Mechanobiological osteocyte feedback drives mechanostat regulation of bone in a multiscale computational model

A review of the current status and future prospects of the bone remodeling process: Biological and mathematical perspectives

This review dives into the complex dynamics of bone remodeling, combining biological insights with mathematical perspectives to better understand this fundamental aspect of skeletal health. Bone, being a crucial part of our body, constantly renews itself, and with the growing number of individuals facing bone-related issues, research in this field is vital. In this review, we categorized and classified most common mathematical models used to simulate the mechanical behavior of bone under different loading and health conditions, shedding light on the evolving landscape of bone biology. While current models have effectively captured the essence of healthy bone remodeling, the ever-expanding knowledge in bone biology suggests an update in mathematical methods. Knowing the role of the skeleton in whole-body physiology, and looking at the recent discoveries about activities of bone cells emphasize the urgency of refining our mathematical descriptions of the bone remodeling process. The underexplored impact of bone diseases like osteoporosis, Paget's disease, or breast cancer on bone remodeling also points to the need for intensified research into diverse disease types and their unique effects on bone health. By reviewing a range of bone remodeling models, we show the necessity for tailor-made mathematical models to decipher their roots and enhance patient treatment strategies. Collaboration among scientists from various domains is pivotal to surmount these challenges, ensuring improved accuracy and applicability of mathematical models. Ultimately, this effort aims to deepen our understanding of bone remodeling processes and their broader implications for diverse health conditions.

Advances in mechanobiological pharmacokinetic-pharmacodynamic models of osteoporosis treatment - Pathways to optimise and exploit existing therapies

Osteoporosis (OP) is a chronic progressive bone disease which is characterised by reduction of bone matrix volume and changes in the bone matrix properties which can ultimately lead to bone fracture. The two major forms of OP are related to aging and/or menopause. With the worldwide increase of the elderly population, particularly age-related OP poses a serious health issue which puts large pressure on health care systems. A major challenge for development of new drug treatments for OP and comparison of drug efficacy with existing treatments is due to current regulatory requirements which demand testing of drugs based on bone mineral density (BMD) in phase 2 trials and fracture risk in phase 3 trials. This requires large clinical trials to be conducted and to be run for long time periods, which is very costly. This, together with the fact that there are already many drugs available for treatment of OP, makes the development of new drugs inhibitive. Furthermore, an increased trend of the use of different sequential drug therapies has been observed in OP management, such as sequential anabolic-anticatabolic drug treatment or switching from one anticatabolic drug to another. Running clinical trials for concurrent and sequential therapies is neither feasible nor practical due to large number of combinatorial possibilities. In silico mechanobiological pharmacokinetic-pharmacodynamic (PK-PD) models of OP treatments allow predictions beyond BMD, i.e. bone microdamage and degree of mineralisation can also be monitored. This will help to inform clinical drug usage and development by identifying the most promising scenarios to be tested clinically (confirmatory trials rather than exploratory only trials), optimise trial design and identify subgroups of the population that show benefit-risk profiles (both good and bad) that are different from the average patient. In this review, we provide examples of the predictive capabilities of mechanobiological PK-PD models. These include simulation results of PMO treatment with denosumab, implications of denosumab drug holidays and coupling of bone remodelling models with calcium and phosphate systems models that allows to investigate the effects of co-morbidities such as hyperparathyroidism and chronic kidney disease together with calcium and vitamin D status on drug efficacy.

An in silico approach to elucidate the pathways leading to primary osteoporosis: age-related vs. postmenopausal

Numerical models of bone remodelling have traditionally been used to perform in silico tests of bone loss in postmenopausal women and also to simulate the response to different drug treatments. These models simulate the menopausal oestrogen decline by altering certain signalling pathways. However, they do not consider the simultaneous effect that ageing can have on cell function and bone remodelling, and thus on bone loss. Considering ageing and oestrogen decline together is important for designing osteoporosis treatments that can selectively counteract one or the other disease mechanism. A previously developed bone cell population model was adapted to consider the effect of ageing through: (1) the decrease of TGF- β contained in the bone matrix and (2) an increased production of sclerostin by non-skeletal cells. Oestrogen deficiency is simulated in three different ways: (a) an increase in RANKL expression, (b) a decrease in OPG production, and (c) an increase in the responsiveness of osteoclasts to RANKL. The effect of ageing was validated using the cross-sectional study of (Riggs et al. in J Bone Miner Res 19: 1945-1954, 2004) on BMD of trabecular bone of the vertebral body of men. The joint effect of ageing and oestrogen deficiency was validated using these same clinical results but in women. In ageing, the effect of the increasing production of sclerostin is more important than the decrease of TGF- β , while the three mechanisms used to simulate the effect of oestrogen deficiency produce almost identical responses. The results show that an early menopause leads to a lower average density in the fifth decade, but after the sixth decade the average density is independent of the age at menopause. Treatment of osteoporosis with denosumab was also simulated to conclude that the drug is not very effective if started before 10 years after menopause or before age 60.

