caa a22 4500 605533997 CHVBK 20210128100840.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s10928-015-9422-4 doi (NATIONALLICENCE)springer-10.1007/s10928-015-9422-4 Using early biomarker data to predict long-term bone mineral density: application of semi-mechanistic bone cycle model on denosumab data [Elektronische Daten] [Jenny Zheng, Erno van Schaick, Liviawati Wu, Philippe Jacqmin, Juan Perez Ruixo] Osteoporosis is a chronic skeletal disease characterized by low bone strength resulting in increased fracture risk. New treatments for osteoporosis are still an unmet medical need because current available treatments have various limitations. Bone mineral density (BMD) is an important endpoint for evaluating new osteoporosis treatments; however, the BMD response is often slower and less profound than that of bone turnover markers (BTMs). If the relationship between BTMs and BMD can be quantified, the BMD response can be predicted by the changes in BTM after a single dose; therefore, a decision based on BMD changes can be informed early. We have applied a bone cycle model to a phase 2 denosumab dose-ranging study in osteopenic women to quantitatively link serum denosumab pharmacokinetics, BTMs, and lumbar spine (LS) BMD. The data from two phase 3 denosumab studies in patients with low bone mass, FREEDOM and DEFEND, were used for external validation. Both internal and external visual predictive checks demonstrated that the model was capable of predicting LS BMD at the denosumab regimen of 60mg every 6months. It has been demonstrated that the model, in combination with the changes in BTMs observed from a single-dose study in men, is capable of predicting long-term BMD outcomes (e.g., LS BMD response in men after 1year of treatment) in different populations. We propose that this model can be used to inform drug development decisions for osteoporosis treatment early via evaluating LS BMD response when BTM data become available in early trials. Springer Science+Business Media New York, 2015 Osteoporosis nationallicence Pharmacokinetics nationallicence Pharmacodynamics nationallicence Bone remodeling nationallicence Denosumab nationallicence Zheng Jenny Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut van Schaick Erno SGS Exprimo NV, Generaal de Wittelaan 19A b5, 2800, Mechelen, Belgium aut Wu Liviawati Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut Jacqmin Philippe SGS Exprimo NV, Generaal de Wittelaan 19A b5, 2800, Mechelen, Belgium aut Perez Ruixo Juan Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut Journal of Pharmacokinetics and Pharmacodynamics Springer US; http://www.springer-ny.com 42/4(2015-08-01), 333-347 1567-567X 42:4<333 2015 42 10928 https://doi.org/10.1007/s10928-015-9422-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10928-015-9422-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zheng Jenny Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut NATIONALLICENCE 700 1- van Schaick Erno SGS Exprimo NV, Generaal de Wittelaan 19A b5, 2800, Mechelen, Belgium aut NATIONALLICENCE 700 1- Wu Liviawati Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut NATIONALLICENCE 700 1- Jacqmin Philippe SGS Exprimo NV, Generaal de Wittelaan 19A b5, 2800, Mechelen, Belgium aut NATIONALLICENCE 700 1- Perez Ruixo Juan Pharmacokinetics and Drug Metabolism Division, Amgen Inc., One Amgen Center Drive, 91320, Thousand Oaks, CA, USA aut NATIONALLICENCE 773 0- Journal of Pharmacokinetics and Pharmacodynamics Springer US; http://www.springer-ny.com 42/4(2015-08-01), 333-347 1567-567X 42:4<333 2015 42 10928