A novel multi-scale computational model to evaluate the effect of musculoskeletal interventions in preclinical studies

Bone remodelling (BR) is affected by musculoskeletal pathologies such as osteoporosis and osteoarthritis. Therefore, in order to develop new interventions for such diseases a comprehensive understanding of BR in healthy, pathological and treated condition is needed.
Currently, the efficacy of novel musculoskeletal interventions needs to be tested on animals before its application to clinical studies. Mice models are used intensively due to their low cost and the possibility of performing advanced measurements such as in vivo micro computed tomography (microCT). Computational models that predict the effect of diseases and related interventions on the BR and on the bone densitometric, morphometric and mechanical properties, can be a potential tool to optimise treatments and to reduce and partially replace the usage of mice in musculoskeletal research. Nevertheless, BR is a complex physical phenomenon hard to be modelled due to its multi-scale nature: the bone cells remodel the bone tissue due to local biochemical stimuli and to mechanical stimuli that are heterogeneously distributed on the tissue under external loads applied to the whole bone. Moreover, before any applications, the outcomes of the models need to be calibrated and independently validated by comparison with accurate experimental analyses.

In this project for the first time we will develop, calibrate and validate a multi-scale computational model of BR and test it for different musculoskeletal interventions. The model will be based on the combination of physiology-based finite element (FE) models, which evaluate the mechanical stimuli in the whole bone given a certain loading condition, and ordinary differential equations (ODE), which model the effect of combined mechanical and biochemical stimuli on the cell activity. The combination of the two models will allow predicting the effect of interventions that affect the mechanics (e.g. physical exercise) and/or the biochemistry of the bone (e.g. injection of anabolic treatments) on the BR over time. With the combination of the two models applied to an initial high resolution scan of the mouse tibia we will be able to estimate the bone changes over time in mice treated or not with mechanical or biochemical interventions. The outcomes of the models will be validated against measurement of changes in bone properties using longitudinal in vivo microCT analyses of the mouse tibia.

The successful model can be used to predict the effect of novel interventions given a small dataset from in vivo animal studies for proper calibration and could be used to predict the bone changes in case, for example, of different doses, administration times or combination of treatments.

Eligibility Requirements
The successful candidate should have or be expected to obtain a 1st class or a good 2.1 degree in mechanical engineering, bioengineering, computer science, physics, applied mathematics or a related discipline.