Healthcare Technologies Grand Challenges

These four grand challenges are a key part of the healthcare technologies theme strategy and provide a focus for funding opportunities offered by the theme.

Developing Future Therapies

Supporting the development of novel therapies with technologies to enhance efficacy, minimise costs and reduce risk to patients.

Through this challenge we aim to support the novel engineering, ICT, mathematical and physical sciences research required to develop the drug, biological, cell and regenerative therapies of 2050. Research supported by EPSRC will seek to enhance the efficacy and precision of therapies, improve the efficiency of discovery, lower the cost of manufacturing and reduce the risk to patients from side effects.

Some specific impacts that could be achieved under this challenge include:

  • In-silico, in-vitro, and biomarker technologies for drug discovery, allowing rapid prediction and measurement of therapeutic effect, toxicology and in-vivo drug-target interaction, to reduce development costs and minimise the use of animal models.
  • Advanced drug delivery technologies to administer novel therapeutic agents effectively, targeting specific sites, allowing co-delivery of multiple agents, or providing controlled release.
  • Flexible, adaptive manufacturing processes for high-quality medicines tailored to demand, allowing cost-effective scale-up for mass production (e.g. for epidemics) and scale-down for personalisation (e.g. regenerative therapies from a patient's own cells).
  • Innovative technologies for Regenerative Medicine allowing the creation of a functional organ in the lab to repair or replace damaged organs, without the need for organ donation.
  • Advanced technologies for clinical trials, using multiscale modelling, adaptive design, and data analytics to reduce the time to market for new therapies and identify opportunities for drug-repurposing, maximising cost-benefit.

Frontiers of Physical Intervention

Restoring function, and optimising surgery and other physical interventions to achieve high precision with minimal invasiveness.

Through this challenge we aim to support the novel engineering, ICT, mathematical and physical sciences research required to develop prostheses and devices to restore normal function, and develop precise, minimally invasive physical interventions to repair damage or remove disease. Interventions may include established techniques such as surgery, radiotherapy or high field ultrasound, but we also encourage new approaches to physical treatment.

Some specific impacts that could be achieved under this challenge include:

  • Autonomous or cooperative robotic surgery to reduce costs and recovery times, and improve outcomes by enabling minimally invasive intervention, improving accuracy and lowering infection rates.
  • Advances in physics modelling and image guided planning for surgery and radiotherapy to improve precision/targeting, leading to fewer side-effects, faster recovery, and better outcomes.
  • New affordable, targeting methods, including but not limited to nanoscale devices, for delivering non-ionising energy into patients to revolutionise treatments for cancer and other diseases, by improving efficacy and reducing side effects.
  • Bioelectronic devices that enable long term sensing and control, which could re-establish function, reduce pain, or aid recovery.
  • Disruptive technology for implants, prostheses and assistive devices, to restore function, adapt to changing needs and capabilities, improve success-rates and longevity (e.g. reducing the need for revision surgery), and encourage uptake.

Optimising Treatment

Optimising care through effective diagnosis, patient-specific prediction and evidence-based intervention.

Through this challenge we aim to support the novel engineering, ICT, mathematical and physical sciences research required to optimise treatment for the individual, improving health outcomes. Research supported by EPSRC will focus on technologies for timely and accurate diagnosis, stratification, predictive modelling, and real-time, evidence-based decision making. The aim is the right treatment at the right time.

Some specific impacts that could be achieved under this challenge include:

  • Novel, low-cost diagnostic devices, with high sensitivity, specificity and reliability, for timely and accurate diagnosis, improving the choice and reducing the cost of intervention, and increasing the likelihood of successful health outcomes.
  • Data analytic methods to identify disease phenotypes and associated responses to treatment from population data, allowing evidence-based selection of treatment options, with lower costs and morbidity, and improved health outcomes.
  • Novel non-invasive sensing platforms for the capture of real-time health and lifestyle data, enabling automated intervention - e.g. controlled release of a drug - providing better disease control and allowing patients to lead more normal, independent lives.
  • Patient-specific predictive models that integrate medical knowledge and knowledge of an individual - from medical records, imaging, physiological and behaviour monitoring, response to interventions, self-reporting etc. - for timely, accurate diagnosis and outcome prediction.
  • Systematic treatment of uncertainty in complex models and decision support systems, allowing more sophisticated decision-making, based on an understanding of confidence and sensitivity.

Transforming Community Health and Care

Using real-time information to support self-management of health and wellbeing, and to facilitate timely interventions.

Through this challenge we aim to support the novel engineering, ICT, mathematical and physical sciences research required to transform community-based health and care. Research supported by EPSRC will seek to integrate, interpret and communicate information from multiple sources, including real-time sensing, to help individuals stay healthy, and support a collaborative model of care involving patients, healthcare professionals and informal carers. This should empower individuals to self-manage effectively, and facilitate timely intervention when necessary.

Some specific impacts that could be achieved under this challenge include:

  • Methods for recognising person-specific abnormal patterns in physiological and behavioural time-course data, providing early warning of deterioration to patients, carers, and healthcare professionals.
  • Decision support dashboards and tools for healthcare professionals, supporting safe and effective management in the community of patients with long-term conditions or following early discharge.
  • An intelligent 'companion' that is fully aware of an individual's healthcare history and experience, empowering them to self-manage their health and care by providing directly relevant feedback, information and advice.
  • Individually adaptive data-collection, interaction with healthcare professionals, and self-reporting requests, to support effective care whilst minimising intrusion.
  • Technologies for promoting wellbeing by providing timely, personalised feedback, and exploiting social networking to influence health behaviours.