Letizia Carrara 1, Rami Ayoun Alsoud 2, Marie Wijk 2, Ida Neldemo 2, Giovanni Smania 2, Virginia Ginocchio 1, Martin Bergstrand 2, Massimiliano Germani 1
1 Chiesi Farmaceutici S.p.A. (, ), 2 Pharmetheus AB (Uppsala, )
Introduction: Clevidipine is an intravenous L‑type calcium channel blocker administered intravenously (IV) for the rapid reduction of blood pressure (BP) in settings where tight and predictable BP control is required. Its metabolic profile, characterized by rapid distribution, metabolism by non‑specific carboxylesterases (CES), and a short terminal half‑life of approximately 15 minutes, supports fast onset and offset of effect, with systolic BP reductions observable within minutes of infusion initiation. Although clevidipine has been extensively studied in adults, its use in pediatric populations need to be systematically evaluated.
Objectives: To support the design of an upcoming pediatric study in terms of dose selection, PK sampling schedule and sample size.
Methods: The analysis included data from two studies in adults and one small study in adolescents. Nonlinear mixed effects modeling (using Nonmem version 7.5) was used for population PK and PKPD models development. Clearance and volume parameters were allometrically scaled by body weight. A maturation function on elimination clearance (CL) was included to account for CES ontogeny [1]. Other potential covariates were explored through the stepwise covariate modeling procedure with adaptive scope reduction [2]. The final models were used to simulate steady-state concentration (Css) and relative change from baseline BP at steady state, with the aim of selecting the best candidate dosing strategy for the following age groups: 12 to < 18 years, 6 to < 12 years, 2 to < 6 years, 28 days to < 2 years, 0 to < 28 days. In addition, the final PK model was used to evaluate the proposed pediatric study design with respect to PK sampling times and sample size, using the workflow presented in [3]. The design was evaluated in terms of predicted Relative Standard Errors (RSEs) as well as the power to obtain a 95% Confidence Interval (CI) within 0.6 and 1.4 of the geometric mean estimates for CL and central volume of distribution (Vc) in each pediatric sub-group [4]. The variance-covariance matrix obtained for the final PK model in the present analysis was used as a prior for clearance and volume parameters. Moreover, a weak prior on maturation function parameters based on their in vitro values was included. Results: A two-compartment PK model with first-order elimination best described the PK of clevidipine. Age and body weight were found to be relevant predictors of clevidipine exposure, consistent with physiological expectations for a high clearance drug metabolized by ubiquitous esterases. The PKPD relationship for BP was best described by a direct Emax model with a mono exponential placebo component. PK simulations indicated that, in pediatric population a weight & age-based dosing best matched the target exposure in adults. PKPD simulations confirmed the adequacy of the proposed pediatric dosing strategy. Design evaluation indicated that maturation function parameters are not expected to be reliably estimated with the proposed design (predicted RSE>60%). Nevertheless, the associated relative 95% CI for the geometric mean estimate of CL was within 0.6 and 1.4 in terms of median, translating into a study power of ~90% for CL considering an age range of 0 to <18 years. On the other hand, the power for Vc was low. However, because Css depends solely on clearance for a continuous infusion, the limited precision in Vc does not compromise the ability of the study to characterize exposure or support subsequent PKPD analyses. Conclusions: The final PK model was deemed fit‑for‑purpose for predicting pediatric infusion rates and for evaluating the proposed study design. The assessment of sampling times and sample size supports the adequacy of the proposed design to characterize clearance with the required precision, thereby enabling robust model‑based inference in the upcoming pediatric trial. References: [1] Boberg M, Vrana M, Mehrotra A, Pearce RE, Gaedigk A, Bhatt DK, et al. Age-Dependent Absolute Abundance of Hepatic Carboxylesterases (CES1 and CES2) by LC-MS/MS Proteomics: Application to PBPK Modeling of Oseltamivir In Vivo Pharmacokinetics in Infants. Drug Metabolism and Disposition. 2017;45(2):216-23. [2] Jonsson EN, Harling K. Increasing the Efficiency of the Covariate Search Algorithm in the SCM [Internet]. Leiden: Population Approach Group in Europe; 2018. Available from: www . page-meeting . org/default . asp ? abstract =8429. [3] Ibrahim M, Hansson E, Hooker AC, Bergstrand M. A workflow for evaluating and optimizing the designs of paediatric studies [Internet]. Rome: Population Approach Group in Europe; 2024 [cited 2024 Mar 26]. Available from: www.page-meeting.org/?abstract=11082. [4] Wang Y, Jadhav PR, Lala M, Gobburu JV. Clarification on Precision Criteria to Derive Sample Size When Designing Pediatric Pharmacokinetic Studies. J Clin Pharmacol. 2012;52(10):1601-6.
Reference: PAGE 34 (2026) Abstr 12161 [www.page-meeting.org/?abstract=12161]
Poster: Clinical Applications