UoEdinburgh Confidence in Concept 2013
Lead Research Organisation:
University of Edinburgh
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
The Confidence in Concept scheme is a key part of MRC’s translational research strategy and provides annual awards to institutions, to be used flexibly to support the earliest stages of multiple translational research projects. The award can be used by the institution to support a number of preliminary-stage translational projects. The projects supported should aim to provide sufficient preliminary data to establish the viability of an approach –– before seeking more substantive funding. It is intended to accelerate the transition from discovery research to translational development projects by supporting preliminary work or feasibility studies to establish the viability of an approach.
Organisations
- University of Edinburgh (Lead Research Organisation)
- Blackford Analysis Ltd (Collaboration)
- Charité - University of Medicine Berlin (Collaboration)
- University College London (Collaboration)
- Koninklijke Philips Electronics N.V. (Collaboration)
- The Mentholatum Company Ltd (Collaboration)
- PHARMATICS LIMITED (Collaboration)
- Linde Group (Collaboration)
- Meteorological Office UK (Collaboration)
- My Diabetes My Way (Collaboration)
- Farr Institute of Health Informatics Research (Collaboration)
- Medtronic (Collaboration)
- Oncomark Ltd (Collaboration)
- Johnson & Johnson (Collaboration)
- GlaxoSmithKline (GSK) (Collaboration)
- MYSPHERA (Collaboration)
- Philips Research (Collaboration)
- ARIDHIA INFORMATICS LIMITED (Collaboration)
- MQ Mental Health Research (Collaboration)
People |
ORCID iD |
Publications
Barnhill E
(2017)
Nonlinear multiscale regularisation in MR elastography: Towards fine feature mapping.
in Medical image analysis
Berrout J
(2017)
TRPA1-FGFR2 binding event is a regulatory oncogenic driver modulated by miRNA-142-3p
in Nature Communications
Hiscox LV
(2016)
Magnetic resonance elastography (MRE) of the human brain: technique, findings and clinical applications.
in Physics in medicine and biology
Hiscox LV
(2018)
High-resolution magnetic resonance elastography reveals differences in subcortical gray matter viscoelasticity between young and healthy older adults.
in Neurobiology of aging
Hiscox LV
(2020)
Hippocampal viscoelasticity and episodic memory performance in healthy older adults examined with magnetic resonance elastography.
in Brain imaging and behavior
Kennedy P
(2017)
MR elastography measurement of the effect of passive warmup prior to eccentric exercise on thigh muscle mechanical properties.
in Journal of magnetic resonance imaging : JMRI
Lee RJ
(2020)
Brain microenvironment-driven resistance to immune and targeted therapies in acral melanoma.
in ESMO open
MacLeod K
(2020)
Predicting Response to Radiotherapy in Cancer-Induced Bone Pain: Cytokines as a Potential Biomarker?
in Clinical oncology (Royal College of Radiologists (Great Britain))
Macleod KG
(2017)
Reverse Phase Protein Arrays and Drug Discovery.
in Methods in molecular biology (Clifton, N.J.)
Orchard P
(2018)
Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.
in Journal of medical Internet research
Pawlak M
(2017)
Reverse Phase Protein Arrays elucidate mechanisms-of-action and phenotypic response in 2D and 3D models.
in Drug discovery today. Technologies
Punovuori K
(2019)
N-cadherin stabilises neural identity by dampening anti-neural signals.
in Development (Cambridge, England)
Sriskandarajah P
(2020)
Combined targeting of MEK and the glucocorticoid receptor for the treatment of RAS-mutant multiple myeloma.
in BMC cancer
Thomas-Seale LEJ
(2016)
The simulation of magnetic resonance elastography through atherosclerosis.
