Patient Empowerment Through Predictive Personalised Decision Support (PEPPER)

NCT03186300 | Completed DMC

• 2 other identifiers: 599/16/EC689810
• Study Type: interventional
• Target: 8
• Locations: 1 country
• Sites: 1

Brief Summary

Patient Empowerment through Predictive PERsonalised decision support (PEPPER) is an European Union (EU) funded research project to develop a personalised clinical decision support system for Type 1 Diabetes Mellitus (T1DM) self-management. The tool provides insulin bolus dose advice, tailored to the needs of individuals. The system uses Case-Based Reasoning (CBR), an artificial intelligence methodology that adapts to new situations according to past experience. The PEPPER system also incorporates a safety module that promotes safety by providing glucose alarms, low-glucose insulin suspension, carbohydrate recommendations and fault detection.The principal research objectives are to assess the usability, safety, and technical proof of concept and feasibility of the PEPPER in participants with T1DM. Evaluation of safety is a priority and will be assessed throughout the clinical studies. The safety components only of the PEPPER system will initially be evaluated in an out-of-clinic environment (phase 1) and will measure incidence and percentage time spent in hypoglycaemia, evaluate usability and incidence of technical faults. Following the initial safety study, the overall PEPPER system (integrated with the CBR algorithm) will be assessed (phase 2) and the primary outcome will be percentage time spent in hypoglycaemia.

Conditions

Diabetes Mellitus, Type 1

Keywords

bolus advisor

Outcome Measures

Primary Outcomes (1)

• Change in the percentage of time spent in hypoglycaemia (glucose level below 3, 9 mmol/L or 70 mg/dl)

  The primary outcome is the percentage of time spent in hypoglycaemia defined as glucose level below 3.9 mmol/L (measurement used in UK) or below 70 mg/dl (measurement used in Spain).

  Comparison of the run-in period (2 week period) vs the intervention period (6 week period)

Secondary Outcomes (23)

• Number of incidence of low glucose alarms

  Evaluation during the intervention period (6 week period)

• Number of incidence of high glucose alarms

  Evaluation during the intervention period (6 week period)

• Number of incidence of carbohydrate adviser

  Evaluation during the intervention period (6 week period)

• Number of incidence of low glucose suspend

  Evaluation during the intervention period (6 week period)

• Number of incidence of fault detection alarm

  Evaluation during the intervention period (6 week period)

Study Arms (1)

PEPPER

OTHER

In the phase 1 participants will use PEPPER safety system (with the CBR algorithm enabled) and in the phase 2 participants will use whole PEPPER system (with the CBR algorithm integrated).

Device: PEPPER system

Interventions

PEPPER system DEVICE

In the phase 1 participants will use PEPPER safety system (with the CBR algorithm enabled) and in the phase 2 participants will use whole PEPPER system (with the CBR algorithm integrated).

PEPPER

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Adults ≥18years of age
• Diagnosis of T1DM for \> 1 year
• On MDI using a basal-bolus insulin regime or CSII (insulin pump) for at least 6 month
• Structured education done and good ability perform carbohydrates (CHO) counting
• HbA1c ≥ 48mmol/mol and ≤ 86mmol/mol
• Using insulin carbohydrates ratio (ICR) and insulin sensitivity factor (ISF) to calculate the mealtime bolus
• An understanding of and willingness to follow the protocol and sign the informed consent
• CBG measurements at least 2 times per day for calibration of the CGM

You may not qualify if:

• Severe episode of hypoglycaemia (requiring 3rd party assistance) in the 6 months prior to enrolment
• Diabetic ketoacidosis in the last 6 months prior to enrolment
• Impaired awareness of hypoglycaemia (based on Clarke score)
• Pregnancy, breastfeeding or intention of becoming pregnant over time of study procedures
• Enrolled in other clinical trials
• Have active malignancy or under investigation for malignancy
• Suspected or diagnosed endocrinopathy like adrenal insufficiency, unstable thyroidopathy, endocrine tumour
• Gastroparesis
• Autonomic neuropathy
• Macrovascular complications (acute coronary syndrome, transient ischaemic attack, cerebrovascular event within the last 12 months prior to enrolment in the study)
• Visual impairment including unstable proliferative retinopathy
• Reduced manual dexterity
• Inpatient psychiatric treatment
• Abnormal renal function test results (calculated Glomerular Filtration Rate (GFR) \<40 mL/min/1.73m2)
• Liver cirrhosis

