Soft tissue related diseases (heart, cancer, eyes) are among the leading causes of death worldwide. Despite extensive biomedical research, a major challenge is a lack of mathematical models that predict soft tissue mechanics across subcellular to whole organ scales during disease progression. Given the tremendous scope, the unmet clinical needs, our limited manpower, and the existence of complementary expertise, we seek to forge NEW collaborations with two world-leading research centres: MIT and POLIMI, to embark on two challenging themes that will significantly stretch the initial SofTMech remit: A) Test-based microscale modelling and upscaling, and B) Beyond static hyperelastic material to include viscoelasticity, nonlinear poroelasticity, tissue damage and healing. Our research will lead to a better understanding of how our bodies work, and this knowledge will be applied to help medical researchers and clinicians in developing new therapies to minimise the damage caused by disease progression and implants, and to develop more effective treatments. The added value will be a major leap forward in the UK research. It will enable us to model soft tissue damage and healing in many clinical applications, to study the interaction between tissue and implants, and to ensure model reproducibility through in vitro validations. The two underlying themes will provide the key feedback between tissue and cells and the response of cells to dynamic local environments. For example, advanced continuum mechanics approaches will shed new light on the influence of cell adhesion, angiogenesis and stromal cell-tumour interactions in cancer growth and spread, and on wound healing implant insertion that can be tested with in vitro and in vivo systems. Our theoretical framework will provide insight for the design of new experiments. Our proposal is unique, timely and cost-effectively because advances in micro- and nanotechnology from MIT and POLIMI now enable measurements of sub-cellular, single cell, and cell-ECM dynamics, so that new theories of soft tissue mechanics at the nano- and micro-scales can be tested using in vitro prototypes purposely built for SofTMech. Bridging the gaps between models at different scales is beyond the ability of any single centre. SofTMech-MP will cluster the critical mass to develop novel multiscale models that can be experimentally tested by biological experts within the three world-leading Centres. SofTMech-MP will endeavour to unlock the chain of events leading from mechanical factors at subcellular nanoscales to cell and tissue level biological responses in healthy and pathological states by building a new mathematics capacity. Our novel multiscale modelling will lead to new mathematics including new numerical methods, that will be informed and validated by the design and implementation of experiments at the MIT and POLIMI centres. This will be of enormous benefit in attacking problems involving large deformation poroelasticity, nonlinear viscoelasticity, tissue dissection, stent-related tissue damage, and wound healing development. We will construct and analyse data-based models of cellular and sub-cellular mechanics and other responses to dynamic local anisotropic environments, test hypotheses in mechanistic models, and scale these up to tissue-level models (evolutionary equations) for growth and remodelling that will take into account the dynamic, inhomogeneous, and anisotropic movement of the tissue. Our models will be simulated in the various projects by making use of the scientific computing methodologies, including the new computer-intensive methods for learning the parameters of the differential equations directly from noisy measurements of the system, and new methods for assessing alternative structures of the differential equations, corresponding to alternative hypotheses about the underlying biological mechanisms.

The lifETIME CDT will focus on the development of non-animal technologies (NATs) for use in drug development, toxicology and regenerative medicine. The industrial life sciences sector accounts for 22% of all business R&D spend and generates £64B turnover within the UK with growth expected at 10% pa over the next decade. Analysis from multiple sources [1,2] have highlighted the limitations imposed on the sector by skills shortages, particularly in the engineering and physical sciences area. Our success in attracting pay-in partners to invest in training of the skills to deliver next-generation drug development, toxicology and regenerative medicine (advanced therapeutic medicine product, ATMP) solutions in the form of NATs demonstrates UK need in this growth area. The CDT is timely as it is not just the science that needs to be developed, but the whole NAT ecosystem - science, manufacture, regulation, policy and communication. Thus, the CDT model of producing a connected community of skilled field leaders is required to facilitate UK economic growth in the sector. Our stakeholder partners and industry club have agreed to help us deliver the training needed to achieve our goals. Their willingness, again, demonstrates the need for our graduates in the sector. This CDT's training will address all aspects of priority area 7 - 'Engineering for the Bioeconomy'. Specifically, we will: (1) Deliver training that is developed in collaboration with and is relevant to industry. - We align to the needs of the sector by working with our industrial partners from the biomaterials, cell manufacture, contract research organisation and Pharma sectors. (2) Facilitate