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Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
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Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
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Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab

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Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab
Journal Article

Population pharmacokinetics/pharmacodynamics analysis confirming biosimilarity of SB16 to reference denosumab

2025
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Overview
This analysis aims to evaluate the population pharmacokinetics (PK) and pharmacodynamics (PD) of denosumab and applied a population PK/PD approach to assess the biosimilarity of SB16 in comparison to reference product, denosumab (DEN). Pooled serum concentrations data for SB16 and DEN from male healthy volunteers (HV) in the Phase I and from postmenopausal women with osteoporosis (PMO) Phase III studies, along with lumbar spine bone mineral density (BMD) data from Phase III study, were analyzed using a nonlinear mixed effects population PK/PD sequential modeling approach. The effects of key patient variables on PK/PD parameters were assessed. Treatment effects on clearance (CL) were retained in the model, regardless of statistical significance, to enable comparative simulation between SB16 and DEN. Modeling and simulation were performed using Monolix Suite™. A two-compartment target-mediated drug disposition (TMDD) model with quasi-steady state (QSS) approximation and first-order absorption adequately characterized the PK profile of denosumab. An indirect response model with maximal inhibitory function captured changes in lumbar spine BMD following treatment. The study population had a minimal effect on drug exposure and on changes in BMD, with <5% difference. Race and body weight accounted for up to 19% and 45% of the variability in drug exposure, respectively, but these differences translated into less than a 2% difference in changes in BMD for each covariate. The treatment group (SB16 vs. DEN) was not identified as a significant covariate. Including this factor on CL in the final PK/PD model, irrespective of its statistical significance, did not affect the PK/PD parameter estimates. Comparative simulations showed similar results for both treatment groups. The developed TMDD-QSS model with indirect response model adequately characterized the PK/PD profile of denosumab. Covariate effects, including study population (HV vs. PMO), age, and race showed no clinically meaningful impact on treatment outcomes. Covariate analysis and simulation results revealed no significant differences in PK/PD parameters between SB16 and DEN. The similarity in the PK profile and change in lumbar spine BMD between SB16 and DEN were demonstrated, supporting the potential for SB16 to be substituted for the reference product in the treatment of osteoporosis.