Traditional pharmaceutical drugs are small molecules that treat the symptoms of a disease. Biopharmaceuticals are larger molecules, for example, peptides and proteins, which target the underlying mechanisms and pathways of a disease that are not accessible with traditional drugs. Recently, there have been rapid and revolutionary developments in this field of biotechnology. Therapeutic peptides and proteins are expected to be used increasingly as vaccines and as treatments for cancer, high blood pressure, pain, blood clots and many other illnesses. However, one of the major challenges to successful clinical use of these so-called "biotech" molecules is their efficient delivery to the site of action. The body breaks these medicines down when they are swallowed and they are generally not well-absorbed into the blood. As a result, they have to be given frequently by injection, which is painful and means that these drugs are usually only administered in hospital. Long-acting formulations of small molecules, increasingly to the fore in treating HIV and TB, must also be injected. The COVID-19 pandemic has greatly increased the need for self-administration of injectables at home, away from healthcare settings, where transmission can have dire consequences. Complexities of storage, distribution and administration, needle phobia and the difficulty of domestic disposal of potentially-contaminated sharps all contribute to an urgent need for alternative delivery modes for injectable drugs/vaccines. Similarly, development of blood-free diagnostic systems is a major priority. We have developed a novel type of transdermal patch that by-passes the skin's barrier layer, which is called the stratum corneum. The patch surface has many tiny needles that pierce the stratum corneum without causing any pain - The sensation is said to feel like a cat's tongue. These needles either dissolve quickly, leaving tiny holes in the stratum corneum, through which medicines can enter the body, or swell, turning into a jelly-like material that keeps the holes open and allows continuous drug delivery. Our unique technology could potentially revolutionise the delivery of peptides and proteins, as well as that of long-acting small molecules that cannot currently be delivered across the skin. Notably, we have also found that our swellable microneedles can extract fluid from the skin. This permits us to monitor the levels of medicines and markers of disease without actually taking blood samples. In the UK, the NHS stands to benefit from reduced costs due to shorter hospital stays and reduced occurrence of inappropriate dosing. Ultimately, health-related-quality-of-life will be enhanced through improved disease control, rapid detection of disease and dangerously high or low levels of medicines, facile monitoring of compliance with prescribed dosing and detection of illicit substances in addicts or vehicle drivers. Preterm neonates will derive great benefit from the marked increase in monitoring frequency permitted, as will elderly patients being treated with multiple medicines. At-home treatment/diagnosis, keeping people away from healthcare settings, will also help reduce spread of COVID-19 to vulnerable in-patients and healthcare workers. We have attracted considerable interest and funding from industry to investigate our technologies for a range of applications. However, to facilitate the commercialisation process and maximise value to the UK, it is now essential to develop methods for rationalised skin application of the microneedles such that they are always applied to every patient in the same way every time and that their efficacy is guaranteed. We will also study, for the first time under industry-standard conditions, repeat application of our microneedles to mimic normal use and to demonstrate safety. Ultimately, commercialisation of the technology will be the primary route by which UK industry, the NHS and patients will derive benefits

Our vision is to bring the power of machine learning and computer vision (also known as 'Artificial Intelligence' or AI) to the application of Optical Coherence Tomography (OCT) imaging of skin, in order to dramatically improve the speed, accuracy and utility of these OCT imaging devices to dermatologists and clinical scientists. At present, end-user clinicians and scientists use OCT imaging devices to capture sub-surface images of skin and then they manually analyse the images to extract data, which is then used to assess the effects of pharmaceutical treatments on skin diseases. OCT imaging is faster, less invasive and less costly than taking skin biopsies, but the image analysis step is still time-consuming, somewhat subjective, and requires observer training. This is a hindrance to the use of OCT imaging to accelerate drug development for skin diseases like skin cancer, atopic dermatitis and psoriasis, which are multi-billion-$ markets. We believe that powerful machine learning algorithms will transform how OCT skin imaging is used by clinical scientists and clinical users to research and develop new drugs. To achieve this vision, we propose seconding a leading expert from AI specialists Manchester Imaging Ltd (MIL) to the host organisation Michelson Diagnostics Ltd, UK SME manufacturer of the world-leading VivoSight Optical Coherence Tomography (OCT) skin imaging and measurement system, over 2 years, to develop and test novel machine learning algorithms for OCT. Key barriers to the wider adoption of OCT for dermatology research is that the OCT images require trained experts to interpret them, and also that the image analysis is somewhat manual in nature. Dermatologists are often time-poor and may not have time to learn how to do this, and the manual nature of the analysis creates potential for unwanted bias. Therefore the challenge is to reduce the barriers to adoption by: Automatically identifying image-markers for common skin diseases Automatically quantifying the image-markers Examples of OCT image-markers requested by Michelson's user base are: Thickened epidermis (Atopic Dermatitis) Loss of definition of dermis-epidermis junction (skin cancer) Detection of tumour 'nests' in the dermis and their invasion-depth/extent (skin cancer) Increase in blood vessel density (all inflammatory diseases) Alterations in blood vessel shape/tortuosity (melanoma) The challenge can only be met by bringing together expertise in AI-algorithms (image processing/machine learning) and OCT imaging technology (laser physics, optics and instrumentation) with close links to the end-user clinical science user base, to form a highly focused and motivated multi-disciplinary team and who will develop and test candidate algorithms on real clinical data.

The sensing, processing and transport of information is at the heart of modern life, as can be seen from the ubiquity of smart-phone usage on any street. From our interactions with the people who design, build and use the systems that make this possible, we have created a programme to make possible the first data interconnects, switches and sensors that use lasers monolithically integrated on silicon, offering the potential to transform Information and Communication Technology (ICT) by changing fundamentally the way in which data is sensed, transferred between and processed on silicon chips. The work builds on our demonstration of the first successful telecommunications wavelength lasers directly integrated on silicon substrates. The QUDOS Programme will enable the monolithic integration of all required optical functions on silicon and will have a similar transformative effect on ICT to that which the creation of silicon integrated electronic circuits had on electronics. This will come about through removing the need to assemble individual components, enabling vastly increased scale and functionality at greatly reduced cost.