Benchmarking renin suppression and blood pressure reduction of direct renin inhibitor imarikiren through quantitative systems pharmacology modeling
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.
KeywordsDirect renin inhibitor Quantitative systems pharmacology Antihypertensive drugs RAAS Renal physiology model
This study was supported by Takeda Pharmaceuticals.
Compliance with ethical standards
Conflict of interest
G. Lahu and M. Vakilynejad are/were employees of Takeda Pharmaceutical Corporation.
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