Osteoarthritis affects over eight million people in the UK alone, with nearly three quarters of patients reporting some form of constant pain. Treatment for arthritis is estimated to cost the UK healthcare system over £10 billion per year, with significant additional societal costs for lost working hours and welfare payments. Although hip and knee replacement surgeries are considered successful, these treatments are not suitable for all patients and some devices fail early, requiring costly and less successful revision surgery. There are over 15,000 revision surgeries performed in the UK alone each year. Younger and more active patients, as well as rising numbers with obesity, are placing greater demands on these treatments: implants need to last for longer and withstand more extreme loading than ever before. There is evidence that both individual patient biomechanics and surgical choices influence the outcomes of these treatments. Improved outcomes, particularly for more challenging patient groups, can only be achieved by better matching the treatment to the functional requirements of the individual patient. This proposal will bring together complementary research expertise from two of the world's leading research institutes in the field to build the evidence needed to enable treatments for osteoarthritis to be better tailored to individual patient needs. The Institute of Medical and Biological Engineering at the University of Leeds has developed unique capability and expertise to evaluate artificial and natural joints. These include the world's largest academic facility for experimentally testing joint replacements, as well as computational modelling methods to simulate how implants perform in the body. These capabilities enable the mechanical performance of implants to be evaluated under a range of different conditions, for example to study how the implant wears over time or becomes damaged with usage. The Center for Orthopaedic Biomechanics at the University of Denver has developed world-leading capability in measuring patient joint mechanics in vivo, including methods of imaging patient joints as they undertake different activities, and parallel computational methods for deriving biomechanical information. These methods enable the forces and motions on an individual patient's hip or knee joints to be derived and, by collecting data on many patients, examine how these differ from one individual to another. By combining the expertise across both groups, this Centre-to-Centre Research Collaboration will enable relationships to be developed between an individual patient's characteristics (e.g. their anatomy and how they load their joints) and the mechanical performance of the implant. Specifically, in the hip we will combine methodologies developed at the two centres to evaluate how patient and surgical factors affect the risk of early failure in hip replacements due to the device components pushing into each other or the surrounding bone (impingement), or the way the components are aligned. We will also examine how different choices of implant can influence the outcomes. In the knee, we will combine methodologies to identify how patient factors (such as the anatomy of the knee and the way it is loaded during different activities) affect early-stage treatments for knee osteoarthritis. We will also examine the effects of a greater range of activities, such as squatting and stair climbing, on the outcomes of knee replacements. These studies will bring together different methodologies and build new pathways for acquiring and sharing data that can be adopted more widely and applied to other musculoskeletal systems in the future. The work will build the evidence needed to improve hip and knee implant design, inform clinical decision-making, enhance patient quality of life and reduce early complications.

Over 80 million patients worldwide suffer from hip osteoarthritis, and increasing numbers of patients are requiring total hip replacement surgery. This is considered to be a successful intervention, however, an ageing population with increasing orthopaedic treatment needs, greater levels of obesity and patient expectations, and reducing healthcare budgets and surgical training are conspiring to challenge this success. There is also increasing demand for surgical treatments in younger patients that will delay the need for hip replacement surgery, these interventions reshape bone and repair soft tissue. One of the major causes of failure in the natural hip and in hip replacements is impingement, where there is a mechanical abutment between bone on the femoral side and hip socket or hip replacement components. In the natural hip, surgery reshaping the bone can reduce this impingement and soft tissue damage can be repaired; however, the effects of the amount of bone that is removed is not well understood nor is the best way to repair soft tissue. The number of hip replacements needing to be removed from patients and replaced with a new one in revision surgery is increasing; damage to the cup rim because of impingement is often implicated. It is known that this is more likely if the components are not well aligned relative to each another, or relative to the load direction experienced in the body. In this proposal, I seek to ensure long term outcomes of early intervention and hip replacement surgery are always optimum by negating concerns about impingement. To do this, I will develop an experimental anatomical hip simulator. The simulator will apply loads and motions to the hip similar to those observed clinically, and include high fidelity phantoms that mimic the natural hip, into which hip replacement components can also be implanted. This anatomical simulator will be used to assess how variables such as those associated with the patient (e.g. their bony geometry), the extent of early intervention surgery (e.g. the amount of bone removed) or the design of the prosthesis and how the hip is aligned in the body will affect the likelihood of impingement. This improved understanding of factors affecting the likelihood and severity of impingement will enable better guidance on how the surgery should be performed to optimise outcomes to be provided. I will work with orthopaedic surgeons to integrate this improved understanding into their clinical practice and with an orthopaedic company to integrate the findings into new product development processes; so that future interventions and devices can be designed to provide better outcomes for all patients.

