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Benchmarking renin suppression and blood pressure reduction of direct renin inhibitor imarikiren through quantitative systems pharmacology modeling.

Authors :
Gebremichael Y
Lahu G
Vakilynejad M
Hallow KM
Source :
Journal of pharmacokinetics and pharmacodynamics [J Pharmacokinet Pharmacodyn] 2019 Feb; Vol. 46 (1), pp. 15-25. Date of Electronic Publication: 2018 Nov 16.
Publication Year :
2019

Abstract

Multiple classes of antihypertensive drugs inhibit components of the renin-angiotensin-aldosterone system (RAAS). The primary physiological effector of the RAAS is angiotensin II (AngII) bound to the AT1 receptor (AT1-bound AngII). There is a strong non-linear feedback from AT1-bound AngII on renin secretion. Since AT1-bound AngII is not readily measured experimentally, plasma renin concentration (PRC) and/or activity (PRA) are typically measured to indicate RAAS suppression. We investigated the RAAS suppression of imarikiren hydrochloride (TAK-272; SCO-272), a direct renin inhibitor currently under clinical development. We employed a previously developed quantitative system pharmacology (QSP) model to benchmark renin suppression and blood pressure regulation with imarikiren compared to other RAAS therapies. A pharmacokinetic (PK) model of imarikiren was linked with the existing QSP model, which consists of a mechanistic representation of the RAAS pathway coupled with a model of blood pressure regulation and volume homeostasis. The PK and pharmacodynamic effects of imarikiren were calibrated by fitting drug concentration, PRA, and PRC data, and trough AT1-bound AngII suppression was simulated. We also prospectively simulated expected mean arterial pressure reduction in a cohort of hypertensive virtual patients. These predictions were benchmarked against predictions for several other (previously calibrated) RAAS monotherapies and dual-RAAS therapies. Our analysis indicates that low doses (5-10 mg) of imarikiren are comparable to current RAAS therapies, and at higher doses (25-200 mg), RAAS suppression may be equivalent to existing dual-RAAS combinations (at registered doses). This study illustrates application of QSP modeling to predict phase II endpoints from phase I data.

Details

Language :
English
ISSN :
1573-8744
Volume :
46
Issue :
1
Database :
MEDLINE
Journal :
Journal of pharmacokinetics and pharmacodynamics
Publication Type :
Academic Journal
Accession number :
30443840
Full Text :
https://doi.org/10.1007/s10928-018-9612-y