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9-year agent-based simulations of potmenopausal osteoporosis and its treatment with alendronate
Adapt a model of treatment of osteoporosis with denosumab over 10 years to model treatment of osteoporosis with alendronate over 9 years.
Keywords: agent-based, multiphysics, in silico, bone, osteoporosis, denosumab, alendronate, bisphosphonates
Approximately 10 million osteoporotic fragility fractures occur every year and lead to over 400,000 deaths and health care costs in excess of US$80 billion. We at the laboratory for bone biomechanics at the ETH Zurich have developed a computational model to predict how the bone microstructure and strength will change as a result of bone diseases and their treatments.
The aim of this project is to apply in silico modelling to analyze the effects of two widespread therapeutics for osteoporosis (alendronate and denosumab) on bone. Specifically the project will apply an agent-based multiphysics model which was already used successfully to simulate the effect of 10 years of treatment with denosumab on iliac crest biopsies from a group of post-menopausal women (age: 72±5 years, scanned with micro-CT at a resolution of 10.5 microns, article: https://doi.org/10.1002/jbm4.10494). These micron-scaled agent-based simulations outperformed state-of-the-art bone cell population dynamics models and provide higher resolution agent-based functionalities and comparable performance to alternative multiphysics models. In this project we intend to run simulations of the effect of treatment with alendronate using the same model parameters and the same baseline images.
Both alendronate and denosumab are among the most widely used treatments for osteoporosis. Large randomized controlled trials for 9 years of treatment with alendronate and 10 years of treatment with denosumab provided data on trends in bone mineral density, bone turnover markers and parameters related to the pharmacokinetics and pharmacodynamics of alendronate and denosumab.
Both alendronate and denosumab are anti-resorptives, meaning their mechanism of action most immediately leads to a decrease in bone resorption by osteoclasts. Due to osteoclast-osteoblast coupling bone formation also decreases and the net effect of denosumab and bisphosphonates is to decrease rates of bone remodelling by 50 to 90% with a net shift in the formation resorption balance in favour of formation.
Alendronate and denosumab are both anti-resorptive medications but they differ in their long-term effect on bone mineral density (BMD). Denosumab treatment results in a steady rise in BMD over a period of 10 years while with alendronate treatment BMD only increases over a period of approximately 3 years then remains relatively constant.
Bisphosphonates bind to bone mineral with high affinity, inhibit osteoclastic resorption and promote osteoclast apoptosis. Denosumab is an antibody to RANKL, a cytokine which promotes differentiation of osteoclast precursors to osteoclasts. Binding of denosumab to RANKL thus results in decreased osteoclastogenesis. The denosumab pathway has already been implemented in the model and in this project you will be asked to implement the alendronate pathway.
Approximately 10 million osteoporotic fragility fractures occur every year and lead to over 400,000 deaths and health care costs in excess of US$80 billion. We at the laboratory for bone biomechanics at the ETH Zurich have developed a computational model to predict how the bone microstructure and strength will change as a result of bone diseases and their treatments.
The aim of this project is to apply in silico modelling to analyze the effects of two widespread therapeutics for osteoporosis (alendronate and denosumab) on bone. Specifically the project will apply an agent-based multiphysics model which was already used successfully to simulate the effect of 10 years of treatment with denosumab on iliac crest biopsies from a group of post-menopausal women (age: 72±5 years, scanned with micro-CT at a resolution of 10.5 microns, article: https://doi.org/10.1002/jbm4.10494). These micron-scaled agent-based simulations outperformed state-of-the-art bone cell population dynamics models and provide higher resolution agent-based functionalities and comparable performance to alternative multiphysics models. In this project we intend to run simulations of the effect of treatment with alendronate using the same model parameters and the same baseline images.
Both alendronate and denosumab are among the most widely used treatments for osteoporosis. Large randomized controlled trials for 9 years of treatment with alendronate and 10 years of treatment with denosumab provided data on trends in bone mineral density, bone turnover markers and parameters related to the pharmacokinetics and pharmacodynamics of alendronate and denosumab. Both alendronate and denosumab are anti-resorptives, meaning their mechanism of action most immediately leads to a decrease in bone resorption by osteoclasts. Due to osteoclast-osteoblast coupling bone formation also decreases and the net effect of denosumab and bisphosphonates is to decrease rates of bone remodelling by 50 to 90% with a net shift in the formation resorption balance in favour of formation.
Alendronate and denosumab are both anti-resorptive medications but they differ in their long-term effect on bone mineral density (BMD). Denosumab treatment results in a steady rise in BMD over a period of 10 years while with alendronate treatment BMD only increases over a period of approximately 3 years then remains relatively constant.
Bisphosphonates bind to bone mineral with high affinity, inhibit osteoclastic resorption and promote osteoclast apoptosis. Denosumab is an antibody to RANKL, a cytokine which promotes differentiation of osteoclast precursors to osteoclasts. Binding of denosumab to RANKL thus results in decreased osteoclastogenesis. The denosumab pathway has already been implemented in the model and in this project you will be asked to implement the alendronate pathway.
Review the literature for clinical studies reporting parameters related to the pharmacokinetics and pharmacodynamics of alendronate
Critically evaluate potential implementations of alendronate into the agent-based Multiphysics model
With the chosen implementation and PK and PD parameters from literature, run simulations of 9 years of alendronate and placebo.
Critically compare the results with the bone mineral density at the total hip and bone turnover markers reported in the FIT and FLEX clinical trials. Adapt unknown parameters to reproduce trends seen in these clinical trials while remaining within ranges of parameters reported in literature
Analyze trends in cell behaviour and cytokine concentrations to test hypotheses relating to the levelling off of alendronate’s effect on BMD after 3 years and the residual effect of alendronate upon discontinuation.
Prepare a presentation for the entire laboratory summarizing your results (30 minutes) and a report for your master thesis.
Review the literature for clinical studies reporting parameters related to the pharmacokinetics and pharmacodynamics of alendronate
Critically evaluate potential implementations of alendronate into the agent-based Multiphysics model
With the chosen implementation and PK and PD parameters from literature, run simulations of 9 years of alendronate and placebo.
Critically compare the results with the bone mineral density at the total hip and bone turnover markers reported in the FIT and FLEX clinical trials. Adapt unknown parameters to reproduce trends seen in these clinical trials while remaining within ranges of parameters reported in literature
Analyze trends in cell behaviour and cytokine concentrations to test hypotheses relating to the levelling off of alendronate’s effect on BMD after 3 years and the residual effect of alendronate upon discontinuation.
Prepare a presentation for the entire laboratory summarizing your results (30 minutes) and a report for your master thesis.
Email: charles.ledoux@hest.ethz.ch
Website: https://www.bone.ethz.ch/research/clin-mech/multiphysics.html
Charles Ledoux PhD Student
ETH Zürich, HCP H 18.2
Leopold-Ruzicka-Weg 4 CH - 8093 Zürich