Tumor growth for remodeling process: A 2D approach

This paper aims to present a comprehensive framework for coupling tumor-bone remodeling processes in a 2-dimensional geometry. This is achieved by introducing a bio-inspired damage that represents the growing tumor, which subsequently affects the main populations involved in the remodeling process, namely, osteoclasts, osteoblasts, and bone tissue. The model is constructed using a set of differential equations based on the Komarova's and Ayati's models, modified to incorporate the bio-inspired damage that may result in tumor mass formation. Three distinct models were developed. The first two models are based on the Komarova's governing equations, with one demonstrating an osteolytic behavior and the second one an osteoblastic model. The third model is a variation of Ayati's model, where the bio-inspired damage is induced through the paracrine and autocrine parameters, exhibiting an osteolytic behavior. The obtained results are consistent with existing literature, leading us to believe that our in-silico experiments will serve as a cornerstone for paving the way towards targeted interventions and personalized treatment strategies, ultimately improving the quality of life for those affected by these conditions.

A review of mathematical modeling of bone remodeling from a systems biology perspective

Bone remodeling is an essential, delicately balanced physiological process of coordinated activity of bone cells that remove and deposit new bone tissue in the adult skeleton. Due to the complex nature of this process, many mathematical models of bone remodeling have been developed. Each of these models has unique features, but they have underlying patterns. In this review, the authors highlight the important aspects frequently found in mathematical models for bone remodeling and discuss how and why these aspects are included when considering the physiology of the bone basic multicellular unit, which is the term used for the collection of cells responsible for bone remodeling. The review also emphasizes the view of bone remodeling from a systems biology perspective. Understanding the systemic mechanisms involved in remodeling will help provide information on bone pathology associated with aging, endocrine disorders, cancers, and inflammatory conditions and enhance systems pharmacology. Furthermore, some features of the bone remodeling cycle and interactions with other organ systems that have not yet been modeled mathematically are discussed as promising future directions in the field.

Fluid-solid coupling numerical simulation of the effects of different doses of verapamil on cancellous bone in type 2 diabetic rats

BACKGROUND

The purpose of this study was to investigate the effects of four different doses of verapamil on the mechanical behaviors of solid and the characteristics of fluid flow in cancellous bone of distal femur of type 2 diabetes rats under dynamic external load.

METHODS

Based on the micro-CT images, the finite element models of cancellous bones and fluids at distal femurs of rats in control group, diabetes group, treatment groups VER 4, VER 12, VER 24, and VER 48 (verapamil doses of 4, 12, 24, and 48 mg/kg/day, respectively) were constructed. A sinusoidal time-varying displacement load with an amplitude of 0.8 μm and a period of 1s was applied to the upper surface of the solid region. Then, fluid-solid coupling numerical simulation method was used to analyze the magnitudes and distributions of von Mises stress, flow velocity, and fluid shear stress of cancellous bone models in each group.

RESULTS

The results for mean values of von Mises stress, flow velocity and FSS (t = 0.25s) were as follows: their values in control group were lower than those in diabetes group; the three parameters varied with the dose of verapamil; in the four treatment groups, the values of VER 48 group were the lowest, they were the closest to control group, and they were smaller than diabetes group. Among the four treatment groups, VER 48 group had the highest proportion of the nodes with FSS = 1-3 Pa on the surface of cancellous bone, and more areas in VER 48 group were subjected to fluid shear stress of 1-3 Pa for more than half of the time.

CONCLUSION

It could be seen that among the four treatment groups, osteoblasts on the cancellous bone surface in the highest dose group (VER 48 group) were more easily activated by mechanical loading, and the treatment effect was the best. This study might help in understanding the mechanism of verapamil's effect on the bone of type 2 diabetes mellitus, and provide theoretical guidance for the selection of verapamil dose in the clinical treatment of type 2 diabetes mellitus.

