In the UK, musculoskeletal disorders (joint and back problems) affect one in five people long term. While joint replacements are successful, they are challenged by demands of an active and younger population presenting with disorders due to trauma, obesity, or other lifestyle choices. One of the causes for joint and back pain is the deterioration of the different soft tissues acting as cushions in the joints. New surgical interventions are being developed to repair or locally replace those soft tissues in order to delay or prevent a total joint replacement. There is no clear indication yet on which patients benefit the most from them. There is an urgent need to define the type of patients for which new and existing interventions are most beneficial. The local anatomy or level of tissue deterioration differs greatly between patients, and there is currently a lack of biomechanical evidence that takes into account these large variations to help matching patients to interventions. To tackle these issues, this Fellowship, MSKDamage, will develop novel testing methods and tools combining laboratory simulation with computer modelling and imaging. MSKDamage methods will be used to predict the variation in the mechanical performance of a series of treatments at various levels of joint deterioration. This will enable the different interventions to be matched to different patient's characteristics. I will focus on three musculoskeletal disorders and associated repairs: 1. Emerging treatments involving the injection of biomaterials in the intervertebral disc: I will produce realistic testing conditions that can be personalised to a specific patient, assessing each patient's chance of success and identifying areas for treatment optimisation. 2. Evaluation of meniscus repairs in the knee and their interaction with cartilage defects: I will provide new information on the type of cartilage defect that reduces the chances of success of a meniscus replacement in the knee. The research will develop guidance on the type of cartilage defects that need repair for a meniscus replacement to be successful. 3. Optimisation of custom wrist repair: I will help optimise patient-specific wrist repairs so that they reduce the damage in tendons and ligaments in the wrist. MSKDamage builds on my strong track-record in the field and network of industry, clinical and academic collaborators, as well as my recent work that demonstrates the specific information which need to be included in models of degraded tissues in the spine and the knee. MSKDamage aims to (1) develop a methodology to test interventions for a specific patient and its specific tissue degradation, (2) carry out a series of case studies which demonstrate the capacity to test a range tissues disorders and repairs. This work is a particularly suitable for a Fellowship, as it will allow me to develop fundamental engineering tools and methods while engaging with end users for significant economic and societal impact. I will also develop as a leader in the field, leading a growing research group and taking actions for the research community, directly related to the research, with advocacy on sharing more research outcomes openly for creation of more impact, and indirectly related to act as an ambassador for public and patient involvement for research related to computer simulations in healthcare.

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.

In our work in the current edition of the CMIH we have built up a strong pool of researchers and collaborations across the board from mathematics, statistics, to engineering, medical physics and clinicians. Our work has also confirmed that imaging data is a very important diagnostic biomarker, but also that non-imaging data in the form of health records, memory tests and genomics are precious predictive resources and that when combined in appropriate ways should be the source for AI-based healthcare of the future. Following this philosophy, the new CMIH brings together researchers from mathematics, statistics, computer science and medicine, with clinicians and relevant industrial stakeholder to develop rigorous and clinically practical algorithms for analysing healthcare data in an integrated fashion for personalised diagnosis and treatment, as well as target identification and validation on a population level. We will focus on three medical streams: Cancer, Cardiovascular disease and Dementia, which remain the top 3 causes of death and disability in the UK. Whilst applied mathematics and mathematical statistics are still commonly regarded as separate disciplines there is an increasing understanding that a combined approach, by removing historic disciplinary boundaries, is the only way forward. This is especially the case when addressing methodological challenges in data science using multi-modal data streams, such as the research we will undertake at the Hub. This holistic approach will support the Hub aims to bring AI for healthcare decision making to the clinical end users.

We will integrate structure characterization, molecular simulation and process modelling methods into a single computational toolbox and apply this toolbox to explore the scope and accuracy of multi-scale approaches in the assessment of performance of porous materials in adsorption and membrane separation processes. Separation processes consume about 10-15% of global energy, while high energy cost of carbon capture still presents a major hurdle in the implementation of this technology. Recent discovery of new families of porous materials opens unprecedented opportunities to advance energy efficient adsorption and membrane separations; however the large number of new materials demands a transition from traditional trial-and-error process design to rational selection of materials based on computational screening. In this project, we develop computational tools required for this transition, test them against bench scale experiments, and explore their robustness in screening materials for realistic process configurations. In the latter case, we use portable oxygen concentration technologies as a source of extensive reference data to test computational predictions. At the same time, we use this case as an opportunity to apply multi-scale approaches to explore further optimization of portable oxygen concentrators (POC) to make these medical devices even lighter with longer battery life.

Some of the most pressing global issues today are related to energy consumption, dissipation and waste. There is a great promise to address these issues by developing high-performance, cost-effective and eco-friendly materials for thermoelectric applications. Here we plan to use state-of-the-art theoretical ab initio modelling approaches and state-of-the-art materials synthesis and processing techniques to develop high-efficiency copper-antimony-sulphide based thermoelectric compounds. These ternary compounds have attracted great interest in recent years due to appealing structural, electronic and thermal transport properties. Indeed, Cu-Sb-S compounds display a rich structural variety (ranging from rock-salt to layered structures), a large range of band gaps and are characterised by extremely low thermal conductivities.These features combined with the non-toxicity and abundance of the constituent elements make the Cu-Sb-S system an ideal playground to optimise materials for sustainable thermoelectric devices. Despite the intense research activity on these systems, many fundamental questions remain open, including the origin of the anomalously low thermal conductivity, the role of electronic correlation related to the presence of Cu d electrons, and the effect of defects, dopants and stoichiometry on transport properties as well as on the structural stability and thermo-mechanics of these compounds. Realising the full potential of these systems and producing optimised materials for industrial evaluation requires a combined theoretical and experimental effort. For this we bring together teams from KCL and QMUL with complementary expertise, respectively, in modelling transport properties in complex compounds via advanced first-principles techniques, and in synthesis, processing and characterization of thermoelectric materials. This effort will be crucial to enhance the performance and the stability of these compounds: the experimental work will provide a test for the theoretical approach and the theoretical predictions will guide the synthesis of optimised compounds. Together with our industrial partners (European Thermodynamics, Johnson & Matthey, Kennametal) we will also explore the production process and characterization of Cu-Sb-S-based thermoelectric modules.