in Journal of biomechanics
| Description | Safe Haven at EPCC - LungSolve |
| Geographic Reach | Local/Municipal/Regional |
| Policy Influence Type | Influenced training of practitioners or researchers |
| Impact | The development of the safe haven within EPCC has allowed the security procedures for the uploading of data/images and the access process to be influenced and developed. Influencing NSS policy for accessing and the use of safe havens. |
| Description | AI for Self management of chronic illness |
| Amount | £349,381 (GBP) |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | Breast Cancer Now - Sample Predictor CiC2 |
| Amount | £200,000 (GBP) |
| Organisation | Breast Cancer Now |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | Breast Cancer Research Trust - Sample Predictor CiC2 |
| Amount | £100,000 (GBP) |
| Organisation | Breast Cancer Research Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | CRUK PhD Sample Predictor CiC2 |
| Amount | £56,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | Company contribution Pharmatics - Learning to Care CiC 2 |
| Amount | £85,000 (GBP) |
| Organisation | Pharmatics Limited |
| Sector | Private |
| Country | United Kingdom |
| Start | |
| Description | EPSCRC funding (LungSolve CIC2) |
| Amount | £80,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | European Institutes of Innovation and Technology Grant - Learning to Care CiC 2 |
| Amount | € 140,000 (EUR) |
| Organisation | European Institute of Innovation and Technology (EIT) |
| Sector | Public |
| Country | Hungary |
| Start | 01/2018 |
| End | 12/2018 |
| Description | Fee for Service (Proteomic Platform) |
| Amount | £6,600 (GBP) |
| Organisation | AstraZeneca |
| Sector | Private |
| Country | United Kingdom |
| Start | 03/2018 |
| End | 03/2018 |
| Description | Fee for Service (Proteomic Platform) |
| Amount | £12,800 (GBP) |
| Organisation | Almac Group |
| Sector | Private |
| Country | United Kingdom |
| Start | 09/2017 |
| End | 09/2017 |
| Description | Fee for Service (Proteomic Platform) |
| Amount | £12,800 (GBP) |
| Organisation | Almac Group |
| Sector | Private |
| Country | United Kingdom |
| Start | 06/2018 |
| End | 06/2018 |
| Description | Further funding from MRC CiC (4) - PreMDD CiC2 |
| Amount | £49,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 07/2016 |
| End | 01/2017 |
| Description | Industry funding Pharmatic - Learning to Care CiC 2 |
| Amount | £120,000 (GBP) |
| Organisation | Pharmatics Limited |
| Sector | Private |
| Country | United Kingdom |
| Start | |
| Description | Innovate UK - Learning to Care CiC2 |
| Amount | £36,000 (GBP) |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRC PhD - Transformation of the utility of secondary data in NHS Scotland by forging the missing linkage to imaging data CIC2 |
| Amount | £108,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRC Precision Medicine DTP stipend (Sims) |
| Amount | £89,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRC Precision Medicine Lung Solve CIC2 |
| Amount | £60,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRC Precision Medicine PhD - Sample Predictor CiC2 |
| Amount | £80,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRC/EPSRC Infrastructure support - Transformation of the utility of secondary data in NHS Scotland by forging the missing linkage to imaging data CIC2 |
| Amount | £20,000,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | MRE CiC2 |
| Amount | £131,000 (GBP) |
| Organisation | Siemens Healthcare |
| Sector | Private |
| Country | Germany |
| Start | |
| Description | PDRA - Lung Solve CiC2 |
| Amount | £80,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | PhD bursary - Sample Predictor CiC2 |
| Amount | £10,000 (GBP) |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | |
| Description | PhD stipend (Sims) |
| Amount | £169,200 (GBP) |
| Organisation | Government of Turkey |
| Sector | Public |
| Country | Turkey |
| Start | |
| Description | Sample predictor CiC2 |
| Amount | £108,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | Sample predictor CiC2 |
| Amount | £108,000 (GBP) |
| Organisation | Government of Saudi Arabia |
| Sector | Public |
| Country | Saudi Arabia |
| Start | |
| Description | Systems approach to Therapeutic Combinations for Glioblastoma: New targets and agents delivered and sequenced for synergy (Carragher) |
| Amount | £6,200,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 01/2020 |
| End | 01/2025 |
| Description | The Mentholatum Company - MRE CIC2 |
| Amount | £324,000 (GBP) |
| Organisation | The Mentholatum Company Ltd |
| Sector | Private |
| Country | United Kingdom |
| Start | |
| Description | Wellcome Trust ISSF - Sample Predictor CiC2 |
| Amount | £6,000 (GBP) |
| Organisation | Wellcome Trust |
| Department | Wellcome Trust Institutional Strategic Support Fund |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | proteomics CiC2 |
| Amount | £120,000 (GBP) |
| Organisation | Cancer Research UK |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Description | proteomics CiC2 |
| Amount | £1,481,356 (GBP) |
| Organisation | The Brain Tumour Charity |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | |
| Title | Safe Haven (Database) Lung Solve |
