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Future Solutions In Progress

Round 8: Theme menu with 5 topics / areas of special interests

  • Clinical applications of genetics
  • Early detection and diagnosis of chronic illness or long term conditions
  • Minimising the impact of trauma and serious injury
  • Informing clinical management through software-based analysis of complex datasets
  • Repurposing of medicines and medical devices

Round 8 Projects:


Real-time Adaptive & Predictive Indicator of Deterioration (RAPID)
Real-time Adaptive & Predictive Indicator of Deterioration (RAPID)
Principal Investigator:  Dr Heather Duncan
Organisation: Birmingham Children's Hospital NHS Foundation Trust
Start Date 3rd November 2014
End Date: 2nd November 2017

View Abstract

Of the 1.5 million children admitted to UK hospitals every year; 650 suffer cardiac arrests and 3000 die. Most have signs that indicate deterioration before the life-threatening event. Current early warning scores have reduced avoidable life-threatening illness and death, but these systems need to be improved.

Deterioration can be missed when vital signs change rapidly, observations are made infrequently and slowly deteriorating trends can occur between alarm thresholds. A team led by Dr Heather Duncan of Birmingham Children's Hospital NHS Foundation Trust proposes a system where continuous observations are taken from patients and this data is used to understand, in real-time, what is normal for each patient and detect the changing patterns in their physiology. Small chest and hand sensors wirelessly connect patients in the wards. Continuous monitoring allows deterioration to be recognised, triggering an alert and provoking timely intervention to prevent patients suffering further deterioration and death.

The technology uses software adapted from Formula 1, with Aston University and Birmingham Children’s Hospital algorithms to interface seamlessly with NHS IT systems. The key goals are to deploy RAPID in two cardiac wards, demonstrate reliable collection and processing of data, provide clinical interpretation of processed data and create new patient pathways for better and more effective utilisation of nursing and doctors.

Real-time Adaptive & Predictive Indicator of Deterioration (RAPID)
Repurposing anti-TNF for treating Dupuytren’s disease
Principal Investigator:  Professor Jagdeep Nanchahal
Organisation: University of Oxford
Start Date 1st March 2015
End Date: 30th June 2018

View Abstract

Dupuytren’s disease is a very common condition, affecting 4% of the general UK population. It causes the fingers to curl into the palm and can be extremely disabling. There is no approved treatment for early disease. There is no approved treatment for early disease. Once patients have established deformities, the diseased tissue is removed surgically or cut using less invasive techniques such as a needle or an enzyme

However, recovery following surgery usually takes several months and recurrence rates with the non-surgical techniques are high. A team from the University of Oxford led by Professor Nanchahal has unravelled the molecular mechanisms that initiate and maintain the disease process.

Based on these findings they plan to test a new treatment with anti-TNF, a drug currently approved for use in patients with rheumatoid arthritis. If effective, this will represent the first targeted therapy involving a simple injection for patients with early Dupuytren’s disease that will preserve hand function and avoid the need for subsequent more invasive treatments such as surgery.