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Details of Grant 

EPSRC Reference: EP/X039056/1
Title: InTarget: An intelligent signature for magnetic control
Principal Investigator: Kafash Hoshiar, Dr A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Comosol DGIST King's College Hospital NHS Foundn Trust
Magnebotix UCL University of Leeds
Department: Computer Sci and Electronic Engineering
Organisation: University of Essex
Scheme: New Investigator Award
Starts: 20 May 2024 Ends: 19 August 2026 Value (£): 313,589
EPSRC Research Topic Classifications:
Control Engineering Drug Formulation & Delivery
Particle Technology Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
05 Sep 2023 Engineering Prioritisation Panel Meeting 5 6 7 September 2023 Announced
Summary on Grant Application Form
Cancer will claim 27.5 million lives worldwide annually by 2040 (cancerresearchuk.org). Current cancer treatment options include surgical intervention, chemotherapy, radiation therapy or a combination of these options. With Da Vinci surgical robots, which, amount other things, are used for minimally invasive tumour removal (6000 units in clinical use worldwide, wchh.onlinelibrary.wiley.com), robotics-assisted interventions have reached a maturity level to play an instrumental role in the fight against cancer.

The current trend in medical robotics is toward device miniaturization. This is achieved by wireless transmission of power. Last few years, miniaturized robots (micro/nanoscale) performed endovascular interventions like drug delivery (e. g. microswarms with 200-micrometre lengths). Although magnetic actuation is one of the favoured wireless power transmission methods, the magnetic field affects all microrobots simultaneously. As the microrobots receive the same actuation input, individual or collective steering is challenging.

In many applications, including targeted drug/stem cell delivery for cancer treatment, we need to steer a microswarm - that is, a collection of drug carriers (e.g., drug-coated magnetic nanoparticles (MNPs)). A magnetic field affecting all magnetic particles in the microswarm simultaneously makes precise capturing and steering of the microrobots challenging.

We will develop a robotics architecture to control the magnetic field in multi-domains (controlling fields in different areas) within a region of interest using an intelligent magnetic field (designed based on a data-driven approach). Therefore, the microrobots can be controlled individually, which makes collective control possible. We will also demonstrate the adaptation of this technology to microswarm capturing applications (InTarget). Capturing microswarm can lead to deep region targeting within the body (e.g. targeting inoperable brain tumours).

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