A new framework for computational biomechanical models and 3Rs in musculoskeletal research.

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This project has two overarching goals: (1) to investigate the type and amount of experimental input data required for musculoskeletal computer models to deliver accurate predictions, and (2) in doing so provide quantitative data on the current and future potential of models to contribute to the reduction, replacement and refinement (3Rs) of animal experiments in scientific research. To do this we will develop and validate new computational biomechanical models using mastication in rabbits as our case study. Validating computer models requires a large amount of experimental data about rabbit anatomy and feeding mechanics (e.g. muscle and bite forces). This data does not exist for rabbits, or indeed any other experimental animal. Therefore a systematic anatomical and biomechanical investigation of rabbit feeding is required in which all the primary determinants of feeding mechanics are measured from a cohort of rabbits. Computational models constructed from medical imaging data of those same rabbits can then be directly and immediately used to improve and validate computer simulations. Only in this way can models be truly validated and their potential for achieving 3Rs in future studies be demonstrated. Our specific objectives are therefore to collect: anatomical and image data on bone and muscle morphology in rabbits; in vivo data on bone motion and muscle physiology as they eat various food types; and combine these data to build and validate new computer models of rabbit feeding biomechanics.Rabbits have been chosen because they are widely used in a variety of research areas. They are the first-choice experimental animal for dental implant design and bone (re)growth studies because of their size, easy handling and relative similarities to humans in terms of bone composition, healing and anatomy. These experiments, like many in musculoskeletal research, are highly invasive, causing pain and distress to the animals before they are euthanized. A digital model has the potential to completely replace (or maximally reduce) the use of animals in musculoskeletal research and/or medical device design. The anatomy and behaviour of a digital model can be altered and re-tested without limitation and without any harm or distress to a real animal. This can also allow, for example: a model analysis to be extended to a different strain/breed of the same species (or a similar species) by digital modification of the anatomy/behaviour; elements of anatomy to be modified in multiple ways (e.g. removal of teeth/bone) to examine the consequences of different surgical approaches; and for implant devices to be digitally inserted into the models, and their impact on performance examined, all without the need for any harmful experimentation on real animals. But improving biomechanical models will not only reduce animal use in research, but has the potential to improve modelling of human biomechanics. Currently models are used widely to study healthy biomechanics (e.g. sports performance), ageing (e.g. sacropenia) and related diseases (e.g. knee osteoarithitis), dental procedures (e.g. orthodontic treatment) and injury (e.g. hip fracture). In these human studies they are used to estimate or predict parameters that cannot be measured directly in people, thus their accuracy is inherently difficult to assess. Thus there is clear need for the type of study we propose here.In the first instance we will generate the most comprehensive biomechanical models produced to-date using our exhaustive and state-of-the-art experimental dataset. This will provide a best-case scenario for model accuracy. We will then incrementally reduce the resolution of input data given to the model and observe the effects on accuracy. This will tell us how individual input parameters effect accuracy and help the musculoskeletal research community identify which parameters do not need to be measured through experimentation in real animals to achieve the necessary accuracy.