| Description | The safe haven set up (database) within Lung Solve East is a new database set up utilising the multipartner collaboration between NSS, EPCC, Farr and Edris (ISD) and will have an impact on research going forward both within the team here, other researchers and the collaborators to further develop safe haven use within other modalities. The following is a list of completed new work that will allow the ongoing interrogation of the CT images: 1. Created a standalone analysis application capable of running in a safe haven environment, which performs fully automated analysis of DICOM lung images 2. Created a demonstration visualisation application that aggregates results across patients and combines with demographic data. Results can be visualised through a web browser as graphs or tables. 3. Demonstrated the pipeline operating in a simulated safe haven environment |
| Type Of Material | Database/Collection of data |
| Year Produced | 2015 |
| Provided To Others? | Yes |
| Impact | We have not added to the establishment of private or not for profit organisations but the platform created within EPCC (Lung Solve East) has enabled EPCC to develop and test the setup, computational requirements, administrative and security arrangements for such platforms. This will allow future work and the use of such platforms for similar projects whether within different clinical areas or on a wider scale incorporating a range of data to be successful within this environment. The creation and set-up of Lung Solve East has provided a valuable pathway going forward for EPCC for many projects in Edinburgh and beyond. |
| Description | Aridhia - Lung Solve CiC2 |
| Organisation | Aridhia Informatics Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project plan and vision |
| Collaborator Contribution | A multidisciplinary team of data scientists, information governance specialists, computer scientists, software developers and healthcare experts is delivering services across the UK and Europe, working collaboratively with the NHS, research organisations, life sciences companies, IT service providers and patients to transform clinical research into clinical practice. |
| Impact | 1. Created the structure and process for identifying and collecting data including images. 2. Setup and development of the administrative processes required for creation of, development of and access of the safe havens. 3. Creation of standalone analysis applications capable of running in a safe haven environment, performing fully automated analysis of DICOM lung images 4. Creation of visualisation applications to aggregates results across patients and combine with demographic data. Results are visualised through a web browser as graphs or tables. 5. Developed the algorithms and nodule mapping techniques utilised to analyse the scans in order to predict the outcomes. 6. Demonstrated that this can be accessed, inputted to, developed and used - the pipeline operating in a simulated safe haven environment. This is now ready for a national PACS "dump" of CT scans to enable the process for large scale data analysis for radiology. |
| Start Year | 2016 |
| Description | Blackford Analysis - Lung Solve CIC2 |
| Organisation | Blackford Analysis Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Project plan and vision |
| Collaborator Contribution | Advice and experts on regulatory framework and the possible hurdles to implementation. Blackford have fed into understanding and interacting with the workflow, looking at the PACS interface, integration and reporting as well as looking forward to the commercial considerations. |
| Impact | 1. Created the structure and process for identifying and collecting data including images. 2. Setup and development of the administrative processes required for creation of, development of and access of the safe havens. 3. Creation of standalone analysis applications capable of running in a safe haven environment, performing fully automated analysis of DICOM lung images 4. Creation of visualisation applications to aggregates results across patients and combine with demographic data. Results are visualised through a web browser as graphs or tables. 5. Developed the algorithms and nodule mapping techniques utilised to analyse the scans in order to predict the outcomes. 6. Demonstrated that this can be accessed, inputted to, developed and used - the pipeline operating in a simulated safe haven environment. |
| Start Year | 2016 |
| Description | CiC 2 Learning to Care |
| Organisation | MYSPHERA |
| Country | Spain |
| Sector | Private |
| PI Contribution | Applied to Horizon 2020 with MySphera as commercial partner. Application not funded. |
| Collaborator Contribution | Commercial partner in Horizon 2020 application. |
| Impact | Nothing further as application didn't get funded. |
| Start Year | 2017 |
| Description | CiC 2 Learning to Care |
| Organisation | My Diabetes My Way |
| Sector | Public |
| PI Contribution | Applied to Innovate UK to develop an algorithm for self-management of type-2 diabetes and integrate it with the MDMW IT infrastructure. |
| Collaborator Contribution | Commercial partner for Innovate UK grant |
| Impact | to be confirmed |
| Start Year | 2017 |
