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Why the DIY part of OpenAPS is important

by Dana Lewis

I had the chance to talk about DIYPS and OpenAPS during a demo session in DC last week. (Thank you to Gary from Quantified Self and Marty from the National Academy of Sciences for making this possible!)

I walked away with several insights:

  1. Many people don’t know about diabetes; fewer have a realization of current diabetes tech. In several cases as I was describing the closed loop artificial pancreas, people stopped me and were wowed – but not by the closed loop. They were impressed by the CGM.
  2. Others think that this type of technology is already out on the market.

So, I believe we have a long way to go in communicating and advocating for this type of technology. We know it’s behind where it should be – and we want it to catch up. That’s a big part of the OpenAPS goals to help the FDA, device companies, and everyone involved move a little faster than they might otherwise, because #WeAreNotWaiting.

But here’s the other question I was often asked: “How many people have you given this to?”

I frequently embarked on an explanation of how we can’t “give” away #DIYPS or the OpenAPS implementation – in fact, we can’t and won’t give away the code, either. Some of that is because the FDA says no – and some of it is common sense and principles that both Scott and I hold.

Here’s why I think it is so important to keep the DIY in DIYPS and each OpenAPS implementation that is in progress:

  • You need to have a deep understanding of the system before even considering using it on yourself. You need to know what it’s trying to do in all situations, including the fringe cases (the “this is unlikely to happen but if it does…”), so that you know when it’s working – and when it’s not – whether it’s 3pm in the afternoon at work, or 3am and you wake up and find something is not right and the system is not working.
  • You need to go step by step and test and ensure at each stage that it is working as expected – both in a “this is what it should be doing” and “it is giving out the correct amount of insulin”. Remember, insulin is a lethal drug. It’s also a lifesaving drug. It’s important to remember both of these things and balance the risks accordingly.

From the conversations I’ve had with people interested in learning more or getting a DIYPS-type system for themselves, they fall into two categories:

  1. “How can I buy it from you?”
  2. “What do I need to do to make one?”

Given my above reasoning, the second question is my favorite. The first one scares me, if someone does not then switch to the #2 question. Many people do go from #1 to #2, which is great.

DIYPS, for me, and OpenAPS implementations, for others, are works in progress. They’re not perfect. They’re better than what’s out there (like sleeping through alarms when you’re low at night), but they also have big risks. And it’s important to know, and respect these risks, and understand the limitations of the system, before being able to take advantage of this type of system – and to build the system with appropriate safeguards. (This is one of the reason we have OpenAPS, for example, designed to accept multiple failure points – like walking out of range, loss of connectivity, etc.)

The ability to buy a “black box” type system where you don’t know exactly how it works, but you trust that it works? That will be coming from the major device manufacturers in several years – hopefully sooner rather than later, and that’s something that OpenAPS will hopefully help make happen more quickly.

So to answer the #2 question, what do you need to make a DIYPS or OpenAPS of your own?

I’ll answer the technical aspects of this question in another post, but the first thing I always say is: “The willingness to build and test and test and test some more before ever considering using it on yourself.”

#DIYPS & #OpenAPS

by Dana Lewis

Since I‘ve been using #DIYPS for over a year and also had the closed loop version running for more than two months with excellent results, I get several questions every week about how/when we’re going to make it available to other people. #DIYPS is an individual implementation that we built, and because of FDA regulations it’s not something we can give to another person to use. (Not to mention it’s not been tested for more than n=1, etc.) But, both Scott and I are passionate about moving diabetes technology forward for all, and so this week we kicked off the OpenAPS project.

#OpenAPS is our initiative to build on the #DIYPS closed loop work and eventually make this type of technology available (and faster than the market and traditional research is otherwise moving) for more people with diabetes. We aim to encourage other independent researchers to build their own closed loop implementations based on the OpenAPS reference design, and share their results and help us improve the design further. We are also working toward clinical trials that will enable more people to test and use the system during the research phase, but without having to code and build their own implementation of a closed loop artificial pancreas system. And all of this will be done in an open, transparent way so people can ask questions, monitor progress, and get involved at various stages.

The Open Artificial Pancreas System (#OpenAPS) is an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of Type 1 diabetes.

We believe that we can make safe and effective APS technology available more quickly, to more people, rather than just waiting for current APS efforts to complete clinical trials and be FDA-approved and commercialized through traditional processes. And in the process, we believe we can engage the untapped potential of dozens or possibly hundreds of patient innovators and independent researchers and also make APS technology available to hundreds or thousands of people willing to participate as subjects in clinical trials.

