Our expertise in pathology is included in two major Innovate UK projects in artificial intelligence for cancer diagnosis: PathLAKE and Northern Pathology Imaging Collaborative (NPIC)
PathLAKE - diagsnosis to reduce chemotherapy treatment
A simple test to improve treatment for breast cancer patients invented by scientists in Nottingham could soon benefit people across the UK, as part of this £14 million national initiative.
By detecting which patients can be successfully treated without chemotherapy, around half of the 55,000 people diagnosed annually in the UK will be able to avoid its debilitating effects.
Read further details in the press release
Experts: Professor Emad Rakha, Professor Ian Ellis, Dr Andrew Green
Northern Pathology Imaging Collaborative (NPIC)
NPIC is a £10m collaboration between academia, industry and the NHS, deploying digital pathology in hospitals across the North of England, for over 3 million patients.
The digital pathology images gathered for training AI systems will generate about 760,000 images per year, about 1.2 Petabytes of data.
Clinicians will then work with industry and academic researchers to make new AI systems capable of analysing digital pathology images leading to better diagnoses for diseases like cancer.
Further details on the project website
Optimising NHS breast screening
Nottingham University Hospitals NHS Trust is leading the Innovate UK testbed project "Capacity, Confidence, Care - Using Artificial Intelligence and Machine Learning to support Breast Screening" with the East Midlands Radiology ( EMRAD) consortium.
The diagnosis of cancer and other diseases often uses imaging tests (CT, MRI, x-ray, ultrasound) as part of the pathway of investigation. In the NHS, the number of imaging tests which need to be performed, outstrips the ability of the healthcare services to provide and/or interpret these tests. This can lead to delays in diagnosis and delays to subsequent treatment
The consortium, who have developed an image sharing platform, are developing an AI tool for breast cancer screening.
Further details on the Gateway to Research website
More about EMRAD and artificial intelligence
Accurate prescribing to reduce errors
General Practitioiners in every surgery in England will now be better equipped to reduce the human and societal cost of prescription errors, thanks to our new pharmacist-led PINCER tool.
Some 340 million GP consultations are held in England every year and one billion medications dispensed. Even with the most rigorous practices and highly trained practitioners there is clear potential for errors in any system that’s so busy and dealing with the complex challenge of prescribing effectively and safely for individual needs.
In fact, one in 25 hospital admissions in England are linked to prescription errors, a preventable cost to the NHS of more than £650m a year.
Now, thanks to an online tool created at the University of Nottingham, GPs in every surgery in England will be better equipped to reduce the human and societal cost of prescription errors. Known as PINCER, this pharmacist-led IT-based intervention tool – created to reduce clinically important medication errors – was developed by pharmacists and primary care researchers and colleagues in PRIMIS; a business unit within the School of Medicine with expertise in extracting knowledge and value from primary care data.
PINCER searches GP computer systems to identify patients who are potentially at risk from hazardous prescribing using a set of safety indicators. The doctors are alerted and work with pharmacists to head off this potential prescription error. GPs are familiar with other ‘pop-up’ alerts and sometimes inclined to ignore them – what makes PINCER more effective is bringing together doctors and practice-dedicated pharmacists to support a coordinated action plan for each patient.
Find out more about PINCER
Identifying next generation medicines
A new partnership between the Universities of Nottingham and Strathclyde and pharmaceutical company GSK will accelerate research into the discovery of new medicines, using AI and machine-learning technologies for the efficient identification of next generation medicines.
The five-year ESPRC funded programme will see the partners deliver a new suite of methods and approaches to tackle some of the major challenges in the discovery, development, and manufacture of medicines. The total project funding is £12.9 million, including a £5.5 million grant award from the EPSRC.
The research programme aims to enable the production of transformative medicines at lower costs with reduced waste production and shorter time for manufacture.
Researchers will apply cutting edge Artificial Intelligence and machine-learning technologies to the efficient identification of next generation medicines.
Read more in the press release - July 2019
We have developed and tested a system of computer-based machine learning algorithms to predict the risk of early death due to chronic disease in a large middle-aged population. This will allow personalised preventative medicine and risk management for patients.
Read more in the press release
Experts: Dr Stephen Weng, Professor Joe Kai