Trabecular bone remodeling in the aging mouse: A micro-multiphysics agent-based in silico model using single-cell mechanomics

Bone remodeling is regulated by the interaction between different cells and tissues across many spatial and temporal scales. Notably, in silico models are regarded as powerful tools to further understand the signaling pathways that regulate this intricate spatial cellular interplay. To this end, we have established a 3D multiscale micro-multiphysics agent-based (micro-MPA) in silico model of trabecular bone remodeling using longitudinal in vivo data from the sixth caudal vertebra (CV6) of PolgA(D257A/D257A) mice, a mouse model of premature aging. Our in silico model includes a variety of cells as single agents and receptor-ligand kinetics, mechanomics, diffusion and decay of cytokines which regulate the cells' behavior. We highlighted its capabilities by simulating trabecular bone remodeling in the CV6 of five mice over 4 weeks and we evaluated the static and dynamic morphometry of the trabecular bone microarchitecture. Based on the progression of the average trabecular bone volume fraction (BV/TV), we identified a configuration of the model parameters to simulate homeostatic trabecular bone remodeling, here named basal. Crucially, we also produced anabolic, anti-anabolic, catabolic and anti-catabolic responses with an increase or decrease by one standard deviation in the levels of osteoprotegerin (OPG), receptor activator of nuclear factor kB ligand (RANKL), and sclerostin (Scl) produced by the osteocytes. Our results showed that changes in the levels of OPG and RANKL were positively and negatively correlated with the BV/TV values after 4 weeks in comparison to basal levels, respectively. Conversely, changes in Scl levels produced small fluctuations in BV/TV in comparison to the basal state. From these results, Scl was deemed to be the main driver of equilibrium while RANKL and OPG were shown to be involved in changes in bone volume fraction with potential relevance for age-related bone features. Ultimately, this micro-MPA model provides valuable insights into how cells respond to their local mechanical environment and can help to identify critical pathways affected by degenerative conditions and ageing.

Spatio-temporal simulations of bone remodelling using a bone cell population model based on cell availability

Here we developed a spatio-temporal bone remodeling model to simulate the action of Basic Multicelluar Units (BMUs). This model is based on two major extensions of a temporal-only bone cell population model (BCPM). First, the differentiation into mature resorbing osteoclasts and mature forming osteoblasts from their respective precursor cells was modelled as an intermittent process based on precursor cells availability. Second, the interaction between neighbouring BMUs was considered based on a "metabolic cost" argument which warrants that no new BMU will be activated in the neighbourhood of an existing BMU. With the proposed model we have simulated the phases of the remodelling process obtaining average periods similar to those found in the literature: resorption ( ∼ 22 days)-reversal (∼8 days)-formation (∼65 days)-quiescence (560-600 days) and an average BMU activation frequency of ∼1.6 BMUs/year/mm³. We further show here that the resorption and formation phases of the BMU become coordinated only by the presence of TGF-β (transforming growth factor β), i.e., a major coupling factor stored in the bone matrix. TGF-β is released through resorption so upregulating osteoclast apoptosis and accumulation of osteoblast precursors, i.e., facilitating the transition from the resorption to the formation phase at a given remodelling site. Finally, we demonstrate that this model can explain targeted bone remodelling as the BMUs are steered towards damaged bone areas in order to commence bone matrix repair.

Mathematical modeling of the effects of Wnt-10b on bone metabolism

Bone health is determined by factors including bone metabolism or remodeling. Wnt-10b alters osteoblastogenesis through pre-osteoblast proliferation and differentiation and osteoblast apoptosis rate, which collectively lead to the increase of bone density. To model this, we adapted a previously published model of bone remodeling. The resulting model for the bone compartment includes differential equations for active osteoclasts, pre-osteoblasts, osteoblasts, osteocytes, and the amount of bone present at the remodeling site. Our alterations to the original model consist of extending it past a single remodeling cycle and implementing a direct relationship to Wnt-10b. Four new parameters were estimated and validated using normalized data from mice. The model connects Wnt-10b to bone metabolism and predicts the change in trabecular bone volume caused by a change in Wnt-10b input. We find that this model predicts the expected increase in pre-osteoblasts and osteoblasts while also pointing to a decrease in osteoclasts when Wnt-10b is increased.

