Influence of a change in activity regime on femoral bone architecture and failure behaviour

The incidence and morbidity of femoral fractures increases drastically with age. Femoral architecture and associated fracture risk are strongly influenced by loading during physical activities and it has been shown that the rate of loss of bone mineral density is significantly lower for active individuals than inactive. The objective of this work is to evaluate the impact of a cessation of some physical activities on elderly femoral structure and fracture behaviour. The authors previously established a biofidelic finite element model of the femur considered as a structure optimised to loading associated with daily activities. The same structural optimisation algorithm was used here to quantify the changes in bone architecture following cessation of stair climbing and sit-to-stand. Side fall fracture simulations were run on the adapted bone structures using a damage elasticity formulation. Total cortical and trabecular bone volume and failure load reduced in all cases of activity cessation. Bone loss distribution was strongly heterogeneous, with some locations even showing increased bone volume. This work suggests that maintaining the physical activities involved in the daily routine of a young healthy adult would help reduce the risk of femoral fracture in the elderly population by preventing bone loss.

Abstract 5699: Development and validation of a quantitative systems pharmacology model for prediction of preclinical efficacy of PARP inhibitors rucaparib and talazoparib combined with the ATR inhibitor gartisertib (M4344)

Introduction: Poly (ADP-ribose) polymerase (PARP) and ataxia telangiectasia and Rad3-related (ATR) inhibitors target key DNA damage response (DDR) kinases. PARP inhibitors (PARPi) suppress the catalytic activity of PARP and trap PARP in a complex with damaged DNA, resulting in the accumulation of unrepaired single-strand breaks (SSBs) and stalled replication forks. Loss of ATR activity blocks cell cycle arrest induced by single-stranded DNA and sensitizes cancer cells to agents that induce DNA replication stress. Thus, PARP inhibition synergizes (through synthetic lethality) with concurrent ATR inhibition by inducing replication fork collapse, double-strand breaks (DSBs), and PARP-DNA complex formation, with simultaneous loss of intra-S and G2/M checkpoints and suppression of DNA-damage repair, leading to mitotic catastrophe. Four PARPi are currently approved for the treatment of various cancers and several ATR inhibitors (ATRi) are in clinical trials either as monotherapies or in combination with other chemotherapeutic agents. We developed and validated a semi-mechanistic quantitative systems pharmacology (QSP) model that represents the mechanisms of action of PARPi and ATRi with minimal parameters, which could be used to inform the optimization of combination regimens.

Methods: A QSP model of a growing cancer cell population was developed by considering SSBs and DSBs, and parallel DNA repair pathways relying on PARP and ATR. PARPi and ATRi mediated saturable inhibitory effects on their respective DDR pathways, while PARP-DNA trapping was represented as an increased conversion rate from SSBs to DSBs. Phenotypic impairments of the DDR such as BRCA mutations were embedded as DDR pathway deficiencies. The model was calibrated using experimental data derived from rucaparib and talazoparib combination studies with gartisertib.

Results: The calibrated model captured well the tumor-growth inhibition observed in the HBCx9 PDX model for rucaparib and gartisertib, either alone or in combination, over average daily doses ranging from 50 mg/kg to 200 mg/kg (QD/BID) of rucaparib and 1-3 mg/kg (QD/BIW/QD alternate weeks) of gartisertib. The model was also able to predict the wide range of responses (from shrinkage to progressive disease) observed in a panel of triple-negative breast cancer PDX models (BRCA-mutant and wild type) treated with talazoparib and gartisertib in combination. The complete DDR model utilized 9 variable parameters, and the mechanisms of action of PARP and ATR inhibition were described by 4 parameters each.

Conclusion: This newly developed QSP model provides a framework that can be applied to optimize the dosing regimens of PARP and ATR inhibitor combinations and help with clinical dosing strategy.

Citation Format: Claire C. Villette, Frances Brightman, Nathalie Dupuy, Astrid Zimmermann, Florianne Lignet, Frank T. Zenke, Nadia Terranova, Jayaprakasam Bolleddula, Samer El Bawab, Christophe Chassagnole. Development and validation of a quantitative systems pharmacology model for prediction of preclinical efficacy of PARP inhibitors rucaparib and talazoparib combined with the ATR inhibitor gartisertib (M4344). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5699.

Should personalised dosing have a role in cancer treatment?

Almost all pharmaceutical products are approved on the basis of their effect in patients representing the "average" of the population studied in registrational trials, with most drug labels allowing, at most, for empirical dose reduction in the case of toxicity. In this perspective article we explore some of the evidence that supports the use of personalised dosing in cancer treatment and show how we have been able to build on existing models linking dose, exposure and toxicity to demonstrate how dose optimisation, including increasing the dose, has the potential to significantly improve efficacy outcomes. We also explore, through the lens of our own experience of developing a personalised dosing platform, some of the hurdles that stand in the way of implementing a personalised approach to dosing in real world settings. In particular, our experience is illustrated by the application of a dosing platform for docetaxel treatment in prostate cancer.

Multitechnology Biofabrication: A New Approach for the Manufacturing of Functional Tissue Structures?

Most available 3D biofabrication technologies rely on single-component deposition methods, such as inkjet, extrusion, or light-assisted printing. It is unlikely that any of these technologies used individually would be able to replicate the complexity and functionality of living tissues. Recently, new biofabrication approaches have emerged that integrate multiple manufacturing technologies into a single biofabrication platform. This has led to fabricated structures with improved functionality. In this review, we provide a comprehensive overview of recent advances in the integration of different manufacturing technologies with the aim to fabricate more functional tissue structures. We provide our vision on the future of additive manufacturing (AM) technology, digital design, and the use of artificial intelligence (AI) in the field of biofabrication.

