On this page you will find details of all of the projects that we currently supporting on Cohort F of the Midlands ICURe programme 2020 / 2021
If you would like to make contact with any of the cohort or have any questions for them, please do contact us via email : firstname.lastname@example.org
or by phone: 07385 083391
More than 2 million Total joint replacement (TJR) were performed in the UK for the year 2018, having a cost of primary surgery of £6.36 billion per year. The complications (mainly joint loosening) associated to the TJR often leads to revision surgery. This puts an increase in amount of £1.43 billion per year along with an added cost of post-operative care and routine check-up of £106 million. Currently, the available diagnostic tools lack early loosening detection and they require regular visits of the patients to hospital and multiple x-rays, which expose them to radiation. We have developed a first of its kind technology that can detect early signs of the joint loosening without any radiographic exposure. In addition to that, this technology has the capability to monitor the joint performance remotely and will have the ability to power-up wirelessly. This technology will not only replace the current detection method that rely on x-ray exposure but its unique remote monitoring and powering will aid in easing the burden of the hospitals by potentially eliminating hospital visits along with providing of vital information to the healthcare professionals and, longer term, will help in improving TJR. With the first aim of developing a smart TJR product, this innovative technology will also be developed for other applications within the healthcare sector that require precise micro motion detection. Therefore, the second aim is to be a service provider for implant testing. The business opportunities to take this beyond healthcare include the potential in the future to use this technology in the oil and gas sector where there is no accessibility and remote powering along with precise measurements are required.
The initial research into high-fidelity virtual experiences was funded by the EPSRC PSi project [EPS12]. Subsequently a proof-of-concept virtual flavour device was built with support of a BBSRC Challenge Fund Agri-Food Technology Seeding Catalyst Award [BBS17], and a Warwick Impact Fund grant [WIF18]. Subsequent funding by a Royal Academy of Engineering grant [RAE19], with partners New Food-Innovation, the University of Cape Town and the rooibos tea producer, Carmién Tea in South Africa, enabled a Minimum Viable Product (MVP) to be built and a user study in South Africa undertaken, Figure 1, to clearly show that people were unable to tell the difference between a sample of a real rooibos tea blend and a virtual sample. In addition, it is also known that many medical conditions are accompanied by a change/loss in taste and/or smell [CA20]. Consequently, the virtual flavour research also underpins a study, funded by University of Warwick Heath GRP Priority Funding Award [GRP20], jointly being undertaken with the Universidad Peruana Cayetano Heredia and Hospital Cayetano Heredia (both Lima, Peru) to investigate the potential for a flavour-based test for COVID-19. This study will also provide feedback of the suitability of an FBT deployed at a home compared to at a dedicated test centre. The research opens up the possibility of producing new, virtual flavours that have high sensitivity for detecting specific medical conditions and to deliver these in a safe, controlled, and repeatable manner.
Extreme (working) environments often requires careful monitoring of personnel or patients. There are no suitable low-cost solutions that can accurately track a range of health-related signs during in-field operation. This is particular true for domains, such as (i) construction, (ii) military and (iii) contact-sports. There is a great need to have access to a customizable platform, which can support the monitoring of a range of different modalities for a range of different users. The OXHOME system developed in the Natural Interaction Lab (NIL) provides a scalable solution that offers a unique sensor platform that can operate under harsh environmental conditions. The system is created to work under extreme mechanical requirements and offers a platform that allows for customizable data collection through the integration of a range of sensor units. The device is supported by several patents and initial verification of in-house algorithms have taken place. The proposed goal is to demonstrate the integrated system in a pilot (TRL 7). Our ongoing engagement with key stakeholders across the domains will then allow us to further address specific needs within a sector. More importantly, it will provide a direct route to market and ensure there is appropriate market fit.
Bio to follow...