Sponsors & Collaborators

• Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta: lead
• Imperial College London: collaborator
• Oxford Brookes University: collaborator
• Universitat de Girona: collaborator
• Cellnovo Limited: collaborator
• Romsoft SRL: collaborator

Study Sites (1)

Institut d'Investigació Biomèdica de Girona (IDIBGI)

Girona, Girona, 17007, Spain

Location

Related Publications (19)

• Buckingham B, Wilson DM, Lecher T, Hanas R, Kaiserman K, Cameron F. Duration of nocturnal hypoglycemia before seizures. Diabetes Care. 2008 Nov;31(11):2110-2. doi: 10.2337/dc08-0863. Epub 2008 Aug 11.

  PMID: 18694975 RESULT

• Perez-Gandia C, Facchinetti A, Sparacino G, Cobelli C, Gomez EJ, Rigla M, de Leiva A, Hernando ME. Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring. Diabetes Technol Ther. 2010 Jan;12(1):81-8. doi: 10.1089/dia.2009.0076.

  PMID: 20082589 RESULT

• Diabetes Control and Complications Trial Research Group; Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, Rand L, Siebert C. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep 30;329(14):977-86. doi: 10.1056/NEJM199309303291401.

  PMID: 8366922 RESULT

• Dassau E, Cameron F, Lee H, Bequette BW, Zisser H, Jovanovic L, Chase HP, Wilson DM, Buckingham BA, Doyle FJ 3rd. Real-Time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas. Diabetes Care. 2010 Jun;33(6):1249-54. doi: 10.2337/dc09-1487.

  PMID: 20508231 RESULT

• FDA Advisory Panel Votes to Recommend Non-Adjunctive Use of Dexcom G5 Mobile CGM. Diabetes Technol Ther. 2016 Aug;18(8):512-6. doi: 10.1089/dia.2016.07252.mr. Epub 2016 Jul 29. No abstract available.

  PMID: 27472488 RESULT

• Garg SK, Bookout TR, McFann KK, Kelly WC, Beatson C, Ellis SL, Gutin RS, Gottlieb PA. Improved glycemic control in intensively treated adult subjects with type 1 diabetes using insulin guidance software. Diabetes Technol Ther. 2008 Oct;10(5):369-75. doi: 10.1089/dia.2007.0303.

  PMID: 18715213 RESULT

• National Clinical Guideline Centre (UK). Type 1 Diabetes in Adults: Diagnosis and Management. London: National Institute for Health and Care Excellence (NICE); 2015 Aug. Available from http://www.ncbi.nlm.nih.gov/books/NBK315808/

  PMID: 26334079 RESULT

• Herrero P, Calm R, Vehi J, Armengol J, Georgiou P, Oliver N, Tomazou C. Robust fault detection system for insulin pump therapy using continuous glucose monitoring. J Diabetes Sci Technol. 2012 Sep 1;6(5):1131-41. doi: 10.1177/193229681200600518.

  PMID: 23063040 RESULT

• Herrero P, Pesl P, Reddy M, Oliver N, Georgiou P, Toumazou C. Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning. IEEE J Biomed Health Inform. 2015 May;19(3):1087-96. doi: 10.1109/JBHI.2014.2331896.

  PMID: 24956470 RESULT

• Herrero P, Pesl P, Bondia J, Reddy M, Oliver N, Georgiou P, Toumazou C. Method for automatic adjustment of an insulin bolus calculator: in silico robustness evaluation under intra-day variability. Comput Methods Programs Biomed. 2015 Apr;119(1):1-8. doi: 10.1016/j.cmpb.2015.02.003. Epub 2015 Feb 16.

  PMID: 25733405 RESULT

• Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group; Bode B, Beck RW, Xing D, Gilliam L, Hirsch I, Kollman C, Laffel L, Ruedy KJ, Tamborlane WV, Weinzimer S, Wolpert H. Sustained benefit of continuous glucose monitoring on A1C, glucose profiles, and hypoglycemia in adults with type 1 diabetes. Diabetes Care. 2009 Nov;32(11):2047-9. doi: 10.2337/dc09-0846. Epub 2009 Aug 12.

