Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes

This study assessed the safety and performance of the Omnipod personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. A supervised 54-h hybrid cl...

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Veröffentlicht in:	Diabetes technology & therapeutics Jg. 20; H. 9; S. 585
Hauptverfasser:	Buckingham, Bruce A, Christiansen, Mark P, Forlenza, Gregory P, Wadwa, R Paul, Peyser, Thomas A, Lee, Joon Bok, O'Connor, Jason, Dassau, Eyal, Huyett, Lauren M, Layne, Jennifer E, Ly, Trang T
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.09.2018
Schlagworte:	Adult Algorithms Blood Glucose Diabetes Mellitus, Type 1 - drug therapy Feeding Behavior Female Humans Hypoglycemic Agents - administration & dosage Insulin - administration & dosage Male Middle Aged Pancreas, Artificial Postprandial Period Young Adult Artificial pancreas Omnipod Automated insulin delivery tubeless Insulin pump Closed-loop Postprandial
ISSN:	1557-8593, 1557-8593
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Abstract	This study assessed the safety and performance of the Omnipod personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18-65 years with type 1 diabetes and HbA1c 6.0%-10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus. Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0-1.2%), 70-180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0-0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal. The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes.
AbstractList	This study assessed the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals.BACKGROUNDThis study assessed the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals.A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18-65 years with type 1 diabetes and HbA1c 6.0%-10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus.MATERIALS AND METHODSA supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18-65 years with type 1 diabetes and HbA1c 6.0%-10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus.Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0-1.2%), 70-180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0-0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal.RESULTSTwelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0-1.2%), 70-180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0-0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal.The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes.CONCLUSIONSThe Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes. This study assessed the safety and performance of the Omnipod personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18-65 years with type 1 diabetes and HbA1c 6.0%-10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus. Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0-1.2%), 70-180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0-0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal. The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes.
Author	Christiansen, Mark P Wadwa, R Paul Peyser, Thomas A Layne, Jennifer E Dassau, Eyal Lee, Joon Bok O'Connor, Jason Huyett, Lauren M Ly, Trang T Forlenza, Gregory P Buckingham, Bruce A
Author_xml	– sequence: 1 givenname: Bruce A surname: Buckingham fullname: Buckingham, Bruce A organization: 1 Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University , Stanford, California – sequence: 2 givenname: Mark P surname: Christiansen fullname: Christiansen, Mark P organization: 2 Diablo Clinical Research , Walnut Creek, California – sequence: 3 givenname: Gregory P surname: Forlenza fullname: Forlenza, Gregory P organization: 3 Barbara Davis Center for Diabetes, University of Colorado School of Medicine , Aurora, Colorado – sequence: 4 givenname: R Paul surname: Wadwa fullname: Wadwa, R Paul organization: 3 Barbara Davis Center for Diabetes, University of Colorado School of Medicine , Aurora, Colorado – sequence: 5 givenname: Thomas A surname: Peyser fullname: Peyser, Thomas A organization: 4 ModeAGC LLC , Palo Alto, California – sequence: 6 givenname: Joon Bok surname: Lee fullname: Lee, Joon Bok organization: 5 Insulet Corporation , Billerica, Massachusetts – sequence: 7 givenname: Jason surname: O'Connor fullname: O'Connor, Jason organization: 5 Insulet Corporation , Billerica, Massachusetts – sequence: 8 givenname: Eyal surname: Dassau fullname: Dassau, Eyal organization: 6 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts – sequence: 9 givenname: Lauren M surname: Huyett fullname: Huyett, Lauren M organization: 5 Insulet Corporation , Billerica, Massachusetts – sequence: 10 givenname: Jennifer E surname: Layne fullname: Layne, Jennifer E organization: 5 Insulet Corporation , Billerica, Massachusetts – sequence: 11 givenname: Trang T surname: Ly fullname: Ly, Trang T organization: 5 Insulet Corporation , Billerica, Massachusetts
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References	28733374 - Diabetes Care. 2017 Aug;40(8):994-999 27629148 - JAMA. 2016 Oct 4;316(13):1407-1408 19175898 - Pediatr Diabetes. 2009 Apr;10(2):142-8 28656656 - Pediatr Diabetes. 2018 Feb;19(1):14-17 7497862 - Diabetes Care. 1995 Apr;18(4):517-22 29658779 - Diabetes Technol Ther. 2018 May;20(5):335-343 25188375 - Diabetes Technol Ther. 2014 Oct;16(10):623-32 29162582 - Diabetes Care. 2017 Dec;40(12):1622-1630 28533136 - Lancet Diabetes Endocrinol. 2017 Jul;5(7):501-512 26257323 - Diabetes Obes Metab. 2015 Dec;17(12):1173-9 27330126 - Diabetes Care. 2016 Jul;39(7):1175-9 28842523 - Diabetes Care. 2017 Nov;40(11):1453-1461 27364997 - Diabetologia. 2016 Sep;59(9):1795-805 28039172 - Diabetes Care. 2017 Jul;40(7):832-838 27979887 - Diabetes Care. 2017 Jan;40(Suppl 1):S4-S5 28340542 - Diabetes Educ. 2017 Apr;43(2):223-232 27203694 - Diabetes Technol Ther. 2016 Jun;18(6):341-2 29422651 - Sci Rep. 2018 Feb 8;8(1):2621 19885271 - J Diabetes Sci Technol. 2008 Sep;2(5):863-72 25998293 - Diabetes Care. 2015 Jun;38(6):1008-15 25348683 - Pediatr Diabetes. 2016 Feb;17(1):28-35 24757226 - Diabetes Care. 2014;37(5):1191-7 28134564 - Diabetes Technol Ther. 2017 Mar;19(3):155-163 27621531 - Clin Diabetes. 2016 Jul;34(3):142-7 24725149 - Ann N Y Acad Sci. 2014 Apr;1311:102-23 29431513 - Diabetes Technol Ther. 2018 Apr;20(4):257-262
References_xml	– reference: 24757226 - Diabetes Care. 2014;37(5):1191-7 – reference: 24725149 - Ann N Y Acad Sci. 2014 Apr;1311:102-23 – reference: 27364997 - Diabetologia. 2016 Sep;59(9):1795-805 – reference: 25188375 - Diabetes Technol Ther. 2014 Oct;16(10):623-32 – reference: 25998293 - Diabetes Care. 2015 Jun;38(6):1008-15 – reference: 27330126 - Diabetes Care. 2016 Jul;39(7):1175-9 – reference: 27979887 - Diabetes Care. 2017 Jan;40(Suppl 1):S4-S5 – reference: 29658779 - Diabetes Technol Ther. 2018 May;20(5):335-343 – reference: 28134564 - Diabetes Technol Ther. 2017 Mar;19(3):155-163 – reference: 27203694 - Diabetes Technol Ther. 2016 Jun;18(6):341-2 – reference: 25348683 - Pediatr Diabetes. 2016 Feb;17(1):28-35 – reference: 28656656 - Pediatr Diabetes. 2018 Feb;19(1):14-17 – reference: 29431513 - Diabetes Technol Ther. 2018 Apr;20(4):257-262 – reference: 28842523 - Diabetes Care. 2017 Nov;40(11):1453-1461 – reference: 28340542 - Diabetes Educ. 2017 Apr;43(2):223-232 – reference: 19885271 - J Diabetes Sci Technol. 2008 Sep;2(5):863-72 – reference: 28733374 - Diabetes Care. 2017 Aug;40(8):994-999 – reference: 26257323 - Diabetes Obes Metab. 2015 Dec;17(12):1173-9 – reference: 29162582 - Diabetes Care. 2017 Dec;40(12):1622-1630 – reference: 19175898 - Pediatr Diabetes. 2009 Apr;10(2):142-8 – reference: 29422651 - Sci Rep. 2018 Feb 8;8(1):2621 – reference: 27629148 - JAMA. 2016 Oct 4;316(13):1407-1408 – reference: 27621531 - Clin Diabetes. 2016 Jul;34(3):142-7 – reference: 7497862 - Diabetes Care. 1995 Apr;18(4):517-22 – reference: 28533136 - Lancet Diabetes Endocrinol. 2017 Jul;5(7):501-512 – reference: 28039172 - Diabetes Care. 2017 Jul;40(7):832-838
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SubjectTerms	Adult Algorithms Blood Glucose Diabetes Mellitus, Type 1 - drug therapy Feeding Behavior Female Humans Hypoglycemic Agents - administration & dosage Insulin - administration & dosage Male Middle Aged Pancreas, Artificial Postprandial Period Young Adult
Title	Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes
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