| Description | CiC 2013 (MRE software) |
| Organisation | Charité - University of Medicine Berlin |
| Country | Germany |
| Sector | Academic/University |
| PI Contribution | The software central to the CiC grant was developed in concert with beta testing at numerous centres using different MRI sequences and field strengths, different vendors, and different organs. Researchers involved in the beta testing are currently at: • Charité Medical University Berlin • Albert Einstein School of Medicine, New York • Mount Sinai Medical Center, New York • Wolfson Brain Imaging Centre, Cambridge • University of Birmingham Department of Engineering |
| Collaborator Contribution | beta testing of system |
| Impact | validated software |
| Start Year | 2015 |
| Description | CiC 2013 (learning to care) |
| Organisation | Meteorological Office UK |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | telemonitoring data on predictions of hospital admissions in Telescot. |
| Collaborator Contribution | investigations of the combined effects of weather and telemonitoring data on predictions of hospital admissions in Telescot. |
| Impact | data interpretation |
| Start Year | 2015 |
| Description | CiC 2013 (learning to care) |
| Organisation | Pharmatics Limited |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | telle-heath data |
| Collaborator Contribution | machine learning |
| Impact | new algorithm for data analysis |
| Start Year | 2017 |
| Description | CiC 2014 (Predicting MDD) |
| Organisation | MQ Mental Health Research |
| Department | MQ Fellowship |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Dr Kristin Nicodemus and Prof David Porteous are part of a UK wide network on Data Science established by the new mental health research charity MQ and are main contributors to a position paper being prepared for submission to Lancet Psychiatry. |
| Collaborator Contribution | Treatment pathways |
| Impact | position paper being prepared for submission to Lancet Psychiatry. |
| Start Year | 2015 |
| Description | CiC 2014 (imaging data) |
| Organisation | Farr Institute of Health Informatics Research |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We collaborated with Farr@Scotland, who in developing their research imaging archive independently identified this issue. A prototype of the tool has been used recently in a collaboration, automating the collection of imaging for an identified cohort, which previously had been a labour intensive manual process. |
| Collaborator Contribution | The imaging of the cohort will be used to investigate the development an automated software application that will identify stroke. |
| Impact | processed images |
| Start Year | 2015 |
| Description | CiC2 Learning to Care |
| Organisation | Medtronic |
| Country | United States |
| Sector | Private |
| PI Contribution | Applied to Horizon 2020 with Medronic as the commercial partner. Passed acceptance threshold but not funded. |
| Collaborator Contribution | Commercial partner for Horizon 2020 application |
| Impact | Nothing further as application didn't receive funding |
| Start Year | 2017 |
| Description | Farr Institute - Lung Solve CIC2 |
| Organisation | Farr Institute of Health Informatics Research |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Project plan and vision |
| Collaborator Contribution | Farr is a UK-wide research collaboration involving 21 academic institutions and health partners in England, Scotland and Wales. Publically funded by a consortium of ten organisations led by the Medical Research Council, the Institute is committed to delivering high-quality, cutting-edge research using 'big data' to advance the health and care of patients and the public. EPCC is working closely with the Farr Institute of Health Informatics Research (link is external) to build a new secure, data-driven computational platform for health research. |
| Impact | The most important benefit has been to establish within Edinburgh a pipeline and data environment for image analyses of chest Computerised Tomography (CT) scans in a secure safe haven linked to demographic data and enabling remote access for researchers across the UK. The set up and procedure/pipeline building utilising the multipartner collaboration within the LUNG SOLVE project will have an impact on research going forward. This is within the team and its collaborators and for other researchers across the UK, developing safe haven use and data interrogation within lung disease but also to be utilised across other modalities. Across two sites (and as such demonstrating the set up and use within different parameters) we have: 1. Created the structure and process for identifying and collecting data including images. 2. Setup and development of the administrative processes required for creation of, development of and access of the safe havens. 3. Creation of standalone analysis applications capable of running in a safe haven environment, performing fully automated analysis of DICOM lung images 4. Creation of visualisation applications to aggregates results across patients and combine with demographic data. Results are visualised through a web browser as graphs or tables. 5. Developed the algorithms and nodule mapping techniques utilised to analyse the scans in order to predict the outcomes. 6. Demonstrated that this can be accessed, inputted to, developed and used - the pipeline operating in a simulated safe haven environment. |