multidisciplinary engineering and physical sciences training to enable students to exploit the emerging opportunities. - We build in multidisciplinarity through our supervisor pool who have backgrounds ranging from bioengineering, cell engineering, on-chip technology, physics, electronic engineering, -omic technologies, life sciences, clinical sciences, regenerative medicine and manufacturing; the cohort community will share this multidisciplinarity. Each student will have a physical science, a biomedical science and a stakeholder supervisor, again reinforcing multidisciplinarity. (3) Address key challenges associated with medicines manufacturing. - We will address medicines manufacturing challenges through stakeholder involvement from Pharma and CROs active in drug screening including Astra Zeneca, Charles River Laboratories, Cyprotex, LGC, Nissan Chemical, Reprocell, Sygnature Discovery and Tianjin. (4) Embed creative approaches to product scale-up and process development. - We will embed these approaches through close working with partners including the Centre for Process Innovation, the Cell and Gene Therapy Catapult and industrial partners delivering NATs to the marketplace e.g. Cytochroma, InSphero and OxSyBio. (5) Ensure students develop an understanding of responsible research and innovation (RRI), data issues, health economics, regulatory issues, and user-engagement strategies. - To ensure students develop an understanding of RRI, data issues, economics, regulatory issues and user-engagement strategies we have developed our professional skills training with the Entrepreneur Business School to deliver economics and entrepreneurship, use of TERRAIN for RRI, links to NC3Rs, SNBTS and MHRA to help with regulation training and involvement of the stakeholder partners as a whole to help with user-engagement. The statistics produced by Pharma, UKRI and industry, along with our stakeholder willingness to engage with the CDT provides ample proof of need in the sector for highly skilled graduates. Our training has been tailored to deliver these graduates and build an inclusive, cohesive community with well-developed science, professional and RRI skills. [1] https://goo.gl/qNMTTD [2] https://goo.gl/J9u9eQ

Heart disease is the leading cause of disability and death in the UK and worldwide, resulting in enormous health care costs. Risk prediction on an individual patient basis is imperfect. Advanced medical development has already saved many lives, particularly in systolic heart failure. However, there is currently no treatment option for diastolic heart failure (with preserved ejection fraction) due to its complexity of multiple mechanisms and co-modality. Structural heart diseases, such as myocardial infarction (MI- commonly known as heart attack) and mitral regurgitation (MR, a leakage of blood through the mitral valve to left atrium in systole), where biomechanical factors are crucial, are often precursors to heart failure. MI can eventually lead to dilated heart failure despite immediate treatments post-MI. MR can induce pulmonary hypertension and oedema and subsequently, right heart overload and heart failure. The grand challenge is for these situations the heart simply cannot be modelled as an isolated left ventricle (as in most of the current studies); flow-structure interaction (FSI), heart-valve interaction, multiscale soft tissue mechanics, and tissue growth and remodelling (G&R) all play important roles in the progression of the structural diseases. This project is set up to meet this challenge by delivering a multiscale computational framework to include Whole-Heart FSI with G&R. Making use of the novel mathematical tools (constitutive laws, G&R, upscaling and statistical inference) developed by SofTMech, I will build a realistic four-chamber heart model that include heart-valve, chamber-chamber, heart-blood, and heart-circulation interactions, which will be powerful enough to model MI, MR and their pathological consequences. This work will be in close collaboration with my clinical, industrial and academic collaborators. The model will quantify which factors lead to adverse G&R and what variations are to be expected as the disease progresses. We will also identify significant biomechanical markers (e.g. constitutive parameters, energy indices, stress/strain evolution). The predictive values of these biomechanical parameters will be assessed against other established predictors of adverse remodellings, such as duration of ischaemia, final coronary flow grade after a primary percutaneous coronary intervention, and microvascular obstruction revealed by MRI. Thus, this project will generate new testable hypotheses and will be a significant step up towards more consistent decision-support for clinicians, since increasingly the pace and complexity of medical advances outstrip the ability of individual clinicians to cope with. Due to the statistical emulation and uncertainty quantification built into the project, the model predictions will be fast and quantified with error bounds on the outcome of alternative treatments. Consequently, we will also address the critical aspect of convincing clinicians that information obtained from simulations will be correct and relevant to their daily practice. The proposed research is right within the Healthcare Technologies "Optimising Treatment" and "Developing Future Therapies" priority areas, as well as targeting "New Connections from Mathematical Sciences", and "Statistics and Applied Probability" of Mathematical Sciences.