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Application of Disease System Analysis to Osteoporosis: From Temporal to Spatio-Temporal Assessment of Disease Progression and Intervention

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Multiscale Mechanobiology of Bone Remodeling and Adaptation

Part of the book series: CISM International Centre for Mechanical Sciences ((CISM,volume 578))

Abstract

Osteoporosis (OP) is a progressive bone disorder regarded as an important worldwide health issue. OP is characterised by a slow reduction of the bone matrix and changes in the bone matrix properties. Novel drug treatments are continuously developed to reduce the risk of bone fractures. Assessing the effects of novel and existing treatments on OP can be challenging. This is due to the difficulties of establishing the effects of the drug on the disease progression as reflected in the slowly changing bone mineral density (BMD). In recent years, our understanding of the pathophysiology of OP has considerably improved. Biomarkers reflecting bone physiology have been identified at the cellular, tissue and organ levels. Cellular biomarkers reflect the dynamics of bone remodelling (i.e., bone formation and resorption) on a short time scale. On the other hand, tissue and organ scale biomarkers show changes of BMD and bone structural arrangements on a larger time scale. Biomarkers can be used to characterise bone remodelling and to quantify the effect of the drug on OP. Recently, the concept of disease system analysis (DSA) has been proposed as a novel approach to quantitatively characterise drug effects on disease progression. This approach integrates physiology, disease progression and drug treatment in a comprehensive mechanism-based modelling framework using a large amount of complementary biomarker data. This chapter will provide an overview of the use of DSA to characterise drug effects on OP. We will review classical (i.e., non-mechanistic) pharmacokinetic-pharmacodynamic (PK/PD) models used to study drug dose-effect responses. Latest mechanistic bone remodelling models will be presented together with the study of the effect of the drug denosumab on disease progression in postmenopausal osteoporosis (PMO). Finally, we will provide an outlook on how to extend the temporal mechanistic model towards a spatio-temporal description. We conclude that the development of fully mechanistic disease system models of OP has great potential to adequately predict the long-term effects of drug treatments on clinical outcomes. This may provide a means for patient-specific estimation of bone fracture risk.

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Notes

  1. 1.

    Following the notation of L. Lanyon we will use (re)modelling to denote both modelling and remodelling.

  2. 2.

    It is important to distinguish between blood, plasma, and serum. Blood includes fluid, white and red cells and platelets; plasma is the fluid portion of blood including only soluble proteins; serum is the plasma without the soluble protein.

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Acknowledgements

Dr Pivonka acknowledges support of this work by the Australian Research Council (ARC). Miss Trichilo acknowledges support by The University of Melbourne as part of the International PhD scholarship program.

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  1. St Vincent’s Department of Surgery, The University of Melbourne, Melbourne, VIC, Australia

    Silvia Trichilo & Peter Pivonka

  2. Australian Institute of Musculoskeletal Science, Melbourne, VIC, Australia

    Silvia Trichilo & Peter Pivonka

  3. School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, QLD, Australia

    Peter Pivonka

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Trichilo, S., Pivonka, P. (2018). Application of Disease System Analysis to Osteoporosis: From Temporal to Spatio-Temporal Assessment of Disease Progression and Intervention. In: Pivonka, P. (eds) Multiscale Mechanobiology of Bone Remodeling and Adaptation. CISM International Centre for Mechanical Sciences, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-319-58845-2_2

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