Osteoporosis (OP) is a chronic progressive bone disease which affects a large portion of the elderly population worldwide. OP is characterized by a slow reduction of bone matrix and changes in the bone matrix properties which ultimately leads to whole (organ) bone fractures [1].

Novel drug treatments are developed to more effectively reduce the risk of bone fractures. Assessing the effects of novel and existing treatments on OP is challenging due to the complexity of the bone remodeling process, its effects on the bone matrix and the different spatial and temporal scales involved. Identification and characterization of various bone biomarkers has significantly improved our understanding of OP pathophysiology. The bone matrix and its constituents are specific bone biomarkers measured at a particular bone site. On the other hand, biochemical ligands released during bone remodeling and measured in blood or urine are non-specific bone biomarkers. These biomarkers can be used to characterize the underlying bone mechanobiological system and drug treatment effects [1].

Recently, disease system analysis (DSA) has been proposed as a novel approach to quantitatively characterize drug effects on disease progression [1]. DSA integrates physiology, disease progression and drug treatment in a comprehensive mechanism-based modelling framework using a large amount of complementary biomarker data. DSA applied to population based structural models of whole bony organs (e.g. femur and vertebra) can be used to perform in silico trials of drug efficacy for osteoporosis treatment. In this presentation, I will present latest mechanistic pharmacokinetic-pharmacodynamic (PK/PD) models of osteoporosis treatments. Examples of currently used drug interventions including denosumab [2,3] romozosumab [4], and PTH [5] treatments will serve as discussion points on which mechanisms are essential for accurate bone remodeling simulations. Bone matrix mineralization turns out to be an essential model feature that is required to predict BV/TV changes for the case of anti-catabolic drug treatments of OP [3]. Finally, I will elucidate on how PK/PD models, typically applied at the tissue scale, can be adapted to the whole organ scale and coupled with structural finite element simulations of bone in order to predict effects of drug treatments on bone strength and fracture risk.

Acknowledgments: Dr Pivonka acknowledges support from the Australian Research Council (IC190100020) and (DP230101404).

References: ”[1] S. Trichilo and P. Pivonka, Disease systems analysis in osteoporosis and mechanobiology, in Multiscale mechanobiology of bone remodelling and adaptation, Editor P. Pivonka, CISM Courses and Lectures No. 1406, Springer, 2017; [2] S. Scheiner et al.. Mathematical modeling of postmenopausal osteoporosis and its treatment by the anti-catabolic denosumab, Int. Journal for Numerical Methods in Biomedical Engineering, 30(1), pp1-27, 2014; [3] J. Martinez-Reina and P. Pivonka, Effects of long-term treatment of denosumab on bone mineral density: insights from an in-sillico model of bone mineralization, Bone, 125, pp87-95, 2019; [4] M. Martin et al., Assessment of Romozosumab efficacy in the treatment of postmenopausal osteoporosis: results from a mechanistic PK-PD mechanostat model of bone remodeling, Bone, 133, pp1-16, 2020; [5] M. Lavaill et al., Effects of PTH treatment in osteoporosis, BMMB, pp1-16, 2020.”