Vincent Croixmarie1, Caroline Apert-Maarek2, Sylvain Fouliard1
1Quantitative Pharmacology, Translational Medicine, Servier, 2Cardiometabolic & Venous Diseases Life Cycle Management, Servier
Objectives: An estimated 1.4 billion people globally have high blood pressure (BP), but only 14% have it under control, making elevated BP a leading cause of premature death and disability. Both the 2023 European Society of Hypertension (ESH) and the 2024 European Society of Cardiology (ESC) Guidelines[1,2] recommend the use of fixed dose combinations (FDCs) to improve treatment adherence and BP control, with three-drug combinations potentially controlling BP in up to 90% of patients. In hypertension, reduction of BP is considered a valid surrogate endpoint[3]. The development of an FDC candidate, combining Perindopril, Indapamide and Bisoprolol, can then be supported by PK/PD modeling to assess the contribution of each mono-component, as required by EMA guidelines for development of FDC[4]. Our work aimed at characterizing the PK/PD relationship between drug concentration and systolic BP in monotherapy or in combo, in a framework allowing to separate system-related and drug-related parameters. The assessment of PD interactions is a major objective of the modeling activity with the exploration of sources of variability. Methods: Data originated from six clinical trials involving single-dose administrations of Perindopril (4 and 8 mg), Indapamide (1.25 to 2.5 mg), and Bisoprolol (10 mg), in monotherapy or as a combination of 2 or 3 drugs. The PK dataset included 319 participants, with a total of 12128, 8707 and 6011 PK observations for Perindopril, Indapamide and Bisoprolol, respectively and 4716 systolic blood pressure (SBP) observations used to inform the population PK/PD models. PK and PK/PD assessments thus followed an extensive sampling design. Nonlinear mixed effects modeling with Monolix software version 2023R1[5] has been used for population PK/PD model building through a sequential modeling approach. First, monotherapy arms were used to build three independent population PK/PD models. Then dual-drugs related arms were included into the datasets to estimate the related “dual-drug” interaction term (a_xy): effect(C_x ,C_y ) = effect(C_x ) + effect(C_y ) – a_xy*(effect(C_x )*effect( C_y )) The full dataset was then used to assess the “tri-drug” interaction term: effect(C_x ,C_y,C_z ) = (effect(C_x ,C_y ) + effect(C_x ,C_z ) + effect(C_y ,C_z ))/2 – a_xyz*(effect(C_x ,C_y )*effect(C_x ,C_z )*effect(C_y ,C_z )) Although the dataset consisted in HV population, a covariate analysis was performed for population PK and PK/PD models to investigate how age, gender, body weight, creatinine clearance, formulation-related parameters and ethnicity could affect some parameters. Results: The final PK models provided a robust description of the PK profiles for each drug, with a very rich sampling schedules enabling accurate parameter estimation. For Perindopril, the active metabolite Perindoprilat was modelled directly. A three-compartment model with first-order absorption and transit compartments was selected. Indapamide PK was best described by a two-compartment model with first-order absorption and a lag time. Two set of absorption parameters have been used to account for immediate-release (IR) and sustained-release (SR) formulations. Bisoprolol PK was characterized by a two-compartment model with first-order absorption and a lag time. The PK/PD relationship with SBP was described with turnover models with inhibition of the production kin, baseline response R0, degradation rate kout, maximal fraction of inhibition Imax, and half-maximal inhibitory concentration IC50 were kept. The estimated interaction parameter value for the Perindoprilat/Indapamide showed a less than additive effect, while estimated value for the Perindoprilat/Bisoprolol combo showed a slightly less than additive effect. With three drugs the interaction parameter was found to be non-different from zero, showing an additive effect of this combo. The covariate analysis identified significant relationships such as gender, weight, and ethnicity affecting SBP baseline levels. Gender-specific differences and body-weight association with SBP baseline were consistent with literature[6]. Conclusion: This comprehensive PK/PD modeling study provided valuable insights for the PK and PD of Perindopril, Indapamide, and Bisoprolol in HV and their interaction. A clear additive effect was observed for the tri-therapy combination. The models developed in this study are robust and can be used for further simulations and predictions of drug effects in HV. Overall, this study contributes to the understanding of the PK and PD relationships of commonly used antihypertensive drugs and their combinations and could support the development of FDC therapies against hypertension, providing a foundation for future clinical trials and therapeutic strategies. Keywords: Pharmacokinetics, Pharmacodynamics, Population Modeling, Hypertension, Perindopril, Indapamide, Bisoprolol, Fixed-Dose Combination, Covariate Analysis, Healthy Volunteers.
[1] Mancia G, Kreutz R, Brunstrom M. 2023 ESH Guidelines for the management of arterial hypertension. The Task Force for the management of arterial hypertension of the European Society of Hypertension. J Hypertens. 2023;41 (in press). [2] McEvoy JW, McCarthy CP & All 2024 ESC Guidelines for the management of elevated blood pressure and hypertension. 2024; 00, 1-107. [3] Guideline on clinical investigation of medicinal products in the treatment of hypertension (23 June 2016) EMA/CHMP/29947/2013/Rev4, Committee for Human Medicinal Products (CHMP) [4] Guideline on clinical development of fixed combination medicinal products (23 March 2017) EMA/CHMP/158268/2017, Committee for Human Medicinal Products (CHMP) [5] Monolix 2023R1, Lixoft SAS, a Simulations Plus company [6] Maranon R, Reckelhoff JF. Sex and gender differences in control of BP. Clin Sci (Lond). 2013 Oct;125(7):311-8. doi: 10.1042/CS20130140. PMID: 23746374; PMCID: PMC4283814.
Reference: PAGE 33 (2025) Abstr 11385 [www.page-meeting.org/?abstract=11385]
Poster: Drug/Disease Modelling - Other Topics