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Details of Grant 

EPSRC Reference: EP/V041789/1
Title: COVID-19: Patient-specific lung models to guide interventions prior to clinical application
Principal Investigator: Arora, Dr H
Other Investigators:
Van Loon, Dr R Johnston, Professor RE Nithiarasu, Professor P
Pant, Dr S
Researcher Co-Investigators:
Project Partners:
3D LifePrints
Department: College of Engineering
Organisation: Swansea University
Scheme: Standard Research
Starts: 01 November 2020 Ends: 30 April 2022 Value (£): 259,369
EPSRC Research Topic Classifications:
Biomechanics & Rehabilitation Med.Instrument.Device& Equip.
Medical science & disease
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:  
Summary on Grant Application Form
This project will deliver computational models of the lung, to support the development of

patient-specific treatment strategies for the COVID-19 pandemic. The models will i)

automate analysis of the damaged lung, providing additional quantitative data to support

more reliable and rapid conclusions about the presentation of the virus, ii) provide predictions

of how the lung will perform in response to different management strategies (supplemental

oxygen, mechanical ventilation, fluid balance) and potential future treatment strategies

outlined in the RECOVERY/REMAP-CAP trial (e.g. steroids, anti-inflammatories, antibiotics

and plasma from recovered patients); innovatively factoring specific parameters such as

weight, height, age, general fitness and ethnicity - which unquestionably have acute

relevance for recovery.

COVID-19 is heterogenous - affecting everyone differently. Therefore, rapid and

appropriate medical responses to individual cases are critical. Presently patients can remain

on ineffective treatment pathways for 4-6 hours before alternative treatment strategies are

employed. This project reduces waiting times, enabling prioritisation based on quantitative

tools. The models deliver heightened understanding of individual lung mechanics, enabling

clinicians to quickly make better informed treatment decisions to optimise COVID-19 survival

rates.

The model will use patient CT data, patient-specific calibration factors (age, sex, size) and

risk factors (comorbidities, clinical frailty score, exercise tolerance, APACHE-II, ethnicity),

state-of-the-art image analysis and computer simulation, in collaboration with 3DLifePrints

to build human lung models. Patient data will be accessed via ICNARC and the SAIL

databank. The model will mimic lung structure and mechanical function, accounting for the

effect of tissue damage and providing dynamic feedback of lung health.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
Sectors submitted by the Researcher
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Project URL:  
Further Information:  
Organisation Website: http://www.swan.ac.uk