Literature DB >> 27333446

Improving Efficacy of Inhaled Technosphere Insulin (Afrezza) by Postmeal Dosing: In-silico Clinical Trial with the University of Virginia/Padova Type 1 Diabetes Simulator.

Roberto Visentin1, Clemens Giegerich2, Robert Jäger2, Raphael Dahmen2, Anders Boss3, Marshall Grant4, Chiara Dalla Man1, Claudio Cobelli1, Thomas Klabunde2.   

Abstract

BACKGROUND: Technosphere(®) insulin (TI), an inhaled human insulin with a fast onset of action, provides a novel option for the control of prandial glucose. We used the University of Virginia (UVA)/Padova simulator to explore in-silico the potential benefit of different dosing regimens on postprandial glucose (PPG) control to support the design of further clinical trials. Tested dosing regimens included at-meal or postmeal dosing, or dosing before and after a meal (split dosing).
METHODS: Various dosing regimens of TI were compared among one another and to insulin lispro in 100 virtual type-1 patients. Individual doses were identified for each regimen following different titration rules. The resulting postprandial glucose profiles were analyzed to quantify efficacy and the risk for hypoglycemic events.
RESULTS: This approach allowed us to assess the benefit/risk for each TI dosing regimen and to compare results with simulations of insulin lispro. We identified a new titration rule for TI that could significantly improve the efficacy of treatment with TI.
CONCLUSION: In-silico clinical trials comparing the treatment effect of different dosing regimens with TI and of insulin lispro suggest that postmeal dosing or split dosing of TI, in combination with an appropriate titration rule, can achieve a superior postprandial glucose control while providing a lower risk for hypoglycemic events than conventional treatment with subcutaneously administered rapid-acting insulin products.

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Year:  2016        PMID: 27333446      PMCID: PMC5035370          DOI: 10.1089/dia.2016.0128

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  15 in total

Review 1.  The kinetics of insulin in man. I. General aspects.

Authors:  E Ferrannini; C Cobelli
Journal:  Diabetes Metab Rev       Date:  1987-04

2.  A minimal model of insulin secretion and kinetics to assess hepatic insulin extraction.

Authors:  Gianna Toffolo; Marco Campioni; Rita Basu; Robert A Rizza; Claudio Cobelli
Journal:  Am J Physiol Endocrinol Metab       Date:  2005-09-06       Impact factor: 4.310

3.  Adherence to insulin treatment, glycaemic control, and ketoacidosis in insulin-dependent diabetes mellitus. The DARTS/MEMO Collaboration. Diabetes Audit and Research in Tayside Scotland. Medicines Monitoring Unit.

Authors:  A D Morris; D I Boyle; A D McMahon; S A Greene; T M MacDonald; R W Newton
Journal:  Lancet       Date:  1997-11-22       Impact factor: 79.321

4.  Population pharmacokinetic model of human insulin following different routes of administration.

Authors:  Elizabeth Potocka; Robert A Baughman; Hartmut Derendorf
Journal:  J Clin Pharmacol       Date:  2010-10-12       Impact factor: 3.126

5.  GIM, simulation software of meal glucose-insulin model.

Authors:  Chiara Dalla Man; Davide M Raimondo; Robert A Rizza; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2007-05

6.  Incorporation of inhaled insulin into the FDA accepted University of Virginia/Padova Type 1 Diabetes Simulator.

Authors:  Roberto Visentin; Thomas Klabunde; Marshall Grant; Chiara Dalla Man; Claudio Cobelli
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015

7.  Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index.

Authors:  B P Kovatchev; D J Cox; L A Gonder-Frederick; D Young-Hyman; D Schlundt; W Clarke
Journal:  Diabetes Care       Date:  1998-11       Impact factor: 19.112

Review 8.  Coverage of prandial insulin requirements by means of an ultra-rapid-acting inhaled insulin.

Authors:  Anders H Boss; Richard Petrucci; Daniel Lorber
Journal:  J Diabetes Sci Technol       Date:  2012-07-01

9.  The UVA/PADOVA Type 1 Diabetes Simulator: New Features.

Authors:  Chiara Dalla Man; Francesco Micheletto; Dayu Lv; Marc Breton; Boris Kovatchev; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2014-01-01

10.  Translating the A1C assay into estimated average glucose values.

Authors:  David M Nathan; Judith Kuenen; Rikke Borg; Hui Zheng; David Schoenfeld; Robert J Heine
Journal:  Diabetes Care       Date:  2008-06-07       Impact factor: 19.112

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Journal:  J Diabetes Sci Technol       Date:  2016-09-25

2.  The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day.

Authors:  Roberto Visentin; Enrique Campos-Náñez; Michele Schiavon; Dayu Lv; Martina Vettoretti; Marc Breton; Boris P Kovatchev; Chiara Dalla Man; Claudio Cobelli
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3.  Clinical Impact of Blood Glucose Monitoring Accuracy: An In-Silico Study.

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4.  Minimal and Maximal Models to Quantitate Glucose Metabolism: Tools to Measure, to Simulate and to Run in Silico Clinical Trials.

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Journal:  J Diabetes Sci Technol       Date:  2021-05-25

5.  Modeling Between-Subject Variability in Subcutaneous Absorption of a Fast-Acting Insulin Analogue by a Nonlinear Mixed Effects Approach.

Authors:  Edoardo Faggionato; Michele Schiavon; Chiara Dalla Man
Journal:  Metabolites       Date:  2021-04-12

6.  Impact of Accelerating Insulin on an Artificial Pancreas System Without Meal Announcement: An In Silico Examination.

Authors:  Patricio Colmegna; Eda Cengiz; Jose Garcia-Tirado; Kristen Kraemer; Marc D Breton
Journal:  J Diabetes Sci Technol       Date:  2020-06-17

7.  Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models.

Authors:  Iván Contreras; Silvia Oviedo; Martina Vettoretti; Roberto Visentin; Josep Vehí
Journal:  PLoS One       Date:  2017-11-07       Impact factor: 3.240

Review 8.  Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas.

Authors:  J Geoffrey Chase; Thomas Desaive; Julien Bohe; Miriam Cnop; Christophe De Block; Jan Gunst; Roman Hovorka; Pierre Kalfon; James Krinsley; Eric Renard; Jean-Charles Preiser
Journal:  Crit Care       Date:  2018-08-02       Impact factor: 9.097

  8 in total

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