Powered by OpenAIRE graph
Found an issue? Give us feedback

OPTO BIOSYSTEMS LTD

OPTO BIOSYSTEMS LTD

2 Projects, page 1 of 1
  • Funder: UK Research and Innovation Project Code: EP/Y035364/1
    Funder Contribution: 8,403,450 GBP

    Our EPSRC CDT in Advanced Engineering for Personalised Surgery & Intervention will train a new generation of researchers for diverse engineering careers that deliver patient and economic impact through innovation in surgery & intervention. We will achieve this through cohort training that implements the strategy of the EPSRC by working across sectors (academia, industry, and NHS) to stimulate innovations by generating and exchanging knowledge. Surgery is recognised as an "indivisible, indispensable part of health care" but the NHS struggles to meet its rising demand. More than 10m UK patients underwent a surgical procedure in 2021, with a further 5m patients still requiring treatment due to the COVID-19 backlog. This level of activity, encompassing procedures such as tumour resection, reconstructive surgery, orthopaedics, assisted fertilisation, thrombectomy, and cardiovascular interventions, accounts for a staggering 10% of the healthcare budget, yet it is not always curative. Unfortunately, one third of all country-wide deaths occur within 90 days of surgery. The Department of Health and Social Care urges for "innovation and new technology", echoing the NHS Long Term Plan on digital transformation and personalised care. Our proposed CDT will contribute to this mission and deliver mission-inspired training in the EPSRC's Research Priority "Transforming Health and Healthcare". In addition to patient impact, engineering innovation in surgery and intervention has substantial economic potential. The UK is a leader in the development of such technology and the 3rd biggest contributor to Europe's c.150bn euros MedTech market (2021). The market's growth rate is substantial, e.g., an 11.4% (2021 - 2026) compound annual growth rate is predicted just for the submarket of interventional robotics. The engineering scientists required to enhance the UK's societal, scientific, and economic capacity must be expert researchers with the skills to create innovative solutions to surgical challenges, by carrying out research, for example, on micro-surgical robots for tumour resection, AI-assisted surgical training, novel materials and theranostic agents for "surgery without the knife", and predictive computational models to develop patient-specific surgical procedures. Crucially, they should be comfortable and effective in crossing disciplines while being deeply engaged with surgical teams to co-create technology solutions. They should understand the pathway from bench-to-bedside and possess an entrepreneurial mindset to bring their innovations to the market. Such researchers are currently scarce, making their training a key contributor to the success of the UK Government's "Build Back Better - our plan for growth" and UKRI's "five-year strategy". The cross-discipline collaboration of King's School of Biomedical Engineering & Imaging Sciences (BMEIS, host), Department of Engineering, and King's Health Partners (KHP), our Academic Health Science Centre, will create an engineering focused CDT that embeds students within three acute NHS Trusts. Our CDT brings together 50+ world-class supervisors whose grant portfolio (c.£150m) underpins the full spectrum of the CDT's activity, i.e., Smart Instruments & Active Implants, Surgical Data Science, and Patient-specific Modelling & Simulation. We will offer MRes/PhD training pathway (1+3), and direct PhD training pathway (0+4). All students, regardless of pathway, will benefit from continuous education modules which cover aspects of clinical translation and entrepreneurship (with King's Entrepreneurship Institute), as well as core value modules to foster a positive research culture. Our graduates will acquire an entrepreneurial mindset with skills in data science, fundamental AI, computational modelling, and surgical instrumentation and implants. Career paths will range from creating next generation medical innovators within academia and/or industry to MedTech start-up entrepreneurs.

    more_vert
  • Funder: UK Research and Innovation Project Code: 10099579
    Funder Contribution: 346,422 GBP

    Opto is a UK-based medical device SME with a core project team of Dr Ben Woodington (CEO), Dr Elise Jenkins (Project Lead/CTO) and Jose Lepe (Product Lead). Electrical monitoring devices are crucial for managing neurological diseases such as brain cancer, epilepsy, and Parkinson's disease. These conditions affect around 105K people annually in the UK alone. Unfortunately, current technologies have made little headway with remote treatment, as they are invasive, uncomfortable and require hospital monitoring, which limits their use to short periods and restricts at-home use. This is problematic for two reasons. First, managing these diseases costs the NHS over £2B per year, and patients lose around £3B in productivity due to ongoing assessments. Secondly, infrequent, inconsistent 'snapshot' assessments of neurological health do not provide the full benefits of the technology, which could help guide treatment, inform disease progression and provide advance warning to patients. People who do not live near major hospitals with advanced facilities (~20 % of UK residents) and lower-income groups who lack the means to travel for treatment regularly are disproportionately affected by this. Opto has developed a minimally invasive, active medical technology platform that enables remote neurological monitoring of brain cancer patients to aid disease treatment and management. This innovation will improve the quality of life of patients suffering from neurological diseases, starting with brain cancer.

    more_vert

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

Content report
No reports available
Funder report
No option selected
arrow_drop_down

Do you wish to download a CSV file? Note that this process may take a while.

There was an error in csv downloading. Please try again later.