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Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies

Postmenopausal osteoporosis is a disease manifesting in degradation of bone mass and microarchitecture, leading to weakening and increased risk of fracture. Clinical trials are an essential tool for evaluating new treatments and may provide further mechanistic understanding of their effects in vivo....

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Autores principales: Tourolle, Duncan C, Dempster, David W, Ledoux, Charles, Boaretti, Daniele, Aguilera, Mauricio, Saleem, Najma, Müller, Ralph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216138/
https://www.ncbi.nlm.nih.gov/pubmed/34189383
http://dx.doi.org/10.1002/jbm4.10494
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author Tourolle, Duncan C
Dempster, David W
Ledoux, Charles
Boaretti, Daniele
Aguilera, Mauricio
Saleem, Najma
Müller, Ralph
author_facet Tourolle, Duncan C
Dempster, David W
Ledoux, Charles
Boaretti, Daniele
Aguilera, Mauricio
Saleem, Najma
Müller, Ralph
author_sort Tourolle, Duncan C
collection PubMed
description Postmenopausal osteoporosis is a disease manifesting in degradation of bone mass and microarchitecture, leading to weakening and increased risk of fracture. Clinical trials are an essential tool for evaluating new treatments and may provide further mechanistic understanding of their effects in vivo. However, the histomorphometry from clinical trials is limited to 2D images and reflects single time points. Biochemical markers of bone turnover give global insight into a drug's action, but not the local dynamics of the bone remodeling process and the cells involved. Additionally, comparative trials necessitate separate treatment groups, meaning only aggregated measures can be compared. In this study, in silico modeling based on histomorphometry and pharmacokinetic data was used to assess the effects of treatment versus control on μCT scans of the same biopsy samples over time, matching the changes in bone volume fraction observed in biopsies from denosumab and placebo groups through year 10 of the FREEDOM Extension trial. In the simulation, treatment decreased osteoclast number, which led to a modest increase in trabecular thickness and osteocyte stress shielding. Long‐term bone turnover suppression led to increased RANKL production, followed by a small increase in osteoclast number at the end of the 6‐month–dosing interval, especially at the end of the Extension study. Lack of treatment led to a significant loss of bone mass and structure. The study's results show how in silico models can generate predictions of denosumab cellular action over a 10‐year period, matching static and dynamic morphometric measures assessed in clinical biopsies. The use of in silico models with clinical trial data can be a method to gain further insight into fundamental bone biology and how treatments can perturb this. With rigorous validation, such models could be used for informing the design of clinical trials, such that the number of participants could be reduced to a minimum to show efficacy. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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spelling pubmed-82161382021-06-28 Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies Tourolle, Duncan C Dempster, David W Ledoux, Charles Boaretti, Daniele Aguilera, Mauricio Saleem, Najma Müller, Ralph JBMR Plus Original Articles Postmenopausal osteoporosis is a disease manifesting in degradation of bone mass and microarchitecture, leading to weakening and increased risk of fracture. Clinical trials are an essential tool for evaluating new treatments and may provide further mechanistic understanding of their effects in vivo. However, the histomorphometry from clinical trials is limited to 2D images and reflects single time points. Biochemical markers of bone turnover give global insight into a drug's action, but not the local dynamics of the bone remodeling process and the cells involved. Additionally, comparative trials necessitate separate treatment groups, meaning only aggregated measures can be compared. In this study, in silico modeling based on histomorphometry and pharmacokinetic data was used to assess the effects of treatment versus control on μCT scans of the same biopsy samples over time, matching the changes in bone volume fraction observed in biopsies from denosumab and placebo groups through year 10 of the FREEDOM Extension trial. In the simulation, treatment decreased osteoclast number, which led to a modest increase in trabecular thickness and osteocyte stress shielding. Long‐term bone turnover suppression led to increased RANKL production, followed by a small increase in osteoclast number at the end of the 6‐month–dosing interval, especially at the end of the Extension study. Lack of treatment led to a significant loss of bone mass and structure. The study's results show how in silico models can generate predictions of denosumab cellular action over a 10‐year period, matching static and dynamic morphometric measures assessed in clinical biopsies. The use of in silico models with clinical trial data can be a method to gain further insight into fundamental bone biology and how treatments can perturb this. With rigorous validation, such models could be used for informing the design of clinical trials, such that the number of participants could be reduced to a minimum to show efficacy. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. John Wiley & Sons, Inc. 2021-04-05 /pmc/articles/PMC8216138/ /pubmed/34189383 http://dx.doi.org/10.1002/jbm4.10494 Text en © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Tourolle, Duncan C
Dempster, David W
Ledoux, Charles
Boaretti, Daniele
Aguilera, Mauricio
Saleem, Najma
Müller, Ralph
Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title_full Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title_fullStr Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title_full_unstemmed Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title_short Ten‐Year Simulation of the Effects of Denosumab on Bone Remodeling in Human Biopsies
title_sort ten‐year simulation of the effects of denosumab on bone remodeling in human biopsies
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8216138/
https://www.ncbi.nlm.nih.gov/pubmed/34189383
http://dx.doi.org/10.1002/jbm4.10494
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