Mechanistic PK-PD model of alendronate treatment of postmenopausal osteoporosis predicts bone site-specific response

Alendronate is the most widely used drug for postmenopausal osteoporosis (PMO). It inhibits bone resorption, affecting osteoclasts. Pharmacokinetics (PK) and pharmacodynamics (PD) of alendronate have been widely studied, but few mathematical models exist to simulate its effect. In this work, we have developed a PK model for alendronate, valid for short- and long-term treatments, and a mechanistic PK-PD model for the treatment of PMO to predict bone density gain (BDG) at the hip and lumbar spine. According to our results, at least three compartments are required in the PK model to predict the effect of alendronate in both the short and long terms. Clinical data of a 2-year treatment of alendronate, reproduced by our PK-PD model, demonstrate that bone response is site specific (hip: 7% BDG, lumbar spine: 4% BDG). We identified that this BDG is mainly due to an increase in tissue mineralization and a decrease in porosity. The difference in BDG between sites is linked to the different loading and dependence of the released alendronate on the bone-specific surface and porosity. Osteoclast population diminishes quickly within the first month of alendronate treatment. Osteoblast population lags behind but also falls due to coupling of resorption and formation. Two dosing regimens were studied (70 mg weekly and 10 mg daily), and both showed very similar BDG evolution, indicating that alendronate accumulates quickly in bone and saturates. The proposed PK-PD model could provide a valuable tool to analyze the effect of alendronate and to design patient-specific treatments, including drug combinations.

Assessment of Strategies for Safe Drug Discontinuation and Transition of Denosumab Treatment in PMO—Insights From a Mechanistic PK/PD Model of Bone Turnover

Denosumab (Dmab) treatment against postmenopausal osteoporosis (PMO) has proven very efficient in increasing bone mineral density (BMD) and reducing the risk of bone fractures. However, concerns have been recently raised regarding safety when drug treatment is discontinued. Mechanistic pharmacokinetic-pharmacodynamic (PK-PD) models are the most sophisticated tools to develop patient specific drug treatments of PMO to restore bone mass. However, only a few PK-PD models have addressed the effect of Dmab drug holidays on changes in BMD. We showed that using a standard bone cell population model (BCPM) of bone remodelling it is not possible to account for the spike in osteoclast numbers observed after Dmab discontinuation. We show that inclusion of a variable osteoclast precursor pool in BCPMs is essential to predict the experimentally observed rapid rise in osteoclast numbers and the associated increases in bone resorption. This new model also showed that Dmab withdrawal leads to a rapid increase of damage in the bone matrix, which in turn decreases the local safety factor for fatigue failure. Our simulation results show that changes in BMD strongly depend on Dmab concentration in the central compartment. Consequently, bone weight (BW) might play an important factor in calculating effective Dmab doses. The currently clinically prescribed constant Dmab dose of 60 mg injected every 6 months is less effective in increasing BMD for patients with high BW (2.5% for 80 kg in contrast to 8% for 60 kg after 6 years of treatment). However, bone loss observed 24 months after Dmab withdrawal is less pronounced in patients with high BW (3.5% for 80kg and 8.5% for 60 kg). Finally, we studied how to safely discontinue Dmab treatment by exploring several transitional and combined drug treatment strategies. Our simulation results indicate that using transitional reduced Dmab doses are not effective in reducing rapid bone loss. However, we identify that use of a bisphosphonate (BP) is highly effective in avoiding rapid bone loss and increase in bone tissue damage compared to abrupt withdrawal of Dmab. Furthermore, the final values of BMD and damage were not sensitive to the time of administration of the BP.

Effects of Osteocyte Shape on Fluid Flow and Fluid Shear Stress of the Loaded Bone