Multitechnology Biofabrication: A New Approach for the Manufacturing of Functional Tissue Structures?

Most available 3D biofabrication technologies rely on single-component deposition methods, such as inkjet, extrusion, or light-assisted printing. It is unlikely that any of these technologies used individually would be able to replicate the complexity and functionality of living tissues. Recently, new biofabrication approaches have emerged that integrate multiple manufacturing technologies into a single biofabrication platform. This has led to fabricated structures with improved functionality. In this review, we provide a comprehensive overview of recent advances in the integration of different manufacturing technologies with the aim to fabricate more functional tissue structures. We provide our vision on the future of additive manufacturing (AM) technology, digital design, and the use of artificial intelligence (AI) in the field of biofabrication.

Rate and age-dependent damage elasticity formulation for efficient hip fracture simulations

Prediction of bone failure is beneficial in a range of clinical situations from screening of osteoporotic patients with high fracture risk to assessment of protective equipment against trauma. Computational efficiency is an important feature to consider when developing failure models for iterative applications, such as patient-specific diagnosis or design of orthopaedic devices. The authors previously developed a methodology to generate efficient mesoscale structural full bone models. The aim of this study was to implement a damage elasticity formulation representative of an elasto-plastic material model with age and strain rate dependencies compatible with these structural models. This material model was assessed in the prediction of femoral fractures in longitudinal compression and side fall scenarios. The simulations predicted failure loads and fracture patterns in good agreement with reported results from experimental studies. The observed influence of strain rate on failure load was consistent with literature. The superiority of a simplified elasto-plastic formulation over an elasto-brittle bone material model was assessed. This computationally efficient damage elasticity formulation was capable of capturing fracture development after onset.

Microscale poroelastic metamodel for efficient mesoscale bone remodelling simulations

Bone functional tissue adaptation is a multiaspect physiological process driven by interrelated mechanical and biological stimuli which requires the combined activity of osteoclasts and osteoblasts. In previous work, the authors developed a phenomenological mesoscale structural modelling approach capable of predicting internal structure of the femur based on daily activity loading, which relied on the iterative update of the cross-sectional areas of truss and shell elements representative of trabecular and cortical bones, respectively. The objective of this study was to introduce trabecular reorientation in the phenomenological model at limited computational cost. To this aim, a metamodel derived from poroelastic microscale continuum simulations was used to predict the functional adaptation of a simplified proximal structural femur model. Clear smooth trabecular tracts are predicted to form in the regions corresponding to the main trabecular groups identified in literature, at minimal computational cost.

Informing phenomenological structural bone remodelling with a mechanistic poroelastic model

Studies suggest that fluid motion in the extracellular space may be involved in the cellular mechanosensitivity at play in the bone tissue adaptation process. Previously, the authors developed a mesoscale predictive structural model of the femur using truss elements to represent trabecular bone, relying on a phenomenological strain-based bone adaptation algorithm. In order to introduce a response to bending and shear, the authors considered the use of beam elements, requiring a new formulation of the bone adaptation drivers. The primary goal of the study presented here was to isolate phenomenological drivers based on the results of a mechanistic approach to be used with a beam element representation of trabecular bone in mesoscale structural modelling. A single-beam model and a microscale poroelastic model of a single trabecula were developed. A mechanistic iterative adaptation algorithm was implemented based on fluid motion velocity through the bone matrix pores to predict the remodelled geometries of the poroelastic trabecula under 42 different loading scenarios. Regression analyses were used to correlate the changes in poroelastic trabecula thickness and orientation to the initial strain outputs of the beam model. Linear (R(2) > 0.998) and third-order polynomial (R(2) > 0.98) relationships were found between change in cross section and axial strain at the central axis, and between beam reorientation and ratio of bending strain to axial strain, respectively. Implementing these relationships into the phenomenological predictive algorithm for the mesoscale structural femur has the potential to produce a model combining biofidelic structure and mechanical behaviour with computational efficiency.

The influence of extreme speeds on scapula kinematics and the importance of controlling the plane of elevation

BACKGROUND

The effect of high-speed movement on scapula kinematics is not clear from the literature. Understanding these effects is important for clinicians examining, managing and understanding scapula kinematic pathologies: impingement, glenohumeral instability, muscle patterning instability and athletic injuries. The scapula tracking methodology and the lack of quantified control of the movement's plane of elevation limits previous studies. The aim of the present study is to use improved dynamic scapula kinematic measurement to assess differences during planar movements across different speeds. Athletic and maximal speeds, neglected in previous studies, are the focus.

METHODS

Thirteen subjects performed slow, fast and maximal scapula plane abduction and forward flexion. A previously validated skin-fixed scapula tracker was used and optimally calibrated. A stiff board controlled the plane of elevation. Scapula kinematics were consistent with the literature.

FINDINGS

Large and statistically significant differences were found to exist between scapula kinematics at slow speeds compared to fast and maximal speeds in lateral rotation and protraction. Although some differences were observed in the plane of elevation between speeds, these were not considered to effect the conclusions.

INTERPRETATION

The speed of movement should be considered an important factor affecting scapula kinematics. Clinical studies analysing muscle recruitment strategies and causes of injury in athletic tasks must account for changing kinematics rather than extrapolating slow or static measures and effective clinical examination and management of pathology must take these kinematic changes into account. Control of the plane of movement is challenging and its effectiveness must be quantified in future kinematic studies.