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PEPPER SIGNED

Patient Empowerment through Predictive PERsonalised decision support

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 PEPPER project word cloud

Explore the words cloud of the PEPPER project. It provides you a very rough idea of what is the project "PEPPER" about.

health    adoption    diabetes    data    risk    professionals    basal    adaptive    examine    social    meets    quality    hindered    behavioural    broad    adverse    thereby    medical    communicated    personalised    bolus    clinical    participate    individuals    safety    diseases    validated    involve    initially    device    capacity    patient    previously    raises    framework    bespoke    regulatory    interactions    outputs    predictive    hypoglycaemia    episodes    chronic    outcomes    human    events    emphasis    predictions    monitoring    sources    disease    mobile    components    insulin    decision    limits    underlying    usability    meet    personal    reasoning    lifestyle    therapy    empower    life    architecture    combined    stage    commercial    integrating    computer    adhere    time    environmental    dose    hyperglycaemia    preventing    setting    ing    physiological    alarms    self    interoperability    individual    glucose    healthcare    standards    innovation    innovative    people    ambulatory    guidance    tool    advice   

Project "PEPPER" data sheet

The following table provides information about the project.

Coordinator
OXFORD BROOKES UNIVERSITY 

Organization address
address: HEADINGTON CAMPUS GIPSY LANE
city: OXFORD
postcode: OX3 OBP
website: www.brookes.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website http://www.pepper.eu.com/
 Total cost 3˙548˙071 €
 EC max contribution 3˙548˙071 € (100%)
 Programme 1. H2020-EU.3.1.4. (Active ageing and self-management of health)
 Code Call H2020-PHC-2015-single-stage
 Funding Scheme RIA
 Starting year 2016
 Duration (year-month-day) from 2016-02-01   to  2020-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    OXFORD BROOKES UNIVERSITY UK (OXFORD) coordinator 643˙013.00
2    IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE UK (LONDON) participant 1˙198˙398.00
3    FUNDACIO INSTITUT D'INVESTIGACIO BIOMEDICA DE GIRONA DOCTOR JOSEP TRUETA ES (GIRONA) participant 651˙555.00
4    CELLNOVO UK (LONDON) participant 406˙248.00
5    UNIVERSITAT DE GIRONA ES (GIRONA) participant 327˙355.00
6    ROMSOFT SRL RO (IASI) participant 321˙500.00

Map

 Project objective

This proposal is for a personalised decision support system for chronic disease management that will make predictions based on real-time data in order to empower individuals to participate in the self-management of their disease. The design will involve users at every stage to ensure that the system meets patient needs and raises clinical outcomes by preventing adverse episodes and improving lifestyle, monitoring and quality of life. Research will be conducted into the development of an innovative adaptive decision support system based on case-based reasoning combined with predictive computer modelling. The tool will offer bespoke advice for self-management by integrating personal health systems with broad and various sources of physiological, lifestyle, environmental and social data. The research will also examine the extent to which human behavioural factors and usability issues have previously hindered the wider adoption of personal guidance systems for chronic disease self-management. It will be developed and validated initially for people with diabetes on basal-bolus insulin therapy, but the underlying approach can be adapted to other chronic diseases. There will be a strong emphasis on safety, with glucose predictions, dose advice, alarms, limits and uncertainties communicated clearly to raise individual awareness of the risk of adverse events such as hypoglycaemia or hyperglycaemia. The outputs of this research will be validated in an ambulatory setting and a key aspect will be innovation management. All components will adhere to medical device standards in order to meet regulatory requirements and ensure interoperability, both with existing personal health systems and commercial products. The resulting architecture will improve interactions with healthcare professionals and provide a generic framework for providing adaptive mobile decision support, with innovation capacity to be applied to other applications, thereby increasing the impact of the project.

 Deliverables

List of deliverables.
Ethical approval for the validation study Other 2020-01-20 17:38:59
Ethical approval for the feasibility study Other 2020-01-20 17:38:58
Clinical protocol for the clinical validation study Other 2020-01-20 17:38:58
Regulatory documentation Documents, reports 2020-01-20 17:38:58
Project website Websites, patent fillings, videos etc. 2020-01-20 17:38:58
Clinical protocol for feasibility study Other 2020-01-20 17:38:58
Report on standards and regulatory approval acceptance Documents, reports 2020-01-20 17:38:59

Take a look to the deliverables list in detail:  detailed list of PEPPER deliverables.

 Publications

year authors and title journal last update
List of publications.
2017 Daniel Brown, Clare Martin, David Duce, Arantza Aldea, R. Harrison
Towards a Formal Model of Type 1 Diabetes for Artificial Intelligence
published pages: , ISSN: , DOI:
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes AIME 2017 2020-01-20
2016 Participants of the1st ECAI Workshop on Artificial intelligence for Diabetes
1st ECAI Workshop on Artificial intelligence for Diabetes
published pages: , ISSN: , DOI: 10.5281/zenodo.400204
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes 1 2020-01-20
2017 Pau Herrero, Peter Pesl, Monika Reddy, Nick Oliver, Pantelis Georgiou
Automatic Adjustment of Basal Insulin Infusion Rates in Type 1 Diabetes using Run-to-Run Control and Case-Based Reasoning
published pages: , ISSN: , DOI:
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes AIME 2017 2020-01-20
2016 Herrero, Pau; López, Beatriz; Martin, Clare
PEPPER: Patient Empowerment Through Predictive Personalised Decision Support
published pages: , ISSN: , DOI: 10.5281/zenodo.427542
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes 2020-01-20
2016 López Ibáñez, Beatriz; Viñas, Ramon; Torrent-Fontbona, Ferran; Fernández-Real Lemos, José Manuel
Handling Missing Phenotype Data with Random Forests for Diabetes Risk Prognosis
published pages: , ISSN: , DOI: 10.5281/zenodo.427979
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes 1 2020-01-20
2017 Torrent-Fontbona, Ferran; López Ibáñez, Beatriz; Pozo-Alonso, Alejandro
A CBR-based bolus recommender system for type 1 diabetes
published pages: , ISSN: , DOI:
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes 2 2020-01-20

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The information about "PEPPER" are provided by the European Opendata Portal: CORDIS opendata.

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