This study was conducted to better understand the specific behavior of the intraosseous fluid flow. We calculated the number and distribution of bone canaliculi around the osteocytes based on the varying shapes of osteocytes. We then used these calculated parameters and other bone microstructure data to estimate the anisotropy permeability of the lacunar-canalicular network. Poroelastic finite element models of the osteon were established, and the influence of the osteocyte shape on the fluid flow properties of osteons under an axial displacement load was analyzed. Two types of boundary conditions (BC) that might occur in physiological environments were considered on the cement line of the osteon. BC1 allows free fluid passage from the outer elastic restraint boundary, and BC2 is impermeable and allows no free fluid passage from outer displacement constrained boundary. They both have the same inner boundary conditions that allow fluid to pass through. Changes in the osteocyte shape altered the maximum value of pressure gradient (PG), pore pressure (PP), fluid velocity (FV), and fluid shear stress (FSS) relative to the reference model (spherical osteocytes). The maximum PG, PP, FV, and FSS in BC2 were nearly 100% larger than those in BC1, respectively. It is found that the BC1 was closer to the real physiological environment. The fluid flow along different directions in the elongated osteocyte model was more evident than that in other models, which may have been due to the large difference in permeability along different directions. Changes in osteocyte shape significantly affect the degrees of anisotropy of fluid flow and porous media of the osteon. The model presented in this study can accurately quantify fluid flow in the lacunar-canalicular network.

Implementing computational modeling in tissue engineering: where disciplines meet

In recent years, the mathematical and computational sciences have developed novel methodologies and insights that can aid in designing advanced bioreactors, microfluidic set-ups or organ-on-chip devices, in optimizing culture conditions, or predicting long-term behavior of engineered tissues in vivo. In this review, we introduce the concept of computational models and how they can be integrated in an interdisciplinary workflow for Tissue Engineering and Regenerative Medicine (TERM). We specifically aim this review of general concepts and examples at experimental scientists with little or no computational modeling experience. We also describe the contribution of computational models in understanding TERM processes and in advancing the TERM field by providing novel insights.

Bone: An Outstanding Composite Material

Bone is an outstanding, well-designed composite. It is constituted by a multi-level structure wherein its properties and behavior are dependent on its composition and structural organization at different length scales. The combination of unique mechanical properties with adaptive and self-healing abilities makes bone an innovative model for the future design of synthetic biomimetic composites with improved performance in bone repair and regeneration. However, the relation between structure and properties in bone is very complex. In this review article, we intend to describe the hierarchical organization of bone on progressively greater scales and present the basic concepts that are fundamental to understanding the arrangement-based mechanical properties at each length scale and their influence on bone’s overall structural behavior. The need for a better understanding of bone’s intricate composite structure is also highlighted.

Overexpression of Lrp5 enhanced the anti-breast cancer effects of osteocytes in bone

Osteocytes are the most abundant cells in bone, which is a frequent site of breast cancer metastasis. Here, we focused on Wnt signaling and evaluated tumor-osteocyte interactions. In animal experiments, mammary tumor cells were inoculated into the mammary fat pad and tibia. The role of Lrp5-mediated Wnt signaling was examined by overexpressing and silencing Lrp5 in osteocytes and establishing a conditional knockout mouse model. The results revealed that administration of osteocytes or their conditioned medium (CM) inhibited tumor progression and osteolysis. Osteocytes overexpressing Lrp5 or β-catenin displayed strikingly elevated tumor-suppressive activity, accompanied by downregulation of tumor-promoting chemokines and upregulation of apoptosis-inducing and tumor-suppressing proteins such as p53. The antitumor effect was also observed with osteocyte-derived CM that was pretreated with a Wnt-activating compound. Notably, silencing Lrp5 in tumors inhibited tumor progression, while silencing Lrp5 in osteocytes in conditional knockout mice promoted tumor progression. Osteocytes exhibited elevated Lrp5 expression in response to tumor cells, implying that osteocytes protect bone through canonical Wnt signaling. Thus, our results suggest that the Lrp5/β-catenin axis activates tumor-promoting signaling in tumor cells but tumor-suppressive signaling in osteocytes. We envision that osteocytes with Wnt activation potentially offer a novel cell-based therapy for breast cancer and osteolytic bone metastasis.

Bone Homeostasis and Gut Microbial-Dependent Signaling Pathways

Although research on the osteal signaling pathway has progressed, understanding of gut microbial-dependent signaling pathways for metabolic and immune bone homeostasis remains elusive. In recent years, the study of gut microbiota has shed light on our understanding of bone homeostasis. Here, we review microbiota-mediated gut-bone crosstalk via bone morphogenetic protein/SMADs, Wnt and OPG/receptor activator of nuclear factor-kappa B ligand signaling pathways in direct (translocation) and indirect (metabolite) manners. The mechanisms underlying gut microbiota involvement in these signaling pathways are relevant in immune responses, secretion of hormones, fate of osteoblasts and osteoclasts and absorption of calcium. Collectively, we propose a signaling network for maintaining a dynamic homeostasis between the skeletal system and the gut ecosystem. Additionally, the role of gut microbial improvement by dietary intervention in osteal signaling pathways has also been elucidated. This review provides unique resources from the gut microbial perspective for the discovery of new strategies for further improving treatment of bone diseases by increasing the abundance of targeted gut microbiota.