  PMID: 19675193 RESULT

• Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group; Tamborlane WV, Beck RW, Bode BW, Buckingham B, Chase HP, Clemons R, Fiallo-Scharer R, Fox LA, Gilliam LK, Hirsch IB, Huang ES, Kollman C, Kowalski AJ, Laffel L, Lawrence JM, Lee J, Mauras N, O'Grady M, Ruedy KJ, Tansey M, Tsalikian E, Weinzimer S, Wilson DM, Wolpert H, Wysocki T, Xing D. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008 Oct 2;359(14):1464-76. doi: 10.1056/NEJMoa0805017. Epub 2008 Sep 8.

  PMID: 18779236 RESULT

• Kovatchev BP, Breton M, Man CD, Cobelli C. In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. J Diabetes Sci Technol. 2009 Jan;3(1):44-55. doi: 10.1177/193229680900300106.

  PMID: 19444330 RESULT

• Lepore G, Dodesini AR, Nosari I, Scaranna C, Corsi A, Trevisan R. Bolus calculator improves long-term metabolic control and reduces glucose variability in pump-treated patients with Type 1 diabetes. Nutr Metab Cardiovasc Dis. 2012 Aug;22(8):e15-6. doi: 10.1016/j.numecd.2012.04.001. Epub 2012 Jun 4. No abstract available.

  PMID: 22673770 RESULT

• Reddy M, Pesl P, Xenou M, Toumazou C, Johnston D, Georgiou P, Herrero P, Oliver N. Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Nonrandomized Single-Arm Pilot Study. Diabetes Technol Ther. 2016 Aug;18(8):487-93. doi: 10.1089/dia.2015.0413. Epub 2016 May 19.

  PMID: 27196358 RESULT

• Reddy M, Rilstone S, Cooper P, Oliver NS. Type 1 diabetes in adults: supporting self management. BMJ. 2016 Mar 10;352:i998. doi: 10.1136/bmj.i998. No abstract available.

  PMID: 26965473 RESULT

• Vaddiraju S, Burgess DJ, Tomazos I, Jain FC, Papadimitrakopoulos F. Technologies for continuous glucose monitoring: current problems and future promises. J Diabetes Sci Technol. 2010 Nov 1;4(6):1540-62. doi: 10.1177/193229681000400632.

  PMID: 21129353 RESULT

• Sovik O, Thordarson H. Dead-in-bed syndrome in young diabetic patients. Diabetes Care. 1999 Mar;22 Suppl 2:B40-2.

  PMID: 10097898 RESULT

• Zisser H, Robinson L, Bevier W, Dassau E, Ellingsen C, Doyle FJ, Jovanovic L. Bolus calculator: a review of four "smart" insulin pumps. Diabetes Technol Ther. 2008 Dec;10(6):441-4. doi: 10.1089/dia.2007.0284.

  PMID: 19049372 RESULT

Related Links

• Project website

MeSH Terms

Conditions

Diabetes Mellitus, Type 1

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases

Study Officials

• José Manuel Fernández Real

  Institut d'Investigació Biomèdica de Girona (IDIBGI) Unitat de Diabetis, Endocrinologia i Nutrició de Girona (UDENG) Hospital Universitari de Girona Dr Josep Trueta

  PRINCIPAL INVESTIGATOR

• Mercè Fernández-Balsells

  Institut d'Investigació Biomèdica de Girona (IDIBGI) Unitat de Diabetis, Endocrinologia i Nutrició de Girona (UDENG) Hospital Universitari de Girona Dr Josep Trueta

  PRINCIPAL INVESTIGATOR

• Nick Oliver

  Imperial Collage London

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DEVICE FEASIBILITY
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: May 23, 2017
• First Posted: June 14, 2017
• Study Start: September 1, 2017
• Primary Completion: December 12, 2018
• Study Completion: December 12, 2018
• Last Updated: March 27, 2026

Record last verified: 2026-03

Locations

ES (1)