Microfabrication Industry needs: We are now moving from Moore’s law to “More than Moore”: i.e. combining multiple technologies such as sensors and processors on the same high-value microsystem for e.g: Internet-of-Things and biosensors. To facilitate the 3D-microfabrication of multiple technologies, new fabrication methods are required: How the Hy-MEMBS system addresses those needs: I am part of a team at Newcastle University that has developed a microscale 3D fabrication system which can process brittle materials, and thus high value microdevices with the following capabilities:
- 3D-micro-subtractive printing: Patterning at any angle for sensors and 3D system integration.
- 3D-micro-geometries: Conventional techniques can only produce rectangular products. Hy-MEMBS can create complex geometries such as microlenses.
- Jigsaw dicing: All semiconductor devices need to be “diced” from their wafer into smaller shapes. Currently that can only be rectangular. Hy-MEMBS in contrast, is able to dice complex features like a jigsaw.
Hy-MEMBS secondary attributes:
- Rapid prototyping: No specialist tooling is required, such as lithography masks (which can take 1-2 weeks).
- Versatile: The system can be utilised with a wide range of materials.
- Defect-free fabrication: Our approach is a hybrid-mechanical approach – which unlike conventional micro-mechanical approaches, can create a defect-free finish on brittle materials such as silicon.
- Low-cost: The system can be produced at low-cost – ~£30k. Depending on sales price mark¬up, it can therefore fit more easily into procurement budgets than £100k+ systems.
- Small-size: The technology has a low footprint and thus can be easily be situated in existing facilities.
Age-related macular degeneration (AMD) is a leading cause of vision loss in Europe and the US. Currently, 196 million people are estimated to be affected by AMD globally, a figure expected to hit 288 million by 2040. Some forms of AMD can be treated, using antibodies that block the activity of a molecule that causes the excessive growth of new blood vessels, known as vascular endothelial growth factor (VEGF). These antibodies are large proteins and are too large to pass into the eye if applied topically; thus they need to be injected into the eye. Monthly injections of these anti-VEGF antibodies for at least 5 years provides effective treatment for most patients. However, these injections have significant side effects, including retinal detachment, infection inside the eye, and raised intraocular pressure. We have developed a novel means of delivering drugs currently injected as eye drops instead. Our technology is a family of polyamine carriers that have shown the ability to deliver large antibodies used in treatment of AMD to the back of the eye when applied to the cornea in the form of eye drops. The polyamines we use are all naturally-occurring within the human body and are of low toxicity. Delivery as eye drops will address several issues with the current treatment regime. While injections must be administered by trained healthcare professionals in a clinical setting, eye drops can be administered by the patient themselves anywhere, resulting in large healthcare cost savings.
A Digital Twin is a `living’ computer model which imitates a physical system or asset. By using continuous real time data from sensors, the computer model improves its predictive capabilities over time through machine learning and AI. Engineering companies see the huge potential a digital twin can have in product development and long-term asset management. However, industry can find it difficult to understand the technology landscape and to develop the technical skills to transfer scientific methods into useable software for the company. There is a scarcity of robust, enterprise-wide data analytics capabilities, and highly specialised cross-disciplinary skills in applied mathematics, scientific computing and engineering. Our group is often approached by companies seeking to harness these capabilities for Digital Twins. We have developed and published new fundamental methods, at the cutting-edge of Digital Twin technology and uncertainty quantification, for the integration of data and complex simulations. The principle idea of these methods is to utilise different fidelities of computer models as a hierarchy. By combining this hierarchy of simulations and data, we achieve orders of magnitude computational speed-ups over existing methods. In one industry motivated problem in aerospace composites we reduced the computational time from 218 days (using existing approaches) to just 4.5 hours. This level of speed-up makes Digital Twins that would otherwise be unthinkable, now possible.
eGRiST is unique because it represents mental-health expertise using a psychological model of how practitioners naturally think and reason about risk. This makes it intuitive to use without requirement for specialist training. The model of mental health knowledge provides a formal specification of risk expertise that breaks each concept down into questions that are simple and quick to answer. We now have a database of more than one million risk evaluations, including suicide, self-harm, harm to others, self-neglect, and vulnerability. This links detailed information about a person to a trained mental-health practitioner's evaluation of risks from 0 (no raised risk) to 10 (maximum item). Machine learning algorithms applied to the data mean GRiST: - identifies people who are at risk; - knows what issues have raised the risk; - advises on how to reduce risks; - and automatically learns how all of these functions can be improved by linking outcomes to predictions and advice. The advantage of using a psychological model of expertise alongside these predictions is that GRiST can explain the reasons for the predictions in ways that are easy for human users to understand. There is no competitor that can link empirical evidence to clinicians’ own expertise like GRiST.