A General Mechano-Pharmaco-Biological Model for Bone Remodeling Including Cortisol Variation

The process of bone remodeling requires a strict coordination of bone resorption and formation in time and space in order to maintain consistent bone quality and quantity. Bone-resorbing osteoclasts and bone-forming osteoblasts are the two major players in the remodeling process. Their coordination is achieved by generating the appropriate number of osteoblasts since osteoblastic-lineage cells govern the bone mass variation and regulate a corresponding number of osteoclasts. Furthermore, diverse hormones, cytokines and growth factors that strongly link osteoblasts to osteoclasts coordinated these two cell populations. The understanding of this complex remodeling process and predicting its evolution is crucial to manage bone strength under physiologic and pathologic conditions. Several mathematical models have been suggested to clarify this remodeling process, from the earliest purely phenomenological to the latest biomechanical and mechanobiological models. In this current article, a general mathematical model is proposed to fill the gaps identified in former bone remodeling models. The proposed model is the result of combining existing bone remodeling models to present an updated model, which also incorporates several important parameters affecting bone remodeling under various physiologic and pathologic conditions. Furthermore, the proposed model can be extended to include additional parameters in the future. These parameters are divided into four groups according to their origin, whether endogenous or exogenous, and the cell population they affect, whether osteoclasts or osteoblasts. The model also enables easy coupling of biological models to pharmacological and/or mechanical models in the future.

Combined Effects of Exercise and Denosumab Treatment on Local Failure in Post-menopausal Osteoporosis-Insights from Bone Remodelling Simulations Accounting for Mineralisation and Damage

Denosumab has been shown to increase bone mineral density (BMD) and reduce the fracture risk in patients with post-menopausal osteoporosis (PMO). Increase in BMD is linked with an increase in bone matrix mineralisation due to suppression of bone remodelling. However, denosumab anti-resorptive action also leads to an increase in fatigue microdamage, which may ultimately lead to an increased fracture risk. A novel mechanobiological model of bone remodelling was developed to investigate how these counter-acting mechanisms are affected both by exercise and long-term denosumab treatment. This model incorporates Frost's mechanostat feedback, a bone mineralisation algorithm and an evolution law for microdamage accumulation. Mechanical disuse and microdamage were assumed to stimulate RANKL production, which modulates activation frequency of basic multicellular units in bone remodelling. This mechanical feedback mechanism controls removal of excess bone mass and microdamage. Furthermore, a novel measure of bone local failure due to instantaneous overloading was developed. Numerical simulations indicate that trabecular bone volume fraction and bone matrix damage are determined by the respective bone turnover and homeostatic loading conditions. PMO patients treated with the currently WHO-approved dose of denosumab (60 mg administrated every 6 months) exhibit increased BMD, increased bone ash fraction and damage. In untreated patients, BMD will significantly decrease, as will ash fraction; while damage will increase. The model predicted that, depending on the time elapsed between the onset of PMO and the beginning of treatment, BMD slowly converges to the same steady-state value, while damage is low in patients treated soon after the onset of the disease and high in patients having PMO for a longer period. The simulations show that late treatment PMO patients have a significantly higher risk of local failure compared to patients that are treated soon after the onset of the disease. Furthermore, overloading resulted in an increase of BMD, but also in a faster increase of damage, which may consequently promote the risk of fracture, specially in late treatment scenarios. In case of mechanical disuse, the model predicted reduced BMD gains due to denosumab, while no significant change in damage occurred, thus leading to an increased risk of local failure compared to habitual loading.

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. 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.

Integration of mechanics and biology in computer simulation of bone remodeling

Bone remodeling is a complex physiological process that spans across multiple spatial and temporal scales and is regulated by both mechanical and hormonal cues. An imbalance between bone resorption and bone formation in the process of bone remodeling may lead to various bone pathologies. One powerful and non-invasive approach to gain new insights into mechano-adaptive bone remodeling is computer modeling and simulation. Recent findings in bone physiology and advances in computer modeling have provided a unique opportunity to study the integration of mechanics and biology in bone remodeling. Our objective in this review is to critically appraise recent advances and developments and discuss future research opportunities in computational bone remodeling approaches that enable integration of mechanics and cellular and molecular pathways. Based on the critical appraisal of the relevant recent published literature, we conclude that multiscale in silico integration of personalized bone mechanics and mechanobiology combined with data science and analytics techniques offer the potential to deepen our knowledge of bone remodeling and provide ample opportunities for future research.

