PEPPER: Patient Empowerment through Predictive PERsonalised decision support
Completed Project (2016-2020)
Research Team: Dr Pau Herrero, Dr. Parizad Avari, Dr Monika Reddy, Dr Chengyuan Liu, Prof Des Johnston, Prof Chris Toumazou, Prof Nick Oliver, and Dr Pantelis Georgiou
Collaborators: Oxford Brookes University, Universitat de Girona, Institut d’Investigació Biomèdica de Girona, Cellnovo, Romsoft
Funding: European Union’s Horizon 2020 research and innovation programme under grant agreement No 689810
Insulin bolus calculators can assist people with Type 1 diabetes to calculate the amount of insulin required for meals to optimise glucose levels. Whilst some bolus calculators use simple rules to consider parameters such as exercise, illness, and menstrual cycle, all commercially available bolus calculators lack the ability to automatically adapt over time to respond to an individual’s needs or changes in insulin sensitivity, providing real-time adaptive bolus advice to the user.
To overcome this limitation, and within the framework of the EU-funded PEPPER project, we have developed a system that provides personalised bolus advice for people with Type 1 diabetes. The system incorporates an adaptive insulin recommender system based on artificial intelligence methodology, coupled with a safety system that includes predictive glucose alerts and alarms, predictive low-glucose insulin suspension, personalised carbohydrate recommendations, and dynamic bolus insulin constraint. We evaluated the safety and feasibility of the PEPPER system compared to a standard bolus calculator on an open-labeled multicentre randomized controlled cross-over study on 54 participants with Type 1 diabetes. The PEPPER system was proven to be safe, and despite not showing significant changes in glycaemic outcomes, there is wide scope for integrating PEPPER into routine diabetes management. The project has received the category of 'Tech Ready' by the European Commission's Innovation Radar.
For more information visit the PEPPER project homepage.
Clinical trial registration: ClinicalTrials.gov NCT03849755
- Avari, P., Leal, Y., Herrero, P., Wos, M., Jugnee, N., Arnoriaga-Rodríguez, M., Thomas, M., Liu, C., Massana, Q., Lopez, B., et al. Safety and feasibility of the PEPPER adaptive bolus advisor and safety system; a randomized control study. Diabetes Technology and Therapeutics. (2020).
- Liu, C., Avari, P., Leal, Y., Wos, M., Sivasithamparam, K., Georgiou, P., Reddy, M., Fernández-Real, J. M., Martin, C., Fernández-Balsells, M., Oliver, N. & Herrero, P. A modular safety system for an insulin dose recommender: a feasibility study. Journal of diabetes science and technology 14, 87–96. (2020).
- Liu, C., Vehí, J., Avari, P., Reddy, M., Oliver, N., Georgiou, P. & Herrero, P. Long-term glucose forecasting using a physiological model and deconvolution of the continuous glucose monitoring signal. Sensors 19, 4338. x (2019).
- Duce, D. A., Martin, C., Russell, A., Brown, D., Aldea, A., Alshaigy, B., Harrison, R., Waite, M., Leal, Y., Wos, M., Fernandez-Balsells, M., Real, J. M. F., Nita, L., López, B., Massana, J., Avari, P., Herrero, P., Jugnee, N., Oliver, N. & Reddy, M. Visualizing Usage Data from a Diabetes Management System in Computer Graphics and Visual Computing (CGVC) (eds Ritsos, P. D. & Xu, K.) (The Eurographics Association, 2020).