; L Aluisio; C Pudiak; B Lord; C Mazur; F Kamme; S Nishino; N Carruthers; T Lovenberg Journal: Biochem Pharmacol Date: 2006-11-03 Impact factor: 5.858