The first (and currently only) in silico diabetes model accepted by the FDA as a substitute for pre-clinical animal testing of new treatment strategies for Type 1 Diabetes Mellitus.

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[wptabtitle] Overview[/wptabtitle]

T1DMS is a computer simulator of the dynamics of the human metabolic glucose-insulin system. It is based on a kinetic model developed from quantitative knowledge of glucose-insulin metabolism in conjunction with data from a large-population human subject study.
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In January 2008, T1DMS became the first computer tool accepted by the FDA as a substitute for animal trials in the pre-clinical testing of certain control strategies in Type 1 Diabetes Mellitus. Implemented in Simulink/MATLAB, T1DMS uses a well-defined set of interfaces for testing of closed loop, user-defined treatment scenarios.
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TEG offers Simulation Services for the development and optimization of T1D-related devices, protocols, and treatments using the T1DMS. Used in conjunction with the full FDA-accepted in silico subject population, TEG’s T1DMS Simulation Services can be a fast-track to FDA IDE submission.
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Click here to read the T1DMS Simulation Services Whitepaper …

Additionally, TEG distributes and supports a Distributed Version of the T1D metabolic simulator (with a smaller “sample” in silico patient population). This Distributed Version provides members of the wider diabetes research community with a T1DMS system for independent research and teaching.
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[wptabtitle] The T1DMS Difference[/wptabtitle]

Most diabetes models provide only average group-level responses to different treatment strategies based on study populations of randomized controlled clinical trials. Conversely, using T1DMS, pre-clinical testing and experiments are conducted at the level of an individual subject providing insight into the intra- and inter-personal differences seen in humans, in response to the treatment protocol.

The key advantages to using T1DMS are:

  • Individualized, intra-personal results
  • Inter-personal differences are revealed across the spectrum of human variation
  • T1DMS is, to our knowledge, the only model with pediatric and adolescent populations – others only have adults
  • Model design can be identical to a proposed clinical study*
  • Provides individual real-time glucose traces* for visual understanding of insulin-glucose fluctuation
  • Population results are calculated from the individual results as in a clinical trial

* Per FDA’s Draft Guidance for Industry and Food and Drug Administration Staff – The Content of Investigational Device Exemption (IDE) and Premarket Approval (PMA) Applications for Low Glucose Suspend (LGS) Device Systems[/wptabcontent]

[wptabtitle] Applications & Benefits[/wptabtitle]

The capabilities of T1DMS have opened up new possibilities in the mission to bring novel treatments, protocols, and devices to diabetes patients. T1DMS gives researchers a well-defined and validated tool to assess diabetes treatment strategies and controls while saving time and money.

Specific R&D benefits include the following:

  • T1DMS has been shown to reduce the research, development and IDE approval process from 2.5 years to less than 1 year
  • T1DMS can save millions of dollars in bringing new devices and treatments to the marketplace, as an accepted replacement for pre-clinical animal studies
  • T1DMS enables rigorous device/protocol testing scenarios on virtual subjects that would not be possible/ethical in animal and human studies

Typical T1DMS simulation studies investigate “real-life” scenarios including:

  • Modeling and testing of insulin dosing algorithms
  • Subject-specific basal / bolus insulin dosing
  • Insulin pumps and continuous glucose monitors
  • Meal patterns and amounts based on carbohydrate counts
  • Temporary insulin resistance / exercise component
  • SMBG testing with manual correction boluses
  • Rescue carbohydrates
  • Full range of options to model a person in-the-loop

Click here to view example scenarios for which T1DMS has been applied …

T1DMS provides a variety of analysis tools and metrics to understand the simulation data. Such analyses include:

  • Blood glucose excursion analysis
  • Control Variability Grid Analysis
  • Error Grid – Continuous Glucose Analysis
  • Number of subjects experiencing low and high glucose episodes
  • Full range of individual (per subject) responses and population responses