Huong Tra Dang1, Hyunjung Lee2, Seongwon Park1, Lien Thi Ngo1, Soyoung Lee1, Hwi-Yeol Yun1,2,3, Jung-woo Chae1,2,3
1College of Pharmacy, Chungnam National University, Daejeon, Republic of Korea, 2Department of Bio-AI convergence, Chungnam National University, Daejeon, Republic of Korea, 3Senior Health Convergence Research Center, Chungnam National University, Chungnam National University
Type: Posters: Drug/Disease Modelling – Other Topics Objectives Ivabradine (IVA) is a selective inhibitor of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, used for managing heart failure and chronic stable angina, especially in patients with heart failure with reduced ejection fraction (HFrEF). It mainly inhibits the “funny current” (If) in the sinoatrial node, affecting the heart rate (HR). Its active metabolite also has bradycardic effects. Factors like concurrent medications can impact on the pharmacokinetics (PK) of IVA and its metabolite. This study aimed to develop a Physiologically Based Pharmacokinetics/Pharmacodynamics (PBPK/PD) model for IVA to characterize its PK profiles and predict HR effects, with validation against clinical data for dose optimization strategies. Methods The PBPK model for IVA and its metabolite, S18982, was developed using the PK-Sim software from Open Systems Pharmacology. Clinical PK data for IVA and S18982 were obtained from prior clinical trial publications. This data was digitized using the WebPlotDigitizer tool and analyzed in Microsoft Excel. Research for relevant studies on IVA and S18982 were conducted in the National Library of Medicine (Pubmed). The studies encompassed a dose range from 2.5 to 20 mg, administered as either a single dose or repeated doses of IVA. For the model’s development, parameters such as metabolic enzyme activities, lipophilicity, intestinal permeability, and dissolution profiles were estimated for IVA and its metabolite. After evaluating the model, to account for IVA’s pharmacodynamic (PD) effects on HR reduction, the PBPK model was extended to a PBPK-PD model in Mobi software. This extension incorporated a direct Response model utilizing an Emax function based on the published population PBPK/PD models, which can accurately represent the saturable response of HR reduction, align with physiological constraints, and reflect the mechanistic rationale of receptor-mediated drug action. Results Using clinical data from 5 trials, a PBPK model was developed in PK-Sim. The model of IVA and its metabolite, S18982, effectively captured the PK profiles across Asian and European individuals. The dose regimen includes 2.5, 5, 10, and 20mg in single and multiple doses. Key parameters were optimized, after simulations, the estimates were as follows: for IVA, fu 31%, logP 2.1, specific intestinal permeability 1.87E-6 cm/s, and specific CYP3A4 clearance of 15.27 µM/min/mg protein (9.51 µM/min/mg protein for the formation of S18982 and 5.76 µM/min/mg protein for the formation of other metabolites besides S18982); for S18982, fraction unbound 26.73%, logP 2.03, and specific CYP3A4 clearance of 15.93 µM/min/mg protein. Model evaluation through observed versus predicted concentration plots revealed strong concordance, with most data points falling within a 2-fold error range, an MRD value of 1.07, and GMFEs of 1.43. Additionally, with the inclusion of a PK/PD extension, the model was based on the published population PK/PD model using an indirect Emax model, which facilitated the simulation of Ivabradine’s effects on HR reduction. The developed PK/PD models describe the observed PD effect profiles of ivabradine S18982 well, with more than 80% of the observed value lying within a 95% confidence interval. Conclusion The developed PBPK model for IVA and its metabolite, S18982, demonstrated high predictive accuracy across different populations, effectively capturing PK profiles and supporting its applicability in diverse clinical settings. Integrating a PBPK-PD extension successfully characterized Ivabradine’s PD effects on HR reduction, enhancing its potential for dose optimization and personalized therapy. Overall, this PBPK/PD modeling approach is valuable for optimizing IVA therapy, aiding in individualized treatment strategies, and improving patient outcomes.
[1] Younis NK, Abi-Saleh B, Amin F Al, Sedawi O El, Tayeh C, Bitar F, et al. Ivabradine: A Potential Therapeutic for Children With Refractory SVT. Front Cardiovasc Med. 2021;8. [2] Babu KS, Gadzik F, Holgate ST. Absence of Respiratory Effects With Ivabradine in Patients With Asthma. Br J Clin Pharmacol. 2008;66(1):96–101. [3] Depuydt A, Peigneur S, Tytgat J. Review: HCN Channels in the Heart. Curr Cardiol Rev. 2022;18(4). [4] Choi HY, Bae K, Cho SH, Ghim JL, Choe S, Jung JA, et al. Population Plasma and Urine Pharmacokinetics of Ivabradine and Its Active Metabolite S18982 in Healthy Korean Volunteers. The Journal of Clinical Pharmacology. 2015;56(4):439–49. [5] Rajendram R, AlDhahri F, Mahmood N, Kharal M. The Use of Ivabradine in a Patient With Inappropriate Sinus Tachycardia and Cardiomyopathy Due to Limb Girdle Muscular Dystrophy Type 2I. BMJ Case Rep. 2020;13(1):e230647. [6] Lang JM, Vincent L, Chenel M, Ogungbenro K, Galetin A. Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically-Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study. Clin Pharmacol Ther. 2020;109(6):1618–30. [7] Cheng L, Wong H. Food Effects on Oral Drug Absorption: Application of Physiologically-Based Pharmacokinetic Modeling as a Predictive Tool. Pharmaceutics. 2020;12(7):672. [8] Doctor P, Scott W, Tindel K, Nguyen HH. Ivabradine Overdose in a Newborn: Precautions of Dispensing in Infants. Cardiol Res. 2022;13(4):242–5.
Reference: PAGE 33 (2025) Abstr 11389 [www.page-meeting.org/?abstract=11389]
Poster: Drug/Disease Modelling - Other Topics