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

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.

Modeling and simulation of bone cells dynamic behavior under the late effect of breast cancer treatments

Breast Cancer (BC) treatments have been proven to interfere with the health of bones. Chemotherapy and endocrinal treatment regimens such as tamoxifen and aromatase inhibitors are frequently prescribed for women with BC. However, these drugs increase bone resorption and reduce the Bone Mineral Density (BMD), thus increasing the risk of bone fracture. In the current study, a mechanobiological bone remodeling model has been developed by coupling cellular activities, mechanical stimuli, and the effect of breast cancer treatments (chemotherapy, tamoxifen, and aromatase inhibitors). This model algorithm has been programmed and implemented on MATLAB software to simulate different treatment scenarios and their effects on bone remodeling and also predict the evolution of Bone Volume fraction (BV/TV) and the associated Bone Density Loss (BDL) over a period of time. The simulation results, achieved from different combinations of Breast Cancer treatments, allow the researchers to predict the intensity of each combination treatment on BV/TV and BMD. The combination of chemotherapy, tamoxifen, and aromatase inhibitors, followed by the combination of chemotherapy and tamoxifen remain the most harmful regimen. This is because they have a strong ability to induce the bone degradation which is represented by a decrease of 13.55% and 11.55% of the BV/TV value, respectively. These results were compared with the experimental studies and clinical observations which showed good agreement. The proposed model can be used by clinicians and physicians to choose the most appropriate combination of treatments, according to the patient's case.

A multi-model approach to predict efficacious clinical dose for an anti-TGF-β antibody (GC2008) in the treatment of osteogenesis imperfecta

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited bone dysplasias characterized by reduced skeletal mass and bone fragility. Although the primary manifestation of the disease involves the skeleton, OI is a generalized connective tissue disorder that requires a multidisciplinary treatment approach. Recent studies indicate that application of a transforming growth factor beta (TGF-β) neutralizing antibody increased bone volume fraction (BVF) and strength in an OI mouse model and improved bone mineral density (BMD) in a small cohort of patients with OI. In this work, we have developed a multitiered quantitative pharmacology approach to predict human efficacious dose of a new anti-TGF-β antibody drug candidate (GC2008). This method aims to translate GC2008 pharmacokinetic/pharmacodynamic (PK/PD) relationship in patients, using a number of appropriate mathematical models and available preclinical and clinical data. Compartmental PK linked with an indirect PD effect model was used to characterize both pre-clinical and clinical PK/PD data and predict a GC2008 dose that would significantly increase BMD or BVF in patients with OI. Furthermore, a physiologically-based pharmacokinetic model incorporating GC2008 and the body's physiological properties was developed and used to predict a GC2008 dose that would decrease the TGF-β level in bone to that of healthy individuals. By using multiple models, we aim to reveal information for different aspects of OI disease that will ultimately lead to a more informed dose projection of GC2008 in humans. The different modeling efforts predicted a similar range of pharmacologically relevant doses in patients with OI providing an informed approach for an early clinical dose setting.

Clinical Data for Parametrization of In Silico Bone Models Incorporating Cell-Cytokine Dynamics: A Systematic Review of Literature

In silico simulations aim to provide fast, inexpensive, and ethical alternatives to years of costly experimentation on animals and humans for studying bone remodeling, its deregulation during osteoporosis and the effect of therapeutics. Within the varied spectrum of in silico modeling techniques, bone cell population dynamics and agent-based multiphysics simulations have recently emerged as useful tools to simulate the effect of specific signaling pathways. In these models, parameters for cell and cytokine behavior are set based on experimental values found in literature; however, their use is currently limited by the lack of clinical in vivo data on cell numbers and their behavior as well as cytokine concentrations, diffusion, decay and reaction rates. Further, the settings used for these parameters vary across research groups, prohibiting effective cross-comparisons. This review summarizes and evaluates the clinical trial literature that can serve as input or validation for in silico models of bone remodeling incorporating cells and cytokine dynamics in post-menopausal women in treatment, and control scenarios. The GRADE system was used to determine the level of confidence in the reported data, and areas lacking in reported measures such as binding site occupancy, reaction rates and cell proliferation, differentiation and apoptosis rates were highlighted as targets for further research. We propose a consensus for the range of values that can be used for the cell and cytokine settings related to the RANKL-RANK-OPG, TGF-β and sclerostin pathways and a Levels of Evidence-based method to estimate parameters missing from clinical trial literature.

