Literature DB >> 23584887

Mechanistic pharmacokinetic-pharmacodynamic modeling of BACE1 inhibition in monkeys: development of a predictive model for amyloid precursor protein processing.

Xingrong Liu1, Harvey Wong, Kimberly Scearce-Levie, Ryan J Watts, Melis Coraggio, Young G Shin, Kun Peng, Kristin R Wildsmith, Jasvinder K Atwal, Jason Mango, Stephen P Schauer, Kelly Regal, Kevin W Hunt, Allen A Thomas, Michael Siu, Joseph Lyssikatos, Gauri Deshmukh, Cornelis E C A Hop.   

Abstract

This study was conducted to determine the pharmacokinetics (PK) and pharmacodynamics (PD) of two novel inhibitors of β-site amyloid precursor protein (APP)-cleaving enzyme (BACE1), GNE-629 [(4S,4a'S,10a'S)-2-amino-8'-(2-fluoropyridin-3-yl)-1-methyl-3',4',4a',10a'-tetrahydro-1'H-spiro[imidazole-4,10'-pyrano[4,3-b]chromen]-5(1H)-one] and GNE-892 [(R)-2-amino-1,3',3'-trimethyl-7'-(pyrimidin-5-yl)-3',4'-dihydro-2'H-spiro[imidazole-4,1'-naphthalen]-5(1H)-one], and to develop a PK-PD model to predict in vivo effects based solely on in vitro activity and PK. GNE-629 and GNE-892 concentrations and PD biomarkers including amyloid β (Aβ) in the plasma and cerebrospinal fluid (CSF), and secreted APPβ (sAPPβ) and secreted APPα (sAPPα) in the CSF were measured after a single oral administration of GNE-629 (100 mg/kg) or GNE-892 (30 or 100 mg/kg) in cynomolgus monkeys. A mechanistic PK-PD model was developed to simultaneously characterize the plasma Aβ and CSF Aβ, sAPPα, and sAPPβ using GNE-629 in vivo data. This model was used to predict the in vivo effects of GNE-892 after adjustments based on differences in in vitro cellular activity and PK. The PK-PD model estimated GNE-629 CSF and free plasma IC₅₀ of 0.0033 μM and 0.065 μM, respectively. These differences in CSF and free plasma IC₅₀ suggest that different mechanisms are involved in Aβ formation in these two compartments. The predicted in vivo effects for GNE-892 using the PK-PD model were consistent with the observed data. In conclusion, a PK-PD model was developed to mechanistically describe the effects of BACE1 inhibition on Aβ, sAPPβ, and sAPPα in the CSF, and Aβ in the plasma. This model can be used to prospectively predict in vivo effects of new BACE1 inhibitors using just their in vitro activity and PK data.

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Year:  2013        PMID: 23584887     DOI: 10.1124/dmd.112.050864

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  9 in total

Review 1.  Clinical Pharmacokinetics and Pharmacodynamics of Drugs in the Central Nervous System.

Authors:  Nithya Srinivas; Kaitlyn Maffuid; Angela D M Kashuba
Journal:  Clin Pharmacokinet       Date:  2018-09       Impact factor: 6.447

2.  Dose-dependent exposure and metabolism of GNE-892, a β-secretase inhibitor, in monkeys: contributions by P450, AO, and P-gp.

Authors:  Ryan Takahashi; Shuguang Ma; Qin Yue; Heasook Kim-Kang; Yijun Yi; Joseph P Lyssikatos; Kelly Regal; Kevin W Hunt; Nicholas C Kallan; Michael Siu; Cornelis E C A Hop; Xingrong Liu; S Cyrus Khojasteh
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2014-04-03       Impact factor: 2.441

3.  Multilevel pharmacokinetics-driven modeling of metabolomics data.

Authors:  Emilia Daghir-Wojtkowiak; Paweł Wiczling; Małgorzata Waszczuk-Jankowska; Roman Kaliszan; Michał Jan Markuszewski
Journal:  Metabolomics       Date:  2017-02-08       Impact factor: 4.290

4.  Pharmacodynamics of atabecestat (JNJ-54861911), an oral BACE1 inhibitor in patients with early Alzheimer's disease: randomized, double-blind, placebo-controlled study.

Authors:  Maarten Timmers; Johannes Rolf Streffer; Alberto Russu; Yushin Tominaga; Hiroko Shimizu; Ayako Shiraishi; Kanaka Tatikola; Pascale Smekens; Anne Börjesson-Hanson; Niels Andreasen; Jorge Matias-Guiu; Miquel Baquero; Mercè Boada; Ina Tesseur; Luc Tritsmans; Luc Van Nueten; Sebastiaan Engelborghs
Journal:  Alzheimers Res Ther       Date:  2018-08-23       Impact factor: 6.982

Review 5.  Interpreting Alzheimer's disease clinical trials in light of the effects on amyloid-β.

Authors:  Jeremy H Toyn; Michael K Ahlijanian
Journal:  Alzheimers Res Ther       Date:  2014-03-12       Impact factor: 6.982

6.  Prospective Design of Anti-Transferrin Receptor Bispecific Antibodies for Optimal Delivery into the Human Brain.

Authors:  J S Kanodia; K Gadkar; D Bumbaca; Y Zhang; R K Tong; W Luk; K Hoyte; Y Lu; K R Wildsmith; J A Couch; R J Watts; M S Dennis; J A Ernst; K Scearce-Levie; J K Atwal; S Ramanujan; S Joseph
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2016-05-17

Review 7.  BACE1 Function and Inhibition: Implications of Intervention in the Amyloid Pathway of Alzheimer's Disease Pathology.

Authors:  Gerald Koelsch
Journal:  Molecules       Date:  2017-10-13       Impact factor: 4.411

8.  Quantitative Systems Pharmacology Model for Alzheimer Disease Indicates Targeting Sphingolipid Dysregulation as Potential Treatment Option.

Authors:  Diana Clausznitzer; Cesar Pichardo-Almarza; Ana Lucia Relo; Jeroen van Bergeijk; Elizabeth van der Kam; Loic Laplanche; Neil Benson; Marjoleen Nijsen
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2018-10-08

9.  Systematic in silico analysis of clinically tested drugs for reducing amyloid-beta plaque accumulation in Alzheimer's disease.

Authors:  Kumpal Madrasi; Raibatak Das; Hafiz Mohmmadabdul; Lin Lin; Bradley T Hyman; Douglas A Lauffenburger; Mark W Albers; Robert A Rissman; John M Burke; Joshua F Apgar; Lucia Wille; Lore Gruenbaum; Fei Hua
Journal:  Alzheimers Dement       Date:  2021-05-02       Impact factor: 21.566

  9 in total

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