Toward a Mathematical Modeling of Diseases' Impact on Bone Remodeling: Technical Review

A wide variety of bone diseases have hitherto been discovered, such as osteoporosis, Paget's disease, osteopetrosis, and metastatic bone disease, which are not well defined in terms of changes in biochemical and mechanobiological regulatory factors. Some of these diseases are secondary to other pathologies, including cancer, or to some clinical treatments. To better understand bone behavior and prevent its deterioration, bone biomechanics have been the subject of mathematical modeling that exponentially increased over the last years. These models are becoming increasingly complex. The current paper provides a timely and critical analysis of previously developed bone remodeling mathematical models, particularly those addressing bone diseases. Besides, mechanistic pharmacokinetic/pharmacodynamic (PK/PD) models, which englobe bone disease and its treatment's effect on bone health. Therefore, the review starts by presenting bone remodeling cycle and mathematical models describing this process, followed by introducing some bone diseases and discussing models of pathological mechanisms affecting bone, and concludes with exhibiting the available bone treatment procedures considered in the PK/PD models.

Analysis of the uniqueness and stability of solutions to problems regarding the bone-remodeling process

Simulation of the bone remodeling process is extremely important because it makes possible the structure forecast of one or several bones when anomalous situations, such as prosthesis installation, occur. Thus, it is necessary that the mathematical model to simulate the bone remodeling process be reliable; that is, the numerical solution must be stable regardless of initial density field for a phenomenological approach to model the process. For several models found in the literature, this characteristic of stability is not observed, largely due to the discontinuities present in the property values of the models (e.g., Young's modulus and Poisson's ratio). In addition, checkerboard formation and the lazy zone prevent the uniqueness of the solution. To correct these difficulties, this study proposes a set of modifications to guarantee the uniqueness and stability of the solutions, when a phenomenological approach is used. The proposed modifications are: (a) change the rate of remodeling curve in the lazy zone region and (b) create transition functions to guarantee the continuity of the expressions used to describe Young's modulus and Poisson's ratio. Moreover, the stress smoothing process controls the checkerboard formation. Numerical analysis is used to simulate the solution behavior from each proposed modification. The results show that, when all proposed modifications are applied to the three-dimensional models simulated here, it is possible to observe the tendency toward a unique solution.

A mechano-chemo-biological model for bone remodeling with a new mechano-chemo-transduction approach

Bone remodeling is a fundamental biological process that develops in bone tissue along its whole lifetime. It refers to a continuous bone transformation with new bone formation and old bone resorption that changes the internal microstructure and composition of the tissue. The main objectives of bone remodeling are: repair of the internal microcracks; adaptation of the macroscopic stiffness and strength to the actual changing mechanical demands; and control of the calcium homeostasis. Understanding this process and predicting its evolution is critical to reduce the effects of long-term disuse as happens during periods of reduced mobility. It is also important in the design of bone implants to avoid long-term stress shielding. Many mathematical models have been proposed from the earliest purely phenomenological to the latest that include biological knowledge. However, there still exists a lack of connection between the mechanical driving force and the biochemical and cell processes it triggers. Here, and following previous works that model independently the mechanobiological and biochemical processes in bone remodeling, we present a more complete model, useful for both cortical and trabecular bone, that uses a new mechanotransduction approach based on the effect of strains onto the bonding-unbonding rate of RANK/RANKL/OPG receptor-ligand reactions. We compare the results of this model with previous ones, showing a good agreement in similar conditions. We also apply it to realistic situations such as a femoral bone after implantation of a hip prosthesis, getting similar results to the clinical ones in the final bone density distribution. Finally, we extend this approach to the anisotropic case, getting not only the mean density, but also the directional homogenization of the microstructure. This biochemical approach permits, not only to predict the bone evolution under changes in the mechanical loads, but also, to consider anabolic and catabolic drugs to control bone density, such as those used in osteoporosis.

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

PURPOSE OF REVIEW

We review the literature on hip fracture mechanics and models of hip strain during exercise to postulate the exercise regimen for best promoting hip strength.