Efficacy and safety of romosozumab among Japanese postmenopausal women with osteoporosis and mild-to-moderate chronic kidney disease

INTRODUCTION

This post hoc analysis of the placebo-controlled phase 3 FRAME study assessed the efficacy and safety of romosozumab in a subpopulation of Japanese postmenopausal women with osteoporosis and chronic kidney disease (CKD).

MATERIALS AND METHODS

Data were analyzed by baseline estimated glomerular filtration rate (eGFR), where < 90 mL/min/1.73 m² denoted CKD and ≥ 90 mL/min/1.73 m² indicated normal renal function. Efficacy outcomes included percent change in lumbar spine, total hip, and femoral neck bone mineral density (BMD) at 12 months from baseline (primary) and incidence of new vertebral and non-vertebral fractures. Tolerability was also assessed.

RESULTS

Of 489 Japanese patients with available eGFR data, 339 had mild-to-moderate CKD (romosozumab, n = 170; placebo, n = 169) and 150 had normal renal function (romosozumab, n = 75; placebo, n = 75). Compared with placebo, romosozumab increased lumbar spine BMD by 14.8% (95% confidence interval [CI] 13.7-15.9) and 15.2% (95% CI 13.4-16.9) in the eGFR < 90 and ≥ 90 mL/min/1.73 m² subgroups, total hip BMD by 4.6% (95% CI 3.8-5.4) and 5.5% (95% CI 4.4-6.7), and femoral neck BMD by 4.0% (95% CI 2.9-5.2) and 5.5% (95% CI 3.8-7.1) at 12 months, respectively (all p < 0.001 vs. placebo). New vertebral fracture incidence was numerically lower with romosozumab than placebo at 12 months in both eGFR subgroups, while the incidence of adverse events was similar between subgroups.

CONCLUSION

Romosozumab for 12 months is an effective and well-tolerated treatment option for Japanese patients with osteoporosis and mild-to-moderate CKD.

Therapeutic Treatments for Osteoporosis-Which Combination of Pills Is the Best among the Bad?

Osteoporosis is a chronical, systemic skeletal disorder characterized by an increase in bone resorption, which leads to reduced bone density. The reduction in bone mineral density and therefore low bone mass results in an increased risk of fractures. Osteoporosis is caused by an imbalance in the normally strictly regulated bone homeostasis. This imbalance is caused by overactive bone-resorbing osteoclasts, while bone-synthesizing osteoblasts do not compensate for this. In this review, the mechanism is presented, underlined by in vitro and animal models to investigate this imbalance as well as the current status of clinical trials. Furthermore, new therapeutic strategies for osteoporosis are presented, such as anabolic treatments and catabolic treatments and treatments using biomaterials and biomolecules. Another focus is on new combination therapies with multiple drugs which are currently considered more beneficial for the treatment of osteoporosis than monotherapies. Taken together, this review starts with an overview and ends with the newest approaches for osteoporosis therapies and a future perspective not presented so far.

Mechanical stimuli-mediated modulation of bone cell function-implications for bone remodeling and angiogenesis

Bone remodeling, expressed as bone formation and turnover, is a complex and dynamic process closely related to its form and function. Different events, such as development, aging, and function, play a critical role in bone remodeling and metabolism. The ability of the bone to adapt to new loads and forces has been well known and has proven useful in orthopedics and insightful for research in bone and cell biology. Mechanical stimulation is one of the most important drivers of bone metabolism. Interestingly, different types of forces will have specific consequences in bone remodeling, and their beneficial effects can be traced using different biomarkers. In this narrative review, we summarize the major mediators and events in bone remodeling, focusing on the effects of mechanical stimulation on bone metabolism, cell populations, and ultimately, bone health.

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.

Modeling the Impact of Microgravity at the Cellular Level: Implications for Human Disease

A lack of gravity experienced during space flight has been shown to have profound effects on human physiology including muscle atrophy, reductions in bone density and immune function, and endocrine disorders. At present, these physiological changes present major obstacles to long-term space missions. What is not clear is which pathophysiological disruptions reflect changes at the cellular level versus changes that occur due to the impact of weightlessness on the entire body. This review focuses on current research investigating the impact of microgravity at the cellular level including cellular morphology, proliferation, and adhesion. As direct research in space is currently cost prohibitive, we describe here the use of microgravity simulators for studies at the cellular level. Such instruments provide valuable tools for cost-effective research to better discern the impact of weightlessness on cellular function. Despite recent advances in understanding the relationship between extracellular forces and cell behavior, very little is understood about cellular biology and mechanotransduction under microgravity conditions. This review will examine recent insights into the impact of simulated microgravity on cell biology and how this technology may provide new insight into advancing our understanding of mechanically driven biology and disease.