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Details of Grant 

EPSRC Reference: EP/W00433X/1
Title: A Soft Endorobot (SoftEn) for autonomous colonoscopy screening and treatment
Principal Investigator: Manfredi, Dr L
Other Investigators:
Trucco, Professor E Magerand, Dr L Mowat, Dr C
Dolwani, Dr S
Researcher Co-Investigators:
Project Partners:
NHS
Department: Imaging Science and Technology
Organisation: University of Dundee
Scheme: Standard Research
Starts: 01 October 2021 Ends: 31 December 2022 Value (£): 302,874
EPSRC Research Topic Classifications:
Artificial Intelligence Med.Instrument.Device& Equip.
Medical Imaging Medical science & disease
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Jul 2021 Transformative Healthcare Technologies Full Proposals 2nd Call Announced
Summary on Grant Application Form
Colorectal cancer (CRC) is the third cause of cancer death worldwide. In 2018, about 1.8 million new cases were reported worldwide with a mortality of almost 900,000. This has increased more than 30% since 2012. Studies have shown that regular screening and early detection can reduce mortality by up to 70%.

The proposed project will undertake interdisciplinary research to design a low-cost, disposable, autonomous Soft Endorobot (SoftEn) to examine the lower intestine painlessly. SoftEn offers disruptive potential to replace the current optical colonoscopy (OC), including a dual capability of investigation and performance of autonomous surgical tasks. SoftEn will overcome OC's limitations (operator-dependent, patient pain/discomfort, high costs, decontamination). Crucially, the high level of autonomy will reduce the time in performing the procedure as well as shift screening process from secondary to intermediate or primary care, thus saving precious time for diagnosis and intervention.

Advantages of this approach are:

1. Efficiency of the procedure will be augmented by reducing the human-operator skills required to perform the procedure. This will increase the number of procedures performed every year.

2. Reducing the waiting list will consequently improve the CRC stage of detection and will increase the patient survivability due to early intervention and reduced cost of treatment.

3. Less pain and discomfort will increase the patient acceptability of the screening as well as patient experience. This has the potential to make sedation unnecessary, which in turn would make hospital visits shorter.

4. Autonomous robot examination of the large intestine would remove restrictions of the traditional operator-dependent OC and would enable an increased access to investigation. Optical diagnosis and tissue diagnosis could be achieved in most of the procedures, including patients requiring more advanced intervention.

5. Potentially improve screening uptake through reducing barriers to participation.

6. The use of polymers implies a reduction in production costs, allowing the device to be single-use and avoiding additional costs required for a traditional OC, including sterilisation and reprocessing. This will reduce the UK cost in CRC procedures.

7. AI software will allow the endorobot to perform procedures autonomously. A clinician can therefore supervise several devices and intervene only if needed via an external ergonomic control console, locally or remotely. This will limit the use of clinicians' time and increase the number of investigations performed per day. Additionally, more clinicians will be able to perform the procedure supporting the national endoscopy workflow.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.dundee.ac.uk