Our vision is that patients with knee pain receive the right treatment at the right time. In the UK, one third of people aged over 45 have sought treatment for osteoarthritis, and the disease costs the NHS over £5 billion per year. The knee is the most common site for osteoarthritis, with over four million sufferers in England alone. The aging population with expectations of more active lifestyles, coupled with the increasing demand for treatment of younger and more active patients, are challenging the current therapies for knee joint degeneration. There is a major need for effective earlier stage interventions that delay or prevent the requirement for total knee replacement surgery. There are large variations in patients' knees and the way that they function, and it is important that this variation is taken into account when treatments are developed, so that the right treatment can be matched to the right patient. Through this ambitious programme of research we will develop novel testing methods that combine laboratory-based simulation and computer modelling to predict the mechanical performance of new therapies for the knee and enable their design and usage to be optimised. Importantly these tests will take into account the variation in patients' anatomy and knee biomechanics, as well as variations in device design and surgical technique. This will enable different therapies, or different variants of a device, to be matched to different patient groups. The tools will be applied to existing treatments using clinical data to help validate that our model predictions are correct. The outcomes will better define which patients will benefit from a particular intervention and help optimise their usage. We will then apply the methods to new and emerging treatments, including regenerative devices, so that they can be tested and optimised before costly clinical trials take place. We will use these examples as case studies to demonstrate how the new testing methods can optimise the products before they reach the patient, and we will work with industry, standards agencies and regulators to promote the adoption of these methods across the sector. This programme will benefit patients, the NHS and the growing UK industry and science base that are developing new therapies for the knee.

The vision of the Hub is to create ground-breaking embedded metrology and universal metrology informatics systems to be applied across the manufacturing value chain. This encompasses a paradigm shift in measurement technologies, embedded sensors/instrumentation and metrology solutions. A unified approach to creating new, scientifically-validated measurement technologies in manufacturing will lead to critical underpinning solutions to stimulate significant growth in the UK's productivity and facilitate future factories. Global manufacturing is evolving through disruptive technologies towards a goal of autonomous production, with manufacturing value-chains increasingly digitised. Future factories must be faster, more responsive and closer to customers as manufacturing is driven towards mass customisation of lower-cost products on demand. Metrology is crucial in underpinning quality, productivity and efficiency gains under these new manufacturing paradigms. The Advanced Metrology Hub brings together a multi-disciplinary team from Huddersfield with spokes at Loughborough, Bath and Sheffield universities, with fundamental support from NPL. Expertise in Engineering, Mathematics, Physics and Computer Science will address the grand challenges in advanced metrology and the Hub's vision through two key research themes and parallel platform activities: Theme I - Embedded Metrology will build sound technological foundations by bridging four formidable gaps in process- and component-embedded metrology. This covers: physical limits on the depth of field; high dynamic range measurement; real-time dynamic data acquisition in optical sensor/instruments; and robust, adaptive, scalable models for real-time control systems using sensor networks with different physical properties under time-discontinuous conditions. Theme II - Metrology Data analytics will create a smart knowledge system to unify metrology language, understanding, and usage between design, production and verification for geometrical products manufacturing; Establishment of data analytics systems to extract maximal information from measurement data going beyond state-of-the-art for optimisation of the manufacturing process to include system validation and product monitoring. Platform research activities will underpin the Hub's vision and core research programmes, stimulate new areas of research and support the progression of fundamental and early-stage research towards deployment and impact activities over the Hub's lifetime. In the early stage of the Hub, the core research programme will focus on four categories (Next generation of surface metrology; Metrology technologies and applications; In-process metrology and Machine-tool and large volume metrology) to meet UK industry's strategic agenda and facilitate their new products. The resulting pervasive embedding and integration of manufacturing metrology by the Hub will have far reaching implications for UK manufacturing as maximum improvements in product quality, minimization of waste/rework, and minimum lead-times will ultimately deliver direct productivity benefits and improved competitiveness. These benefits will be achieved by significantly reducing (by 50% to 75%) verification cost across a wide swathe of manufacture sectors (e.g. aerospace, automotive, electronics, energy, medical devices, optics, precision engineering) where the current cost of verification is high (up to 20% of total costs) and where product quality and performance is critical.