Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Medical devices impact every aspect of the public's interaction with the NHS, for prevention, screening, diagnosis, monitoring, and treating of diseases. The safety and effectiveness of these devices is critical to the quality of health outcomes. Traditionally, the great majority of medical device testing is done before they are used on patients ("pre-market"). Manufacturers are required to monitor their devices in clinical use ("post-market"), but in practice this is mainly limited to voluntary reporting and feedback from users. We refer to this ongoing information about medical devices in clinical use as "post-market intelligence." The way we approach this has barely changed in decades. However, recent technological innovations mean that post-market intelligence could be transformed. These innovations include: sophisticated medical device software, connected devices, innovative sensors, and growing hospital medical device databases---which are often managed by trained healthcare scientist staff. We believe that new opportunities can be created by connecting these new and enhanced sources of data about device safety and performance. There is an opportunity for post-market-intelligence to provide much earlier warnings about devices that are not operating as they should, are difficult to use, unreliable, or seem to function poorly in sub-groups of patients. This data could be used by hospitals to better manage their services to patients and have greater confidence in deploying innovative devices in their services. Manufacturers could use data to rapidly detect and address any identified issues with their devices (so called "field action"). Regulators could provide pathways that enable innovative devices to get to patients more quickly, by changing the balance of pre-market and post-market safety and performance evaluation. Our network of organisations will come together to explore this opportunity including how to incentivise adoption of this enhanced post-market vigilance by manufacturers and the NHS. Our network includes medical device manufacturers, companies and universities that specialise in developing standards and tools to connect organisations. It also includes NHS staff who might manage the data that we believe can unlock improvements to the way medical devices are developed, delivered and managed. Our network will also identify how to engage with patients to ensure their voices are heard, especially around how to ensure privacy of their data and trust in the technology and systems we plan to develop.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Liver transplantation is a successful treatment for patients with severe liver disease. Despite this, the majority of patients are maintained on immunosuppressants (drugs that dampen down the immune system) life long with associated side effects, affecting the quality of life of the patient and the long term outcome. The aims of this study are, therefore, to i. determine if a new cell based therapy is safe and well tolerated in liver transplantation patients and ii. if immunosuppressive drugs can be withdrawn early after transplantation (once the patient has had this new therapy). The general aim of this therapy is to allow the withdrawal of immunosuppressants in patients receiving a liver transplant, with the ultimate goal of complete withdrawal of immunosuppressants lifelong. Interestingly, populations of immune cells in the recipient, called regulatory T cells, have been shown to regulate the patient's immune system and prevent against organ rejection. Our research is targeting at developing new treatments that involve increasing the number of these cells in the recipient. We will a. isolate these cells from the recipient at the time of transplant, expand them numerically and ensure they are stable in culture and then inject them back into the patient at 3 months after transplantation. Patients will be closely monitored at King's College Hospital (expertese in hepatology and liver transplantation) with assessment of safety of the injected cells. The study's main focus is the assessment of safety of the cell based therapy and providing evidence which will support a larger study looking at the effectiveness of the therapy in the liver transplant recipients.

Developmental language disorder (DLD) and autism are two common neurodevelopmental conditions in which language acquisition is disrupted. Autism affects how children communicate and interact with the world. One in every 100 children has autism, and 70% of autistic children face lifelong language difficulties. DLD is a neurodevelopmental condition characterised by persistent difficulties with understanding and using language. Two children in every classroom are estimated to have DLD. Language difficulties have a severe impact on these children's life outcomes, limiting academic achievement, job prospects, and social and emotional well-being. One factor that could facilitate learning - or exacerbate impairments - is motivation. Children with these conditions often do not enjoy, or pursue, language-based tasks such as reading. This creates a vicious cycle: those who are not good at language disengage from language, and consequently, they struggle to get better at language. Yet, current cognitive models of these two conditions largely neglect the role of motivation. Understanding how to enhance language learning by improving motivation could help us achieve better outcomes from existing or novel interventions. In this project, I focus on the links between motivation and language learning, and their disruption in DLD and autism. Recent advances in methods, particularly in brain imaging and mathematical modelling, now allow us to understand motivation in far greater depth. We can ask which things people find intrinsically rewarding, and quantify how much effort they will exert to obtain them. Crucially, these studies reveal motivation can enhance learning. I plan to use these advanced approaches to study motivation for language learning in DLD and autism for the first time. I will examine if children with DLD and autism find language learning intrinsically rewarding, and if states of intrinsic motivation can be used to improve learning. I will also examine the role of external social and non-social rewards for language learning, assessing if conferred benefit differs in DLD and autism. Finally, I will develop a new task to quantify effort, and assess whether people with DLD or autism perceive language learning as less worthy of effort than neurotypical people. This work will help us understand what changes we might need to make to the learning environment to support language learning for these children. In other populations (e.g. ADHD, Parkinson's disease), differences in motivation have been linked to specific circuits in the brain. We propose to use similar imaging techniques to examine brain structure and function in the neural regions involved in language processing and motivation. This will help us understand which regions or networks might be disrupted in DLD and autism, and give us greater insight into the differences between groups (for instance, different regions may be disrupted in DLD and autism). Additionally, both children with DLD and those with autism who have language difficulties are understudied from a neuroscientific standpoint, so this work will also yield important information about language processing in these groups. In summary, reward and motivation play a crucial role in learning, across a variety of tasks and across species. Yet, their role in language learning is under-studied. Using state-of-the-art methods, I will study the interaction between language processing and reward and motivation systems in DLD, autism, and typical development. This will give us insight into motivation for language learning, shedding light on whether methods that are effective for neurotypical children hold in DLD and autism. Further, by understanding specific brain disruptions in these groups, we will be able to advance our knowledge of the biological differences underlying these two conditions. Ultimately, we can develop more targeted intervention to boost language learning, improving life outcomes in these groups.