What is #DIYPS (Do-It-Yourself Pancreas System)?

#DIYPS (the Do-It-Yourself Pancreas System) was created by Dana Lewis and Scott Leibrand in the fall of 2013.

#DIYPS was developed with the goal of solving a well-known problem with an existing FDA-approved medical device. As recounted here (from Scott) and here (from Dana), we set out to figure out a way to augment continuous glucose monitor (CGM) alerts, which aren’t loud enough to wake heavy sleepers, and to alert a loved one if the patient is not responding.

We were able to solve those problems and include additional features such as:

  •  Real-time processing of blood glucose (BG), insulin on board, and carbohydrate decay
  •  Customizable alerts based on CGM data and trends
  •  Real-time predictive alerts for future high or low BG states (hours in advance)
  •  Continually updated recommendations for required insulin or carbs
  • ..and as of December 2014, we ‘closed the loop’ and have #DIYPS running as a closed loop artificial pancreas.

You can read this post for more details about how the system works.

While #DIYPS was invented for purposes of better using a continuous glucose monitor (CGM) and initially tailored for use with an insulin pump, what we discovered is that #DIYPS can actually be used with many types of diabetes technology. It can be utilized by those with:

  • CGM and insulin pump
  • CGM and multiple daily injections (MDI) of insulin
  • no CGM (fingerstick testing with BG meter) and insulin pump
  • no CGM (fingerstick testing with BG meter) and multiple daily injections (MDI) of insulin

Here are some frequently asked questions about #DIYPS:

  1. Q:I love it. How can I get it?A: Right now, #DIYPS is n=1, and because it is making recommendations based on CGM data, we can’t publicly post the code to enable someone else to utilize #DIYPS.But, you can get Nightscout, which includes all of the publicly-available components of #DIYPS, including the ability to upload Dexcom CGM data, view it on any web browser and on a Pebble watch, and get basic alarms for high and low BG. We’re working to further develop #DIYPS, and also to break out specific features and make them available in Nightscout as soon as possible.
  2. Q: “Does #DIYPS really work?”A: Yes! For N=1, we’ve seen some great results. Click here to read a post about the results from #DIYPS after the first 100 days – it’s comparable to the bionic pancreas trial results. Or, click here to read our results after using #DIYPS for a full year.
  3. Q: “Why do you think #DIYPS works?”A: There could be some correlation with increased timed/energy spent thinking about diabetes compared to normal. (We’d love to do some small scale trials comparing people who use CGMs with easy access to time-in-range metrics and/or eAG data, to compare this effect). And, #DIYPS has also taught us some key lessons related to pre-bolusing for meals and the importance of having insulin activity in the body before a meal begins. You should read 1) this post that talks about our lessons learned from #DIYPS; 2) this post that gives a great example of how someone can eat 120 grams of carbohydrates of gluten-free pizza with minimal impact to blood glucose levels with the help of #DIYPS; and 3) this post that will enable you to find out your own carbohydrate absorption rate that you can start using to help you decide when and how you bolus/inject insulin to handle large meals. And of course, the key reason #DIYPS works is because it reduces the cognitive load for a person with diabetes by constantly providing push notifications and real time alerts and predictions about what actions a person with diabetes might need to consider taking. (Read more detail from this post about the background of the system.)
  4. Q:Awesome!  What’s next?A: We’re working on new features for DIYPS, of course.  Those include:
    • better real-time BG readings using raw unfiltered sensor values
    • calculation of insulin activity and carb absorption curves (and from there, ISF & IC ratios, etc.) from historical data
    • better-calibrated BG predictions using those calculated absorption curves (with appropriate error bars representing predictive uncertainty)
    • recommendations for when to change basal rates, based on observed vs. predicted BG outcomes
    • integration with activity tracking and calendar data
    • closing the loop – done as of December 2014! :)

    We also are starting to collaborate with medical technology and device companies, the FDA, and other projects and organizations like Tidepool, to make sure that the ideas, insights, and features in #DIYPS get integrated as widely as possible. Stay tuned (follow the #DIYPS hashtagDana Lewis & Scott Leibrand on Twitter, and keep an eye on this blog) for more details about what we’re up to.

  5. Q: “I love it. What can I do to help the #DIYPS project?”A: We’d love to know if you’re interested in helping! First and foremost, if you have any ability to code (or a desire to learn), we need contributors to the Nightscout project.  There are many things to work on, including implementing the most broadly applicable #DIYPS features into Nightscout, so we need as many volunteers, with as many different types of skills, as we can get.  For those who are less technical, the CGM in the Cloud Facebook group is a great place to start. Click here to see the Nightscout project roadmap; it shows what developers are currently working on, what each of our priority focus areas are (as of 11/26/14), and the ‘backlog’ of projects we know we want (and the community wants), but no one has started on yet (jump on in!).
    If you want to contact us directly, you can reach out to us on Twitter (@DanaMLewis @ScottLeibrand and #DIYPS) or email us (dana@openAPS.org and scott@openAPS.org). We’d also love to know if you’re working on a similar project or if you’ve heard of something else that you think we should look into for a potential #DIYPS feature or collaboration.


Dana Lewis & Scott Leibrand

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