At the end of the process, we hope to have produced an FDA-approved #OpenAPS reference design and reference implementation that can be used by any medical device manufacturer with minimal regulatory burden. We believe this will in turn allow manufacturers (and the academic research teams they work with) to turn more of their attention to designing and testing more advanced APS systems, and thereby accelerate the pace of innovation toward new and improved Type 1 diabetes treatments, and eventually a cure.

In the mean time, it will make basic overnight closed loop APS technology widely available to anyone with compatible medical devices, thereby reducing the burden of Type 1 diabetes on everyone who lives with the disease.

I’ll continue to post here often with data and updates from my experience & work with #DIYPS, which I’m continuing to use. But I also encourage you to bookmark OpenAPS.org if you’re interested in watching that work move forward, too – and as always, we’ll be on Twitter with #DIYPS and #OpenAPS as @DanaMLewis and @ScottLeibrand (and you can email us for #DIYPS or #OpenAPS info at Dana@OpenAPS.org and Scott@OpenAPS.org).

Why #DIYPS N=1 data is significant (and #DIYPS is a year old!)

by Dana Lewis
As I’ve said many times, last year we set out to create a louder CGM alarm system. By adding “snoozes” so I didn’t drive my co-investigator crazy, we realized I might as well enter what I was doing, and be precise about it (aided by some quick bolus and quick carb buttons that made data-entry not the chore that it sounds). Thus, we had the data and the brains to realize that this made for some great predictions; much better than what you usually see in diabetes tools because they rely only on your insulin sensitivity factor (ISF) and correction rate, but don’t take into account carbs on board and their impact over time, etc.

(If you’re new to #DIYPS, read about the beginnings of it here. For more on this idea of carbs on board and the carbohydrate absorption rate and how significant it is for people with diabetes, read about that here.)

After I had spent 100 days using #DIYPS, Scott and I stopped to look and see what the impact was. For the long version, read this post about the results and the direct comparison to the bionic pancreas trial data that was available then. The short version: #DIYPS reduced my eAG and a1c significantly, reduced lows, reduced highs – aka my time in range was improved from 50% to regularly 80+%.

I have asked myself (and others have asked), are these results sustainable? Are these improved outcomes truly because of #DIYPS? It’s definitely worth noting I never changed what or how I ate. (I ate 120 grams of pizza (for science! ;)) several times to test the system, but I didn’t eat less or any healthier or otherwise change my diet.)
I can’t attribute these outcomes directly to #DIYPS alone, but I do believe they’re highly correlated. It’s hard to separate other contributing factors like the fact that I have more boluses per day using #DIYPS (which other studies have shown decreases a1c); or the fact that I spend less time high/low because with #DIYPS I actually can wake up at night and take action before I’m high or low.
So, it’d be hard to study specific factors and say “it’s all #DIYPS”. But, I’m pretty sure it’s mostly #DIYPS. Regardless, here’s the updated data about the sustainability of the results I’ve seen with #DIYPS over the past year:
Why this is significant
#DIYPS is currently n=1 (meaning one person is the study’s subject). But what is significant is that I have year’s worth of data and actual lab-tested a1cs that shows the outcome of this type of artificial pancreas work. And it (to date, but coming soon  / OMG this week!) hasn’t even been closed loop – I’m still the “human in the loop” making decisions and pushing buttons on my pump.Compared to the bionic pancreas and other artificial pancreas study trials where they have a few days and a few more (usually n=20 or so) subjects; they can look at the decrease in lows and highs and improved eAG…but they can only project what the a1c improvement is going to be.We’ve shown the improvements in lab-tested a1cs – see my graph above?

It all adds up
Scott and I are not the only ones working on a closed loop. The community of developers connected to the Nightscout community has nearly two hands full of people who are working independently on device interoperability to close the loop by freeing our data from devices and enabling us to work with our own algorithms regardless of which hardware device we use to support our diabetes management.When all of these n=1 studies add up, it matters. At some point in the near future, after we’ve closed the loop with #DIYPS (ah! this week! :)) and others have as well, we may have more n=1 hours on closed loop artificial pancreas systems than the (traditional) “researchers”. Scott and I are hoping that we can not only show the world how open source innovation and new regulatory paradigms can deliver safe and effective results for people living with T1D faster than traditional medical device development and traditional regulation; but that we can also change how all successful medical device companies approach interoperability, and how traditional medical researchers do research – possibly in partnership with patient researchers like us.