| Start Year | 2016 |
| Description | Industry interaction - Learning to Care CiC 2 |
| Organisation | GlaxoSmithKline (GSK) |
| Country | Global |
| Sector | Private |
| PI Contribution | Introductory meeting |
| Collaborator Contribution | Introductory meeting |
| Impact | no outputs |
| Start Year | 2017 |
| Description | Industry interactions - Learning to Care CiC 2 |
| Organisation | Koninklijke Philips Electronics N.V. |
| Department | Philips |
| Country | Global |
| Sector | Private |
| PI Contribution | Introductory conversation |
| Collaborator Contribution | Introductory conversation |
| Impact | no outputs to dates |
| Start Year | 2017 |
| Description | Industry interactions - Learning to Care CiC 2 |
| Organisation | Linde Group |
| Country | Global |
| Sector | Private |
| PI Contribution | Introductory meeting |
| Collaborator Contribution | Introductory meeting |
| Impact | no outputs to date |
| Start Year | 2017 |
| Description | Johnson and Johnson - PreMDD CiC2 |
| Organisation | Johnson & Johnson |
| Country | United States |
| Sector | Private |
| PI Contribution | in discussions based on App |
| Collaborator Contribution | in discussions based on App |
| Impact | no outputs to date |
| Start Year | 2017 |
| Description | Mentholaturm Company - MRE CIC2 |
| Organisation | The Mentholatum Company Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | intellectual property |
| Collaborator Contribution | Company provided an introduction to lead scientists in the Healthcare and Beauty divisions of Walgreens Boots Alliance (WBA) following visits to the University of Edinburgh we have submitted a proposal for a project to be funded by WBA concerning MRE studies of the face. |
| Impact | Funding proposal submitted to WBA - outcome to be confirmed in 2018. |
| Start Year | 2017 |
| Description | My Diabetes My Way Innovate UK grant |
| Organisation | My Diabetes My Way |
| Sector | Public |
| PI Contribution | Commercial partner for the Innovate UK Grant |
| Collaborator Contribution | Commercial partner for the Innovate UK Grant |
| Impact | Gained Innovate UK funding with this commercial partner |
| Start Year | 2019 |
| Description | Oncomark - Sample Predictor CiC2 |
| Organisation | Oncomark Ltd |
| Country | Ireland |
| Sector | Private |
| PI Contribution | General project discussions |
| Collaborator Contribution | General project discussions |
| Impact | No outputs to date |
| Start Year | 2017 |
| Description | Philips Research - Sample Predictor CiC2 |
| Organisation | Philips Research |
| Country | United States |
| Sector | Private |
| PI Contribution | General project discussions |
| Collaborator Contribution | General project discussions |
| Impact | No outputs yet |
| Start Year | 2017 |
| Description | UCL - Lung Solve CIC2 |
| Organisation | University College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Joint post-doctoral scientist supported by the EPSRC Image guided surgery network |
| Collaborator Contribution | Joint post-doctoral scientist supported by the EPSRC Image guided surgery network |
| Impact | Post-doctoral scientist work will progress the project |
| Start Year | 2017 |
| Title | Image processing software for producing super resolution MRE |
| Description | Image processing software for producing super resolution MRE. First high quality image available To provide detailed viscoelastic maps of a target volume, such as soft tissue in a living subject, using an imaging technique that combines magnetic resonance imaging and acoustic imaging techniques, images generated at a plurality of different acoustic frequencies are filtered and post-processed. |
| IP Reference | GB1508418.9 |
| Protection | Patent application published |
| Year Protection Granted | |
| Licensed | No |
| Impact | supporting significant discussions with potential partners |
| Title | METHODS AND KITS FOR PREDICTING THE RESPONSE TO THERAPY OF CANCER |
| Description | The present invention relates to methods and kits for predicting an individual's response to cancer therapy, predicting the progression and predicting the prognosis of cancer in an individual, and for selecting a treatment for cancer in an individual. |
| IP Reference | WO2016092299 |
| Protection | Patent granted |
| Year Protection Granted | 2016 |
| Licensed | No |
| Impact | unknown |
| Title | Automated data processsing - Lung Solve |
| Description | The software originally developed by UCL for processing of images has been updated and improved so that it can successfully process a wider range of data that accompanies the images. The software has been updated to automate the data processing so it runs automatically when new data are added to the platform. It has been modified to aggregate the individual patient outputs into population data. An app has been developed to visualise the data results on the platform website. |
| Type Of Technology | Software |
| Year Produced | 2015 |
| Impact | Software improved to aggregate the individual patient output into population data. |