RECENT FINDINGS

The superior neck is a common location for hip fracture and a relevant exercise target for osteoporosis. Current modelling studies showed that fast walking and stair ambulation, but not necessarily running, optimally load the femoral neck and therefore theoretically would mitigate the natural age-related bone decline, being easily integrated into routine daily activity. High intensity jumps and hopping have been shown to promote anabolic response by inducing high strain in the superior anterior neck. Multidirectional exercises may cause beneficial non-habitual strain patterns across the entire femoral neck. Resistance knee flexion and hip extension exercises can induce high strain in the superior neck when performed using maximal resistance loadings in the average population. Exercise can stimulate an anabolic response of the femoral neck either by causing higher than normal bone strain over the entire hip region or by causing bending of the neck and localized strain in the superior cortex. Digital technologies have enabled studying interdependences between anatomy, bone distribution, exercise, strain and metabolism and may soon enable personalized prescription of exercise for optimal hip strength.

Assessment of romosozumab efficacy in the treatment of postmenopausal osteoporosis: Results from a mechanistic PK-PD mechanostat model of bone remodeling

This paper introduces a theoretical framework for the study of the efficacy of romosozumab, a humanized monoclonal antibody targeting sclerostin for the treatment of osteoporosis. We developed a comprehensive mechanistic pharmacokinetic-pharmacodynamic (PK-PD) model of the effect of drug treatment on bone remodeling in postmenopausal osteoporosis (PMO). We utilized a one-compartment PK model to represent subcutaneous injections of romosozumab and subsequent absorption into serum. The PD model is based on a recently-developed bone cell population model describing the bone remodeling process at the tissue scale. The latter accounts for mechanical feedback by incorporating nitric oxide (NO) and sclerostin (Scl) as biochemical feedback molecules. Utilizing a competitive binding model, where Wnt and Scl compete for binding to LRP5/6, allows to regulate anabolic bone remodeling responses. Here, we extended this model with respect to romosozumab binding to sclerostin. For the currently approved monthly injections of 210 mg, the model predicted a 6.59%, 10.38% and 15.25% increase in BMD at the lumbar spine after 6, 12 and 24 months, respectively. These results are in good agreement with the data reported in the literature. Our model is also able to distinguish the bone-site specific drug effects. For instance, at the femoral neck, our model predicts a BMD increase of 3.85% after 12 months of 210 mg injections, which is consistent with literature observations. Finally, our simulations indicate rapid bone loss after treatment discontinuation, indicating that some additional interventions such as use of bisphosphonates are required to maintain bone mass.

Study of the combined effects of PTH treatment and mechanical loading in postmenopausal osteoporosis using a new mechanistic PK-PD model

One of only a few approved and available anabolic treatments for severe osteoporosis is daily injections of PTH (1-34). This drug has a specific dual action which can act either anabolically or catabolically depending on the type of administration, i.e. intermittent or continuous, respectively. In this paper, we present a mechanistic pharmacokinetic-pharmacodynamic model of the action of PTH in postmenopausal osteoporosis. This model accounts for anabolic and catabolic activities in bone remodelling under intermittent and continuous administration of PTH. The model predicts evolution of common bone biomarkers and bone volume fraction (BV/TV) over time. We compared the relative changes in BV/TV resulting from a daily injection of 20 [Formula: see text]g of PTH with experimental data from the literature. Simulation results indicate a site-specific bone gain of 8.66[Formula: see text] (9.4 ± 1.13[Formula: see text]) at the lumbar spine and 3.14[Formula: see text] (2.82 ± 0.72[Formula: see text]) at the femoral neck. Bone gain depends nonlinearly on the administered dose, being, respectively, 0.68[Formula: see text], 3.4[Formula: see text] and 6.16[Formula: see text] for a 10, 20 and 40 [Formula: see text]g PTH dose at the FN over 2 years. Simulations were performed also taking into account a bone mechanical disuse to reproduce elderly frail subjects. The results show that mechanical disuse ablates the effects of PTH and leads to a 1.08% reduction of bone gain at the FN over a 2-year treatment period for the 20 [Formula: see text]g of PTH. The developed model can simulate a range of pathological conditions and treatments in bones including different PTH doses, different mechanical loading environments and combinations. Consequently, the model can be used for testing and generating hypotheses related to synergistic action between PTH treatment and physical activity.