Raphaela Schenk 1, Ibrahim Ince 1, Natalja Strelkowa 1, Holger Richly 1
1 Boehringer Ingelheim Pharma Gmbh & Co. Kg (Biberach/Ingelheim, Deutschland)
Background & Objectives:
Selective aldosterone synthase inhibitors (ASi), such as vicadrostat, are being developed to prevent or slow the progression of heart failure, and to reduce the progression of chronic kidney disease (CKD). The biological complexity of adrenal steroidogenesis—including aldosterone, cortisol, and their precursors—complicates attribution of observed biomarker changes to selective aldosterone synthase inhibition alone, highlighting the need for a mechanistic framework that integrates adrenal steroidogenesis and corticosteroid dynamics. Physiological variability of corticosteroids and the close homology between CYP11B2 (aldosterone synthase) and CYP11B1 further complicate interpretation of clinical data [1,2]. We developed a mechanistic quantitative systems pharmacology (QSP) model of adrenal steroidogenesis to integrate biological knowledge and clinical biomarker data, with the objective of mechanistically interpreting corticosteroid responses to vicadrostat observed in a phase 2 trial (NCT05182840). The model centers on the dynamic interactions of aldosterone, cortisol, and their respective precursors, and includes a mechanistic assessment of the sustained suppression of aldosterone observed four weeks after treatment cessation.
Methods:
A system of Ordinary Differential Equations (ODEs) was built to represent zona glomerulosa and zona fasciculata steroidogenesis, combining mass action precursor fluxes with Michaelis–Menten kinetics for CYP11B2 and CYP11B1 mediated steps [2,3,4]. Vicadrostat was modeled as a competitive, reversible inhibitor of CYP11B2, linked to oral PK (gut → plasma → effect site). Parameters were informed by in vitro enzyme kinetics and further literature values [2,3,4,5], then calibrated to placebo data from a 14-week treatment phase 2 study with CKD patients [1]. Model validation used dosing arm aldosterone, cortisol and their precursor profiles. Sensitivity analyses assessed parameter influence on aldosterone and cortisol pathways.
Results:
The QSP model robustly reproduced the pharmacodynamic biomarker profiles observed in phase 2 [1]. Simulations captured (i) strong aldosterone suppression, (ii) accumulation of aldosterone precursors (11 deoxycorticosterone, corticosterone), and (iii) elevation of the cortisol precursor 11 deoxycortisol.
By explicitly representing CYP11B1 and CYP11B2 mediated fluxes and baseline pool sizes, the model provides a mechanistic explanation for these observed patterns, showing why cortisol concentrations remain stable despite increased precursor levels.
Even though CYP11B2 is, additionally to CYP11B1, active in the pathway 11-deoxycortisol -> cortisol, the baseline of cortisol is orders of magnitude higher than its precursors’ baseline. The very large baseline level of cortisol and its high production via CYP11B1 yields low sensitivity to CYP11B2 inhibition.
No rebound in aldosterone after treatment cessation was predicted, reflecting slow CYP11B2 turnover and partial day exposure of vicadrostat with reported half-life of 4.4-6.3 hours [5]. This indicates that inhibitors with a short half-life exhibit strong efficacy in aldosterone suppression and allow for rapid restoration of adrenal steroidogenesis. Sensitivity analysis confirmed that aldosterone is highly sensitive to CYP11B2 catalytic capacity, whereas cortisol remains robust to perturbations in the aldosterone branch.
Conclusion:
This mechanistic QSP framework highlights the selective inhibition of aldosterone synthesis by vicadrostat, while maintaining cortisol balance. The model robustly explains the clinical biomarker responses observed and analysed before [1] and thus reinforces the safety profile of vicadrostat. Importantly, it offers a quantitative basis for ongoing and future investigations into aldosterone synthase inhibition over time. As additional data from ongoing phase 3 trials become available, the model will be further enriched to enable comprehensive assessment of long-term effects on adrenal steroidogenesis and to support the development of further treatment strategies.
References:
[1] Gashaw I.A., Tuttle K.R., Monroy Kuhn M., Pleiner S., Delic D., Cronin L., Shah S.V., Rossing P.
Pharmacodynamics of vicadrostat for aldosterone synthase inhibition in patients with CKD.
European Journal of Endocrinology, 194(1):46–57, January 2026.
[2] Strushkevich N., Gilep A.A., Shen L., Arrowsmith C.H., Edwards A.M., Usanov S.A., Park H‑W.
Structural insights into aldosterone synthase substrate specificity and targeted inhibition.
Mol. Endocrinol. 27:315–324, 2013.
[3] Hobler A., Kagawa N., Hutter M.C., Hartmann M.F., Wudy S.A., Hannemann F., Bernhardt R.
Human aldosterone synthase: recombinant expression in E. coli and purification enables a detailed biochemical analysis of the protein on the molecular level.
J. Steroid Biochem. Mol. Biol. 132:57–65, 2012.
[4] Weldon S.M., Cogan D.A., Cerny M.A., Frederick K., Gueneva‑Boucheva K., Clifford H., et al.
Pharmacodynamic effects of highly selective aldosterone synthase inhibitor vicadrostat in cynomolgus monkeys; contrasting effects of once vs twice daily dosing.
Journal of Pharmacology and Experimental Therapeutics, 2025.
[5] Schulze F., Schaible J., Goettel M., Tanaka Y., Hohl K., Schultz A., Jang I.-J.
Phase 1 studies of the safety, tolerability, pharmacokinetics, and pharmacodynamics of BI 690517 (vicadrostat), a novel aldosterone synthase inhibitor, in healthy male volunteers.
Reference: PAGE 34 (2026) Abstr 12239 [www.page-meeting.org/?abstract=12239]
Poster: Drug/Disease Modelling - Endocrine