The technology consists of an innovative manufacturing and design process developed for fast production of high-performance lightweight 3D composite tubular or resilient complex structures for advanced applications in automotive, aerospace, energy and biomedical sector. The novel technology comprises the use of a proprietary fibrous reinforcement that can be accurately designed and fabricated into the tubular/rod form and sheathed to add stability. This allows flexibility and resilience properties of the designed product and allows the quick and reliable fabrication of complex 3D structures that are ordinarily extremely challenging and expensive using conventional composite manufacturing processes. The technology also addresses the current weaknesses of composite layers due to the lack of strength and stiffness in the through-the-thickness direction. As a consequence, under normal or impact loading, our composite technology does not suffer from extensive delaminations leading to catastrophic failures as in conventional composite materials. The 3D reinforcement technology can be used to manufacture elongated rod/spring structures or the springs/rods woven together to build up a resilient fabric-like or unidirectional reinforcement structure. The resultant 3-D dry reinforcement structure can be impregnated with resin to create a composite material which can potentially possess the same or similar strength and stiffness in-plane and out-of-plane direction for high-performance transport/energy and biomedical applications. Our initial results show a weight reduction of ~40% or more compared to traditional materials is possible, as well as an improvement in manufacturing cost and speed performance, fuel consumption, CO2 emissions, fatigue and corrosion resistance.
There are pressing issues with farm animal health and welfare including overuse of antibiotics and an upcoming EU ban on the use of zinc oxide for treatment of diarrhoea in piglets. We have identified, isolated, and filed for patent protection a novel plant polysaccharide with a specific structural motif which can trigger a specific type of immune response. The polysaccharide has a number of effects on cells consistent with activation of immune cells, and other factors in a key process called Th1-mediated immunity. For example, prior treatment of an animal with the polysaccharide reduces bacterial infection in an experimental model. Our secret isolation process generates a compound which is natural, cheap, orally available, non-toxic and does not trigger any allergic shock. The discovery is immediately applicable as a supplement for incorporation in animal feed or as a veterinary food which can improve animal disease resistance, reducing mortality. The ban on Zinc oxide (ZnO) use in pig feed EU wide from June 2022 means there will be no effective treatments available and effectively no competitor products. Of discovery is timely, will meet current regulatory requirements and provides a window of opportunity for commercial exploitation.
This is a platform technology with huge potential across all areas of drug discovery, high throughput screening, biologics and fundamental research.
Gene expression is central to life. It involves DNA (the blueprint of life), being converted to RNA, via transcription, and RNA being converted to protein (the building blocks of life), via translation. However, RNA is more than just an information transfer molecule; the control of gene expression at the RNA level is critical for normal cellular processes. Understanding and exploiting gene expression, and RNA control, is important for fields including biotechnology and therapeutics. We have successfully developed a novel technology which enables the high-throughput analysis and manipulation of the gene expression processes (transcription and translation). A key aspect is our ability to generate functional RNA arrays from user-defined DNA template arrays. These RNA arrays can then be used to generate protein arrays or used for bespoke RNA studies, such as exploring RNA-interactions. Despite RNA’s important role, the ability for its study in a high-throughput manner has previously been limited due to the inability to chemically synthesise large functional RNAs cost effectively and the lack of available techniques. Our unique approach overcomes these limitations and give us the exclusive capability of studying many different RNAs in parallel, as well as the associated transcription and translation processes of gene expression, via an easy, low cost, method. Coupled with our expertise in this space, we are in a unique position to use our technology as a ‘design house’ platform for the bespoke analysis and manipulation of RNA and gene expression for broad applications in biotechnology and therapeutics.