Seung Chan Choi1,2, Langdahl Bente3, Eastell Richard4, Siook Baek5, Jinah Jung5, Yoon-Sok Chung6, Jung Min Koh2, Jeonghoon Ha7, Suemin Park1, Hyeong Seok Lim1,2
1Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, 2Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 3Aarhus University Hospital and Department of Clinical Medicine, Aarhus University, 4University of Sheffield, 5Samsung Bioepis Co., Ltd, 6Ajou University School of Medicine, Suwon, Republic of Korea; Institute on Aging, Ajou University Medical Center, 7St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea; Stanford University School of Medicine, Stanford
Introduction: SB16 was developed as a biosimilar to Prolia (reference denosumab; RP) and is approved under the brand name Obodence™ in Europe and Ospomyv™ in the United States (US). Denosumab inhibits the activation of receptor activator of nuclear factor kappa B ligand (RANKL) on osteoclasts and their precursors, reducing bone resorption and increasing bone mass. SB16 is approved for the treatment of osteoporosis in postmenopausal women and men at high fracture risk, as well as bone loss associated with prostate cancer hormone ablation therapy or long-term systemic glucocorticoid therapy [1]. This study aimed to characterize the population pharmacokinetics (PK) and pharmacodynamics (PD) of denosumab in healthy men and postmenopausal women with osteoporosis. The PK-PD modelling assessed the relationship between denosumab concentration and its effects on bone mineral density (BMD)The modeling approach also evaluated PK similarity between SB16 and RP and the impact of denosumab concentration on lumbar spine BMD. Methods: Data from a Phase I study in healthy men (NCT04621318) and a Phase III study in postmenopausal women with osteoporosis (NCT04664959) were used to construct PK and PK-PD model [2,3]. Denosumab concentrations (number of observations, SB16: 2023, EU sourced RP: 1924, US sourced RP: 892) and BMD (SB16: 1007, EU sourced RP: 709) were analyzed. Covariate effects for the clinically relevant variables including body weight, age, and race were evaluated on the PK parameters. PK comparability between SB16 and the RP from EU and US was evaluated by assessing treatment effects on the PK parameter. This included statistical tests such as the Wald statistics test and likelihood ratio tests for hierarchical models. The PK-PD model was validated through visual predictive check plots. Simulations were carried out to compare the pre-dose trough concentration (Ctrough), maximum concentration (Cmax), area under the concentration-time curve over dosing interval (t) at steady state (AUCt,ss), and lumbar spine BMD between SB16 and RP. Modeling was carried out using Monolix, with data processing and plotting using R software v4.3.2 [4]. Results: The quasi steady-state (Qss) model within the target-mediated drug disposition (TMDD) framework accurately described the PK of denosumab [5, 6]. A turnover model with inhibitor effect on bone resorption effectively captured the drug’s effect on BMD, showing good agreement with the observed data [7]. Covariate assessment showed that treatments (i.e., SB16 versus RP) on CL (clearance), ka (absorption rate constant), and Vd (volume of distribution) did not affect the model, indicating that SB16 is similar to RP in terms of PK profile (e.g., CL: 0.0061 L/h vs. 0.0062 L/h). Consequently, the typical value of Vd, adjusted for weight, was 1.79 L (95% confidence interval, CI: 1.61-1.99) and CL in a Caucasian patients was 0.006 L/h (95% CI: 0.0059-0.0063). The maximum inhibitory effect on bone resorption was 0.34 and half-maximal inhibitory concentration was 35.63 nM/L. Additionally, simulations showed no differences in PK and PD profiles by treatments. Conclusion: The developed TMDD model with turnover model effectively characterized the PK/PD profile of denosumab. Based on the modeling and simulation results, our research supports PK and PD similarities of SB16 to reference denosumab.
[1] European Medicines Agency. (2025). European Public Assessment Report for ObodenceTM (denosumab) Available at: https://www.ema.europa.eu/en/medicines/human/EPAR/obodence [2] Samsung Bioepis Co., Ltd. (2022) Clinical study report for A randomised, double-blind, three-arm, parallel group, single-dose study to compare the pharmacokinetics, pharmacodynamics, safety, tolerability, and immunogenicity of denosumab (SB16, EU sourced Prolia, and US sourced Prolia) in healthy male subjects. [SB16-1001] Samsung Bioepis. [3] Samsung Bioepis Co., Ltd. (2022) Clinical study report for a Phase III, Randomised, Double-blind, Multicentre Clinical Study to Compare the Efficacy, Safety, Pharmacokinetics, Pharmacodynamics, and Immunogenicity between SB16 (proposed denosumab biosimilar) and Prolia in Postmenopausal Women with Osteoporosis. [SB16-3001] Samsung Bioepis. [4] R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria, 2018. https://www.R-project.org/ [5] Gibiansky, L., Gibiansky, E., Kakkar, T. et al. Approximations of the target-mediated drug disposition model and identifiability of model parameters. J Pharmacokinet Pharmacodyn 35, 573–591 (2008). https://doi.org/10.1007/s10928-008-9102-8 [6] Sutjandra, L., Rodriguez, R.D., Doshi, S. et al. Population Pharmacokinetic Meta-Analysis of Denosumab in Healthy Subjects and Postmenopausal Women with Osteopenia or Osteoporosis. Clin Pharmacokinet 50, 793–807 (2011). https://doi.org/10.2165/11594240-000000000-00000 [7] Gabrielsson J and Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications, 5th Edition. Apotekarsocieteten. Section 2.5 Turnover.
Reference: PAGE 33 (2025) Abstr 11375 [www.page-meeting.org/?abstract=11375]
Poster: Drug/Disease Modelling - Other Topics